RBI Bulletin - Jun 25, 2025

JUNE 2025 VOLUME LXXIX NUMBER 6Editorial Committee Indranil Bhattacharyya Anujit Mitra Rekha Misra Anupam Prakash Sunil Kumar Snehal Herwadkar Pankaj Kumar V. Dhanya Shweta Kumari Anirban Sanyal Sujata Kundu Editor Asish Thomas George The Reserve Bank of India Bulletin is issued monthly by the Department of Economic and Policy Research, Reserve Bank of India, under the direction of the Editorial Committee. The Central Board of the Bank is not responsible for interpretation and opinions expressed. In the case of signed articles, the responsibility is that of the author. © Reserve Bank of India 2025 All rights reserved. Reproduction is permitted provided an acknowledgment of the source is made. For subscription to Bulletin, please refer to Section ‘Recent Publications’ The Reserve Bank of India Bulletin can be accessed at https://bulletin.rbi.org.inCONTENTS Bi-monthly Monetary Policy Statement (June 4 - 6, 2025) Governor’s Statement: June 6, 2025 1 Resolution of the Monetary Policy Committee (MPC) June 4 to 6, 2025 7 Speeches Convocation Address at the 58th Convocation, Indian Institute of Technology, Kanpur Shri Sanjay Malhotra 11 Moving the Boundaries of Financial Inclusion- A Regulatory Perspective Shri M. Rajeshwar Rao 15 Articles State of the Economy 21 Financial Conditions Index for India: A High-Frequency Approach 57 Balance Sheet Channel of Monetary Policy Transmission: Insights from Indian Manufacturing Firms 71 Drivers of CD Issuances: An Empirical Assessment 87 Predicting CPI inflation in India: Combining Forecasts from a ‘Suite’ of Statistical and Machine Learning Models 105 Current Statistics 117 Recent Publications 171 Supplement Annual Report 2024-25MONETARY POLICY STATEMENT (JUNE 4-6) 2025-26 Governor’s StatementGovernor’s Statement MONETARY POLICY STATEMENT 2025-26 (JUNE 4-6) Governor’s Statement* strength comes from the strong balance sheets of the five major sectors - corporates, banks, households, Sanjay Malhotra government, and the external sector. Second, there is stability on all three fronts – price, financial, and The 55th meeting of the Monetary Policy political – providing policy and economic certainty Committee (MPC) was held in the backdrop of an early in this dynamically evolving global economic and promising start of the monsoon season, which is of order. Third, the Indian economy offers immense vital significance for the Indian economy. In contrast, opportunities to investors through 3Ds – demography, the global backdrop remains fragile and highly fluid. digitalisation and domestic demand.2 This 5x3x3 The uncertainty around the global economic outlook matrix of fundamentals provides the necessary core has somewhat ebbed since the MPC met in April in strength to cushion the Indian economy against global the wake of temporary tariff reprieve and optimism spillovers and propel it to grow at a faster pace. around trade negotiations. However, it is still high to Decisions of the Monetary Policy Committee (MPC) weaken sentiments and lower global growth prospects. The Monetary Policy Committee (MPC) met on the Accordingly, global growth and trade projections have 4th, 5th and 6th of June to deliberate and decide on been revised downwards by multilateral agencies.1 the policy repo rate. After a detailed assessment of the Moreover, the last mile of disinflation is turning out evolving macroeconomic and financial developments to be more protracted. As growth-inflation trade-off is and the outlook, the MPC decided to reduce the policy becoming more challenging, monetary authorities are repo rate under the liquidity adjustment facility (LAF) charting out a more cautious and carefully calibrated by 50 basis points to 5.50 per cent with immediate policy trajectory. effect; consequently, the standing deposit facility Looking beyond the near-term, growing economic (SDF) rate shall stand adjusted to 5.25 per cent and and financial fragmentation is reshaping the global the marginal standing facility (MSF) rate and the Bank economy. Besides, complex interconnections within Rate to 5.75 per cent. the financial system, elevated debt levels and growing I shall now briefly set out the rationale for these influence of frontier technologies are raising financial decisions. Inflation has softened significantly over stability concerns. Amidst heightened volatility the last six months from above the tolerance band in in capital flows and exchange rates, coupled with October 2024 to well below the target with signs of a constrained policy space, central banks of emerging broad-based moderation. The near-term and medium- market economies have a tougher task to stabilise term outlook now gives us the confidence of not only a their economies against global spillovers. durable alignment of headline inflation with the target In this global milieu, the Indian economy presents of 4 per cent, as exuded in the last meeting but also the a picture of strength, stability, and opportunity. First, belief that during the year, it is likely to undershoot * Governor’s Statement - June 6, 2025. the target at the margin. While food inflation outlook 1 The OECD, in its Economic Outlook released in June 2025, revised down remains soft, core inflation is expected to remain the global growth forecast by 20 basis points to 2.9 per cent for 2025 while benign with easing of international commodity prices the IMF in its April World Economic Outlook lowered the global growth projection to 2.8 per cent for 2025 and 3.0 per cent for 2026—well below the historical average of 3.7 per cent recorded between 2000 and 2019. 2 India: A partner in progress and prosperity; Keynote Address by Furthermore, the WTO now projects world merchandise trade volume to Shri Sanjay Malhotra, Governor, RBI - at the US-India Economic Forum contract by 0.2 per cent in 2025, marking a notable downgrade of nearly 3 organised by the Confederation of Indian Industry (CII) and US India percentage points from earlier forecasts. Strategic Partnership Forum (USISPF), Washington DC; April 25, 2025. RBI Bulletin June 2025 1MONETARY POLICY STATEMENT 2025-26 (JUNE 4-6) Governor’s Statement in line with the anticipated global growth slowdown. 26 so far, domestic economic activity has exhibited The inflation outlook for the year is being revised resilience. Agriculture sector remains strong. With a downwards from the earlier forecast of 4.0 per cent very good harvest in both the kharif as well as rabi to 3.7 per cent. Growth, on the other hand, remains cropping seasons, the supply of major food crops is lower than our aspirations amidst challenging global comfortable.4 The reservoir levels remain healthy.5 environment and heightened uncertainty. The highest procurement of wheat6 in the last four years provides a comforting stock position.7 Industrial Thus, it is imperative to continue to stimulate activity is gaining gradually, even though the pace domestic private consumption and investment of recovery is uneven.8 Services sector is expected through policy levers to step up the growth to maintain momentum.9 PMI services stood strong momentum. This changed growth-inflation dynamics at 58.8 in May 2025, indicating robust expansion in calls for not only continuing with the policy easing activity.10 but also frontloading the rate cuts to support growth. Accordingly, the MPC voted to reduce the policy repo On the demand side, private consumption, the rate by 50 basis points to 5.50 per cent. mainstay of aggregate demand, remains healthy, with a gradual rise in discretionary spending.11 Rural After having reduced the policy repo rate by 100 demand12 remains steady, while urban demand13 bps in quick succession since February 2025, under is improving. Investment activity is reviving as the current circumstances, monetary policy is left with very limited space to support growth. Hence, 4 As per the third advance estimates, the combined kharif and rabi food- the MPC also decided to change the stance from grains production at 354.0 million tonnes in 2024-25 is 6.5 per cent higher than a year ago. accommodative to neutral. From here onwards, the 5 As of June 5, 2025, reservoir levels were at 31.1 per cent of the full MPC will be carefully assessing the incoming data and capacity, above last year’s level of 22.5 per cent and higher than the the evolving outlook to chart out the future course of decadal average of 24.2 per cent. 6 Procurement of wheat as on June 1, 2025 at 298.8 lakh tonnes is 13.3 monetary policy in order to strike the right growth- per cent higher over the last year. inflation balance. The fast-changing global economic 7 As on May 16, 2025, the stocks held by the Food Corporation of India for situation too necessitates continuous monitoring wheat stands at 5.1 times the buffer norms (highest in 4 years) and rice at 4.4 times the buffer norms. and assessment of the evolving macroeconomic 8 IIP during April 2025 expanded at tepid rate of 2.7 per cent despite a outlook. lower base of 4.0 per cent growth in 2024-25. While mining contracted by 0.2 per cent in April, electricity and manufacturing recorded growth of 1.1 Assessment of Growth and Inflation per cent and 3.4 per cent, respectively. Manufacturing PMI for May 2025 moderated to 57.6 but remains well above the long-run average. Growth 9 E-way bills increased strongly by 23.4 per cent in April 2025, while toll collections increased by 16.4 per cent in May 2025. Gross GST collections The provisional estimates released by the rose by a healthy 16.4 per cent in May 2025. Domestic air cargo posted a growth of 16.6 per cent in April. Domestic air passenger traffic grew by 9.7 National Statistical Office (NSO) placed India’s real per cent in April, however moderated to 3.7 per cent in May. Port cargo GDP growth in 2024-25 at 6.5 per cent.3 During 2025- witnessed a growth of 5.6 per cent in April-May 2025. 10 PMI services for May 2025 edged up to 58.8 from 58.7 in April, maintaining a level that reflects the sector’s recent stable and robust 3 Real GDP expanded by 7.4 per cent in Q4:2024-25. Private consumption performance. and gross fixed capital formation (GFCF) grew by 6.0 per cent and 9.4 11 IIP consumer durables expanded by 6.4 per cent in April 2025. per cent, respectively, in Q4:2024-25. For the full year 2024-25, private 12 As per the NielsenIQ’s Retail Audit Service, FMCG sales volume growth consumption and GFCF expanded by 7.2 per cent and 7.1 per cent, in rural areas improved to 8.7 per cent in April 2025 from 8.1 per cent in respectively. On the supply side, gross value added (GVA) expanded by 6.8 March. per cent in Q4:2024-25. Manufacturing rose by 4.8 per cent and services registered growth of 7.9 per cent in Q4. For 2024-25, GVA expanded by 6.4 13 Wholesale passenger vehicle sales and FMCG products sales (urban) per cent. Manufacturing and services sector grew by 4.5 per cent and 7.5 recorded a growth of 5.5 per cent and 4.5 per cent, respectively, during per cent, respectively in 2024-25. April 2025. 2 RBI Bulletin June 2025Governor’s Statement MONETARY POLICY STATEMENT 2025-26 (JUNE 4-6) reflected by high-frequency indicators.14 Merchandise and progress with other countries should provide exports recorded a strong growth in April 2025 after a a fillip to trade in goods and services. Spillovers lacklustre performance in the recent past.15 Non- emanating from protracted geopolitical tensions, and oil, non-gold imports posted a double-digit growth, global trade and weather-related uncertainties pose reflecting buoyant domestic demand conditions.16 downside risks to growth. Taking all these factors Services exports continue on a strong growth into consideration, real GDP growth for 2025-26 is trajectory.17 projected at 6.5 per cent with Q1 at 6.5, Q2 at 6.7, Q3 at 6.6 and Q4 at 6.3 per cent. The risks are evenly Going forward, the outlook for agriculture sector balanced. and rural demand is expected to receive further impetus by the expected above normal southwest Inflation monsoon rainfall.18 On the other hand, sustained CPI headline inflation continued its declining buoyancy in services activity should nurture revival trajectory in March-April, with headline CPI inflation in urban consumption. The healthy balance sheets of moderating to a nearly six-year low of 3.2 per cent banks and corporates; government’s continued thrust (y-o-y) in April 2025. This was led mainly by food on capex;19 elevated capacity utilisation;20 improving inflation, which recorded the sixth consecutive business optimism21 and easing of financial conditions monthly decline. Fuel group witnessed a reversal should help further revive investment activity. Trade of deflationary conditions and recorded positive policy uncertainty however continues to weigh on inflation prints during March and April, partly merchandise exports prospects, while conclusion of reflecting the hike in LPG prices. Core23 inflation free trade agreement (FTA) with the United Kingdom22 remained largely steady and contained during March- April, despite increase in gold prices exerting upward 14 Production and Imports of capital goods rose sharply by 20.3 per cent and 21.5 per cent, respectively, in April 2025. Steel consumption and pressure.24 cement production recorded double-digit growth in Q4:2024-25 before moderating to 6.0 per cent and 6.7 per cent, respectively in the month of The outlook for inflation points towards benign April. prices across major constituents. The record wheat 15 Merchandise exports recorded a growth of 9.2 per cent in April 2025 with non-oil exports growing at a healthy 10.3 per cent. production and higher production of key pulses in 16 Non-oil non-gold imports witnessed a strong growth of 17.3 per cent, the Rabi crop season should ensure adequate supply with overall imports growing at 19.1 per cent. of key food items. Going forward, the likely above 17 Services exports increased by 18.6 per cent during March 2025, on the back of robust software and business exports. However, it moderated to normal monsoon along with its early onset augurs 8.8 per cent in April 2025. well for Kharif crop prospects. Reflecting this, inflation 18 Monsoon landed on coast of Kerala on May 24, 2025, eight days in advance. As per the IMD’s updated long-range forecast, monsoon season expectations are showing a moderating trend, more rainfall is likely to be 106 per cent of the long period average (LPA) with a model error of ±4 per cent. 23 CPI headline excluding food and fuel. 19 As per the Union Budget 2025-26, the central government’s effective capital expenditure (including grants-in-aid for creation of capital assets) 24 CPI headline inflation declined by a cumulative 45 basis points during is budgeted to grow by 17.4 per cent. March-April 2025, from 3.6 per cent in February 2025 to a low of 3.2 per cent in April 2025 – the lowest reading since July 2019. As vegetable prices 20 As per the early results of quarterly order books, inventories, and continued to record a strong seasonal correction, food inflation dropped capacity utilisation (OBICUS) survey of RBI, seasonally adjusted capacity to a 42-month low of 2.1 per cent in April from 3.8 per cent in February utilisation (CU) of manufacturing sector at 75.5 per cent in Q4:2024-25 is 2025. Fuel group, however, exited the deflationary zone, recording an year- above the long-period average of 73.9 per cent. on-year inflation of 1.4 per cent in March 2025 and rose further to 2.9 per 21 PMI manufacturing Future Output Index is at a healthy 63.1in May cent in April 2025. CPI excluding food and fuel inflation also edged up to 2025. Future Output Index has hovered above 60.0 since April 2023. Future 4.2 per cent, year-on-year, in April 2025 after remaining steady at 4.1 per Activity Index of PMI services rebounded in May after declining in April. cent in March 2025. Gold, which has a share of 2.3 per cent within CPI 22 As per the Ministry of Commerce and Industry, 99 per cent of Indian excluding food and fuel, contributed 21.4 per cent to the core inflation in exports to the UK will benefit from this Free Trade Agreement. April 2025. RBI Bulletin June 2025 3MONETARY POLICY STATEMENT 2025-26 (JUNE 4-6) Governor’s Statement so for the rural households.25 Most projections point likely to remain in surplus, counterbalancing the rise towards continued moderation in the prices of key in trade deficit. The CAD for 2025-26 is expected to commodities, including crude oil. Notwithstanding remain well within the sustainable level. these favourable prognoses, we need to remain On the financing side in 2024-25, foreign watchful of weather-related uncertainties and still portfolio investment (FPI) to India dropped sharply evolving tariff related concerns with their attendant to 1.7 billion US$, as foreign portfolio investors impact on global commodity prices. Taking all these booked profits in equities.29 Net foreign direct factors into consideration, and assuming a normal investment (FDI)30 too moderated. It is germane to monsoon, CPI inflation for the financial year 2025-26 point out that this moderation is on account of a rise is now projected at 3.7 per cent, with Q1 at 2.9 per in repatriation and net outward FDI while gross FDI cent; Q2 at 3.4 per cent; Q3 at 3.9 per cent; and Q4 at actually increased by 14 per cent. Rise in repatriation 4.4 per cent. The risks are evenly balanced. is a sign of a mature market where foreign investors can enter and exit smoothly, while high gross FDI External Sector indicates that India continues to remain an attractive With the moderation in trade deficit in Q4:2024- investment destination. External commercial 25, alongside strong services exports26 and remittance borrowings (ECBs) and non-resident deposits, receipts, the current account deficit (CAD) for 2024- on the other hand, witnessed higher net inflows 25 is expected to remain low.27 Furthermore, despite compared to the previous year.31 As on May 30, 2025, rising geopolitical uncertainties and trade tensions, India’s foreign exchange reserves stood at US$ 691.5 India’s merchandise trade remained robust in April billion. These are sufficient to fund more than 11 2025. As imports grew faster than exports, trade months of goods imports32 and about 96 per cent of deficit however widened during the month.28 Going external debt outstanding.33 Overall, India’s external sector remains resilient as key external sector forward, net services and remittance receipts are vulnerability indicators continue to improve.34 We 25 Urban households' perception of the current median inflation declined remain confident of meeting our external financing by 10 basis points (bps) and reached 7.7 per cent, while their inflation requirements. expectations for the next three months remained unchanged at 8.9 per cent. Moreover, their expectation for year ahead reduced by 20 bps to 9.5 per cent. For rural households, the current perception of inflation reduced 29 During 2025-26 so far (up to June 4), foreign portfolio investment (FPI) by 30 basis points (bps) to 6.3 per cent in May 2025 as compared with to India registered net outflows of US$ 2.1 billion. the previous round. Moreover, their year ahead inflation expectation also declined by 40 bps to 8.9 per cent in the latest survey. 30 Gross foreign direct investment (FDI) inflows remained strong, rising by around 14 per cent to US$ 81.0 billion in 2024-25 from US$ 71.3 billion a 26 As per provisional figures, India’s services exports grew by 13.6 per cent year ago. However, net FDI inflows moderated to US$ 0.4 billion in 2024- to US$ 387.5 billion during 2024-25, whereas services imports registered a 25 from US$ 10.1 billion a year ago. growth of 11.4 per cent (US$ 198.7 billion). Net services receipts reached an all-time high of US$ 188.8 during 2024-25. In April 2025, services 31 Net inflows under external commercial borrowings (ECBs) to India exports grew by 8.8 per cent to US$32.8 billion on a y-o-y basis, while increased to US$ 18.7 billion during 2024-25 as compared with US$ 3.6 services imports rose moderately by 0.9 per cent (US$16.9 billion). Net billion a year ago. In April 2025, net ECB to India rose to US$2.8 billion services receipts at US$15.9 billion recorded a y-o-y expansion of 18.8 per from US$0.5 billion a year ago. Non-resident deposits recorded a higher cent. net inflow of US$ 16.2 billion in 2024-25 than US$ 14.7 billion a year ago. 27 India’s current account balance recorded a deficit of 1.1 per cent of GDP 32 Based on actual merchandise imports (on a BoP basis) during the four in Q3:2024-25 lower than 1.8 per cent of GDP in Q2:2024-25. quarters (Q4:2023-24 to Q3:2024-25). 28 India’s merchandise exports expanded for the second consecutive 33 Based on external debt outstanding, as at end-December 2024. month, growing by 9.0 per cent (y-o-y) to US$ 38.5 billion in April 2025. 34 India’s CAD stood at 0.7 per cent of GDP in 2023-24 and 1.1 per Merchandise imports at US$ 64.9 billion expanded by 19.1 per cent (y-o-y) cent during Q3:2024-25 (0.9 per cent in Q1:2024-25 and 1.8 per cent in in April 2025. India’s merchandise trade deficit increased to US$ 26.4 Q2:2024-25). India’s external debt to GDP ratio stood at 19.1 per cent at billion in April 2025 from US$ 19.2 billion a year ago. end-December 2024 from 18.5 per cent at end-March 2024. 4 RBI Bulletin June 2025Governor’s Statement MONETARY POLICY STATEMENT 2025-26 (JUNE 4-6) Liquidity and Financial Market Conditions provide durable liquidity, it has been decided to reduce the cash reserve ratio (CRR) by 100 basis A total amount of ₹9.5 lakh crore of durable points (bps) to 3.0 per cent of net demand and time liquidity was injected into the banking system since liabilities (NDTL) in a staggered manner during the January.35 As a result, after remaining in deficit since course of the year. This reduction will be carried mid-December, liquidity conditions transitioned to out in four equal tranches of 25 bps each with effect surplus at the end of March. This is also evident from from the fortnights beginning September 6, October the tepid response to daily VRR auctions36 and high 4, November 1 and November 29, 2025. The cut in SDF balances – the average daily balance during April- CRR would release primary liquidity of about ₹2.5 May amounted to ₹2.0 lakh crore. lakh crore to the banking system by December 2025. Reflecting the improvement in liquidity Besides providing durable liquidity, it will reduce conditions, the weighted average call rate (WACR) – the cost of funding of the banks, thereby helping in the operating target of monetary policy – traded at the monetary policy transmission to the credit market. lower end of the LAF corridor since the last policy.37 I would like to reiterate that we will continue to The comfortable liquidity surplus in the banking monitor the evolving liquidity and financial market system has further reinforced transmission of policy conditions and proactively take further measures, as repo rate cuts to short term rates.38 However, we are warranted. yet to see a perceptible transmission in the credit Financial Stability market segment, though we must keep in mind that it The system-level financial parameters of happens with some lag.39 Scheduled Commercial Banks (SCBs) continue to The Reserve Bank remains committed to provide be robust.40 The asset quality parameters, liquidity sufficient liquidity to the banking system. To further buffers and profitability parameters have shown further improvement. Credit Deposit ratio for the 35 Open market purchases (including through NDS-OM) injected durable banking system at the end of December 2024 was at liquidity amounting to ₹5.2 lakh crore since January. Additionally, term VRR auctions and USD/INR buy-sell swaps injected liquidity 81.84 per cent, broadly similar to a year ago. Similarly, amounting to ₹2.1 lakh crore and ₹2.2 lakh crore, respectively, during the the system-level parameters of NBFCs too are sound same period. 36 The average bid cover ratio of daily VRRs was 0.26 during April-June (up to June 4). 40 Scheduled Commercial Banks (SCBs) Parameters: The outstanding credit 37 The WACR, on an average, traded 16 bps below the policy repo rate and deposit on a y-o-y basis increased by 11.03 per cent and 10.18 per cent, during April-June (up to June 4) as compared to 6 bps above the repo rate respectively, between March-24 and March-25. The system-level Capital during February-March. to Risk Weighted Assets Ratio (CRAR) of 16.43 per cent in December 2024 38 In response to the policy repo rate cut of 50 bps in the current easing was well above the regulatory minimum level. Ratio of non-performing cycle (up to June 4), the WACR moderated by 70 bps, 3-month T-bill rate loans improved further (GNPA ratio at 2.42 per cent in December 2024 by 88 bps, 3-month CP issued by NBFCs by 143 bps and 3-month CD rate vis-à-vis 2.96 per cent in December 2023, NNPA Ratio at 0.55 per cent in by 138 bps. The compression in CP and CD spreads over T-bill suggests December 2024 vis-à-vis 0.69 per cent in December 2023). SMA-2 ratio, easier financing conditions for banks and corporates. The average CP and the proportion of loans that are overdue by 61–90 days as a share of total CD spread over T-bill moderated from 134 bps and 108 bps, respectively in advances -- a lead indicator of the build-up of fresh stress in the banking March to 82 bps and 65 bps, respectively in May. book – remained stable on a y-o-y basis at 0.96 per cent in December 39 The weighted average lending rate (WALR) on fresh rupee loans and 2024 (0.90 per cent in December 2023). Liquidity buffers were robust, outstanding rupee loans declined by 6 bps and 17 bps, respectively, during with an LCR of 130.21 per cent as of December end 2024. The annualised February-April 2025, reflecting policy rate transmission to lending rates. return on assets (RoA) and return on equity (RoE) stood at 1.37 per The weighted average domestic term deposit rates (WADTDR) on fresh cent and 14.14 per cent, respectively, in December 2024. Net Interest deposits declined by 27 bps, while WADTDR on outstanding deposits Margin was 3.49 per cent for December 2024. (3.64 per cent in declined by 1 bp during February-April 2025. December 2023). RBI Bulletin June 2025 5MONETARY POLICY STATEMENT 2025-26 (JUNE 4-6) Governor’s Statement with comfortable capital position and improved should be seen as a step towards propelling growth to GNPA ratios.41 a higher aspirational trajectory. Here, I would like to highlight that there is The stress witnessed earlier in retail segments like no tussle between price stability and growth in the unsecured personal loans and credit card receivables medium and long term. Price stability preserves portfolio has abated, while the stress in micro-finance purchasing power, imparts certainty to households segment is persisting. Banks and NBFCs active in these and businesses in their savings and investment segments are already recalibrating their business decisions and ensures congenial interest rate and models, strengthening their credit underwriting financial conditions, all of which foster consumption, practices and stepping up their collection efforts to investment and overall activity. Moreover, it is crucial avoid any excessive build-up of risks on this front in for equitable growth and shared prosperity because future. its absence is disproportionately burdensome on the poor. Concluding Remarks I must also add that while price stability is a On both inflation and growth fronts, the Indian necessary condition, it is not sufficient to ensure economy is progressing well and broadly on expected growth. A supportive policy environment is vital. lines. Strong macroeconomic fundamentals and This is even more important during periods of high benign inflation outlook provide space to monetary uncertainties such as the current times. At the Reserve policy to support growth, while remaining consistent Bank, therefore, while price stability remains the focus with the goal of price stability. As global environment of monetary policy, we are not oblivious to putting remains uncertain, it has become even more important in place complementary monetary and credit policies and regulations that support growth and prosperity. to focus on domestic growth amidst sustained price stability. Accordingly, today’s monetary policy actions Thank you. Namaskar and Jai Hind. 41 Non-Bank Financial Companies (NBFCs) Parameters: Total CRAR of NBFCs was 26.22 per cent and Tier I capital of 24.13 per cent in December 2024, well above the minimum regulatory requirements. RoA for the sector, decreased from 3.11 per cent in December 2023 to 2.86 per cent in December 2024. GNPA ratio has improved from 2.70 per cent in December 2023 to 2.53 per cent in December 2024, while NNPA ratio remained almost same at 1.10 per cent in December 2024 as compared to 1.11 per cent in December 2023. 6 RBI Bulletin June 2025MONETARY POLICY STATEMENT (JUNE 4-6) 2025-26 Resolution of the Monetary Policy Committee (MPC) June 4-6, 2025Monetary Policy Statement, 2025-26 MONETARY POLICY STATEMENT 2025-26 (JUNE 4-6) Monetary Policy Statement, According to the provisional estimates released by the National Statistical Office (NSO) on May 30, 2025-26 Resolution of the 2025, real GDP growth in Q4:2024-25 stood at 7.4 per Monetary Policy Committee cent as against 6.4 per cent in Q3. On the supply side, real gross value added (GVA) rose by 6.8 per cent in (MPC)* Q4:2024-25. For 2024-25, real GDP growth was placed at 6.5 per cent, while real GVA recorded a growth of Monetary Policy Decisions 6.4 per cent. The Monetary Policy Committee (MPC) held Going forward, economic activity continues to its 55th meeting from June 4 to 6, 2025 under the maintain the momentum in 2025-26, supported by chairmanship of Shri Sanjay Malhotra, Governor, private consumption and traction in fixed capital Reserve Bank of India. The MPC members Dr. Nagesh formation. The sustained rural economic activity Kumar, Shri Saugata Bhattacharya, Prof. Ram Singh, bodes well for rural demand, while continued Dr. Poonam Gupta and Dr. Rajiv Ranjan attended the expansion in services sector is expected to support meeting. the revival in urban demand. Investment activity After assessing the current and evolving is expected to improve in light of higher capacity macroeconomic situation, the MPC voted to reduce utilization, improving balance sheets of financial and the policy repo rate by 50 basis points (bps) to 5.50 non-financial corporates, and government’s capital per cent with immediate effect. Consequently, the expenditure push. Trade policy uncertainty continues standing deposit facility (SDF) rate under the liquidity to weigh on merchandise exports prospects, while adjustment facility (LAF) shall stand adjusted to 5.25 the conclusion of free trade agreement (FTA) with the per cent and the marginal standing facility (MSF) rate United Kingdom and progress with other countries and the Bank Rate to 5.75 per cent. This decision is is supportive of trade activity. On the supply side, in consonance with the objective of achieving the agriculture prospects remain bright on the back of medium-term target for consumer price index (CPI) an above normal south-west monsoon forecast and inflation of 4 per cent within a band of +/- 2 per cent, resilient allied activities. Services sector is expected while supporting growth. to maintain its momentum. However, spillovers Growth and Inflation Outlook emanating from protracted geopolitical tensions, and global trade and weather-related uncertainties pose The uncertainty around the global economic downside risks to growth. Taking all these factors into outlook has ebbed somewhat since the MPC met in April in the wake of temporary tariff reprieve and account, real GDP growth for 2025-26 is projected at optimism around trade negotiations. However, it 6.5 per cent, with Q1 at 6.5 per cent, Q2 at 6.7 per continues to remain elevated to weaken sentiments cent, Q3 at 6.6 per cent, and Q4 at 6.3 per cent (Chart and lower global growth prospects. Accordingly, 1). The risks are evenly balanced. global growth and trade projections have been CPI headline inflation continued its declining revised downwards by multilateral agencies. Market trajectory in March and April, with headline CPI volatility has eased in the recent period with equity inflation moderating to a nearly six-year low of 3.2 markets staging a recovery, dollar index and crude oil per cent (year-on-year) in April 2025. This was led softening though gold prices remain high. mainly by food inflation which recorded the sixth * Released on June 6, 2025. consecutive monthly decline. Fuel group witnessed RBI Bulletin June 2025 7MONETARY POLICY STATEMENT 2025-26 (JUNE 4-6) Monetary Policy Statement, 2025-26 a reversal of deflationary conditions and recorded cent; Q2 at 3.4 per cent; Q3 at 3.9 per cent; and Q4 at positive inflation prints during March and April, 4.4 per cent (Chart 2). The risks are evenly balanced. partly reflecting the hike in LPG prices. Core inflation Rationale for Monetary Policy Decisions remained largely steady and contained during March- Inflation has softened significantly over the last April, despite increase in gold prices exerting upward six months from above the tolerance band in October pressure. 2024 to well below the target with signs of a broad- The outlook for inflation points towards benign based moderation. The near-term and medium-term prices across major constituents. The record wheat outlook now gives us the confidence of not only a production and higher production of key pulses in durable alignment of headline inflation with the target the Rabi crop season should ensure adequate supply of 4 per cent, as exuded in the last meeting but also the of key food items. Going forward, the likely above belief that during the year, it is likely to undershoot normal monsoon along with its early onset augurs well the target at the margin. While food inflation outlook for Kharif crop prospects. Reflecting this, inflation remains soft, core inflation is expected to remain expectations are showing a moderating trend, more benign with easing of international commodity prices so for the rural households. Most projections point in line with the anticipated global growth slowdown. towards continued moderation in the prices of key The inflation outlook for the year is being revised commodities, including crude oil. Notwithstanding downwards from the earlier forecast of 4.0 per cent these favourable prognoses, we need to remain to 3.7 per cent. Growth, on the other hand, remains watchful of weather-related uncertainties and still lower than our aspirations amidst challenging global evolving tariff related concerns with their attendant environment and heightened uncertainty. impact on global commodity prices. Taking all these factors into consideration, and assuming a normal Thus, it is imperative to continue to stimulate monsoon, CPI inflation for the financial year 2025-26 domestic private consumption and investment is now projected at 3.7 per cent, with Q1 at 2.9 per through policy levers to step up the growth 8 RBI Bulletin June 2025 tnec reP Chart 1: Quarterly Projection of Real GDP Growth (y-o-y) 14 12 10 8 6 4 2 0 50 per cent CI 70 per cent CI 90 per cent CI CI - Confidence Interval 32-2202:1Q 32-2202:2Q 32-2202:3Q 32-2202:4Q 42-3202:1Q 42-3202:2Q 42-3202:3Q 42-3202:4Q 52-4202:1Q 52-4202:2Q 52-4202:3Q 52-4202:4Q 62-5202:1Q 62-5202:2Q 62-5202:3Q 62-5202:4Q Chart 2: Quarterly Projection of CPI Inflation (y-o-y) 50 per cent CI 70 per cent CI 90 per cent CI CI - Confidence Interval tnec reP 10 8 6 4 2 0 32-2202:1Q 32-2202:2Q 32-2202:3Q 32-2202:4Q 42-3202:1Q 42-3202:2Q 42-3202:3Q 42-3202:4Q 52-4202:1Q 52-4202:2Q 52-4202:3Q 52-4202:4Q 62-5202:1Q 62-5202:2Q 62-5202:3Q 62-5202:4QMonetary Policy Statement, 2025-26 MONETARY POLICY STATEMENT 2025-26 (JUNE 4-6) momentum. This changed growth-inflation dynamics the MPC also decided to change the stance from calls for not only continuing with the policy easing accommodative to neutral. From here onwards, the but also frontloading the rate cuts to support growth. MPC will be carefully assessing the incoming data Accordingly, the MPC voted to reduce the policy repo and the evolving outlook to chart out the future rate by 50 bps to 5.50 per cent. Dr. Nagesh Kumar, course of monetary policy in order to strike the right Prof. Ram Singh, Dr. Rajiv Ranjan, Dr. Poonam Gupta growth-inflation balance. The fast-changing global and Shri Sanjay Malhotra, voted to decrease the policy economic situation too necessitates continuous monitoring and assessment of the evolving repo rate by 50 bps. Shri Saugata Bhattacharya voted macroeconomic outlook. for a 25 bps cut in repo rate. The minutes of the MPC’s meeting will be After having reduced the policy repo rate by 100 published on June 20, 2025. bps in quick succession since February 2025, under the current circumstances, monetary policy is left The next meeting of the MPC is scheduled from with very limited space to support growth. Hence, August 4 to 6, 2025. RBI Bulletin June 2025 9SPEECHES Convocation Address at the 58th Convocation, Indian Institute of Technology, Kanpur Shri Sanjay Malhotra Moving the Boundaries of Financial Inclusion- A Regulatory Perspective Shri M. Rajeshwar RaoConvocation Address by Shri Sanjay Malhotra, Governor, Reserve Bank of India at the 58th Convocation, Indian Institute of Technology, Kanpur, June 23, 2025 Convocation Address at the 58th Convocation, Indian Institute of Technology, Kanpur SPEECH Convocation Address at the 58th IIT. I still vividly remember my first day at IIT when my mother came to drop me with another batchmate. Convocation, Indian Institute of I recollect my days at Hall III and then Hall I, the Technology, Kanpur* healthy rivalry between Hall II and Hall III, phatta cricket, bulla, the various celebrations at Red Rose Shri Sanjay Malhotra Restaurant on the campus and Chung Fa restaurant in the city, movies at L7, DEC 10 of which we were Chairman of the Board of Governors, Director so proud, the iconic library, Culfest and the many of the Institute, Prof and Padma Shree Manindra friends that I made and treasure till date. The steel Agrawal, winner of numerous awards, who was my trunk which carried my belongings to IIT and which senior here and who I hold in very high esteem, faculty my loving wife has preserved till date is still with members, staff, proud parents, family and friends of me. I still have my Wilson tennis racket, with which the graduating students, distinguished guests, and my I religiously played every evening at the clay courts dear graduating students. on campus. IITK has a special place in my heart. This convocation ceremony is even more special as I did Today marks the culmination of an exciting not attend our convocation ceremony; in fact, we did chapter for the graduating students, where you not have a proper convocation ceremony, perhaps the have not only learnt new things – academic and only batch not to have it. So, it’s an honour to be back extra-curricular – but have also had an enjoyable here after thirty-six long years in a new and privileged and memorable experience. I extend a very warm role and be a part of the convocation ceremony today. congratulations to all the graduating students. Please Thank you, IIT, for this honour. give yourselves a huge round of applause. Times have changed a lot since I graduated. To the parents and guardians, this moment belongs But there are certainly lessons which endure time. as much to you as it does to your children and wards. As a fellow-alumnus, roll number 85213, who has Your innumerable sacrifices, continuous support, experienced life after campus, I will speak about four unconditional love and unwavering encouragement learnings from my journey. have laid the foundation upon which these young achievers now stand. I know this is an emotional and Learning for Life proud moment for you. I have myself experienced Many of you would have got your dream jobs. these emotions when my sons graduated – one from Others, who plan to pursue further studies, would get IIT Bombay and the other from IIT Guwahati. My them soon. With a degree from a prestigious institute warmest congratulations to you as your ward steps and a good job in hand, please don’t think that you into a new chapter in life. have arrived. The moment you think you have arrived, Dear graduates, it is a special day for you as you you will stagnate. The moment you believe you know enter a new and exciting phase of life. It is an equally everything, you will stop growing. special day for me and doubly so. First, this institute This is just the beginning, only the first step. The has had a transformational impact on me, my life and degree has only laid a solid foundation and will take my thoughts. I remember with nostalgia my years at you thus far. You will need to build from here. You * Convocation Address by Shri Sanjay Malhotra, Governor, Reserve Bank will need to learn when you change sectors, move of India at the 58th Convocation, Indian Institute of Technology, Kanpur, June 23, 2025. across organisations within a sector, take up different RBI Bulletin June 2025 11SPEECH Convocation Address at the 58th Convocation, Indian Institute of Technology, Kanpur roles within an organization and even within the our interventions. He had long and diverse experience same role in an organisation. Technology is advancing across organisations. at a lightning speed. What you learnt yesterday would He challenged the forging units there to reduce be outdated tomorrow as new ideas and tools emerge the time taken in changing a die from about eight daily. hours to less than an hour. All of them including I can assure you that the institute has prepared the most advanced, productive and efficient forging you well for your life ahead. It has not only imparted units vehemently denied the possibility of reducing you with knowledge which will be of immense use the time. When he failed after many days of trying but, more importantly, equipped you with the most to convince them to improve, he suggested some important tool – the tool of self-learning. changes including installation of a video camera. This was tried in a unit. These small changes reduced the Like other IAS officers, I worked in diverse fields time to five hours. When asked, the supervisor, apart like urban management, land resources, industries, from other things, explained that the work started on power, health, taxation, banking, finance, etc. Many time, as scheduled; no one was late; no one took an of them were general management but many were unscheduled tea break; all required equipment were highly technical and specialized, which had a steep pre-arranged and kept ready for use; there was no learning curve. The IITK emphasis on basic sciences wastage of time. The small changes and videography and core engineering subjects, its importance to the did the trick as everyone was being watched. What fundamentals of a subject, its priority to deriving followed was a series of improvements or what are the formulae rather than merely memorizing and called kaizens, not only in the exchange of dies, applying them, its attention to problem-solving from but also various other processes – forging, grinding, first principles, and various other methods of problem electroplating, packaging, etc, as every process was solving have held me in good stead. IIT gave me the questioned. We ended up reducing costs by about 10%. necessary tools for self-learning. I am sure it has given I learnt to question the status quo. I learnt that you too the same tools. there is always scope for improvement. This helped So, continue your quest for knowledge. me improve efficiency in various organisations and Remember that learning is for life. The moment one departments that I worked in. It helped in reducing is not learning, it is a signal that one is not growing; processing time of files. I reduced turnaround times one is not advancing. It is knowledge which will keep for applications. It helped me make changes in laws, you ahead of others. Its importance cannot be over- rules and procedures for the benefit of citizens and emphasized. I urge you all, as Stephen Covey said, government alike, as I questioned the status quo. to continuously sharpen your saw and cut the grass As Albert Einstein famously said, “The important under your feet. thing is not to stop questioning.” When you question Question the status quo the status quo and ask questions, you open the door My second learning pertains to the period to new ideas and fresh perspectives. It is fuel for between 2003 and 2006, when I was working in the innovation; it drives you to explore, experiment, and United Nations. I was managing a project to improve create something better. So, no matter where you productivity in the hand tools clusters in India. We are in life or your career, never stop questioning the hired a Total Quality Management expert for some of status quo and improving. 12 RBI Bulletin June 2025Convocation Address at the 58th Convocation, Indian Institute of Technology, Kanpur SPEECH Pursue virtuous Karma results. It is the path that one chooses that broadly determines the destination. Today, I appreciate how The third learning pertains to my tenure as true Steve Jobs was when he said, “You can’t connect Secretary, Department of Personnel in the Government the dots looking forward; you can only connect them of Rajasthan in 2007-08. Promotions from the state looking backward.” Right now, you may not fully grasp civil service to the IAS were plagued with disputes how your karma - each late-night lab session, each and court cases. For almost about 20 years, no one frustrating bug, and each decision that you take - will was promoted to the IAS. My predecessors did not impact your journey. You may not appreciate, how take up this issue as they thought it would be an delayed gratification, the hallmark of all great leaders, exercise in futility as some aggrieved officer will will deliver bigger success over the longer term for the approach the doors of the judiciary. When I was instant rewards foregone. But trust me, over time, the given responsibility for this department, I took up dots will connect and it will be in large measure due the gauntlet. I studied all the disputes and judicial to your karma. pronouncements meticulously; decided on claims of seniority and promotion, without fear or favour; Trust finalized and published the seniority lists; and after My last learning is from the student days in IIT, spending months on this mammoth exercise, sent when we were always short of money and under debt. the proposals to UPSC for promotion. Just when we Food at the mess was as good as it can be. We relied were about to convene the meeting for promotion, heavily on the hostel canteen. A samosa at that time one officer again approached the court and got a stay. costed 35 paise and a bottle of Thums Up 2 rupees and Months of my hard work was brought to nought. Even 25 paise. The canteen was managed by a person called though many officers commended me for the hard Lala. Lala was loved by everyone. He would serve us till work and getting the matter so close to finalization, I late in night and very generously gave us credit. Even was disappointed. outside hostel, we got credit from the juice vendor, I had to leave for Princeton for my masters within the shops in Shopping Centre, etc. This may not be a few days and could not pursue the case in the courts. surprising. Lala knew us, recognizing us as hostelers. After I returned, I was put in a different department. Other vendors too recognized us as students from the In a few years, the court lifted the stay. I was asked campus. What was surprising though was that we got if I would be interested in giving finishing touches credit even from some shopkeepers in Kanpur, who to the work I had initiated. Once bitten, twice shy, did not know us at all. Why did these shopkeepers I did not take up the challenge this time. The work give credit to us? It is because of their trust in the IIT was completed by another officer. In recognition of students. his efforts, he was conferred with the state award for It is because people do business with people civil service. they trust. Trust is the foundation on which any I realized I did not follow my karma as I feared relationship is built, whether it is marriage, friendship, failure. I realized I needed to follow my karma boldly or at workplace - between the CEO and the employees, and decisively without bothering about the results. or between a company and its consumers. Without going in to details of my journey It is trust in a person that makes him a leader; it thereafter, today, as I look back, I can confidently say is trust which makes people follow a leader. Integrity that it is karma that largely determines outcomes and and ethics are paramount to develop trust. It is not RBI Bulletin June 2025 13SPEECH Convocation Address at the 58th Convocation, Indian Institute of Technology, Kanpur easy to gain trust. To earn trust, a leader must have yourselves proud - proud by living lives of character, the courage to take difficult decisions. He must act in ethics and humility; lives filled with purpose, service the interest of the employees and other stakeholders. and impact. As you step into tomorrow, carry with you He must be willing to accept responsibility. He must the spirit of this institution, carry with you the love lead by example. He must possess the humility to of your families, and carry with you the dreams of a learn from his mistakes. He must be just, transparent billion Indians who believe in your potential. and respectful. Trust takes time to build. But it is easy Your journey of transformation began here at IIT to lose trust. To be a successful person, a successful Kanpur. Now, transform the world as leaders who leader, graduating students, try to gain trust and are trustworthy; who continue learning for life; who having gained it, preserve trust. question the status quo and who pursue virtuous Your time to shine karma. To conclude, dear graduating students, as you May God bless you with all the very best in your leave this campus today, have confidence in yourself. journey ahead. Dream big, but more importantly, act on those Thank you. dreams. Make IIT Kanpur proud. Make your parents proud. Make India proud. But most importantly, make Jai Hind. 14 RBI Bulletin June 2025Moving the Boundaries of Financial Inclusion- A Regulatory Perspective SPEECH Moving the Boundaries of enable shared economic development. It also can dissuade the disadvantaged and low-income segments Financial Inclusion- of society from seeking out informal options that A Regulatory Perspective* renders them vulnerable to financial distress, debt, and poverty. Shri M. Rajeshwar Rao History of Financial Inclusion in India Given the theme for today’s discourse, it would Distinguished guests, participants, ladies and be worthwhile to set the historical context regarding gentlemen, Good evening. financial inclusion in India. While the financial At the outset, let me thank the organisers for inclusion initiatives in our country can in many inviting me to share some of my thoughts on the ways be traced back to the 1950s, with significant theme of financial inclusion. Before that, let me take a developments ensuing in the subsequent decade, moment to acknowledge that today i.e., June 05, 2025, it was the National Credit Council meeting of July is the World Environment Day, an UN-recognized 1968 that paved the way for framing of Priority Sector day that brings together people across the globe in a Lending (PSL) guidelines, nationalisation of select shared mission to safeguard and restore our planet. private banks in July 1969 and launch of the Lead Bank This year’s theme of ending plastic pollution is a call Scheme in December 1969 that were the precursors to all of us to make a behavioural shift in our daily life of this journey. The branch expansion policy adopted choices. In the spirit of preserving the purity of our by RBI during the 1970s, which required a specific environment and safeguarding our well-being, let us number of branches to be opened in rural areas for commit toward making more sustainable choices. every branch opened in urban areas, became the Coming back to our theme for the day, let me foundation for expanding the reach of banking begin by stating the obvious that financial inclusion services that we see today. Besides, the experiments is not just a policy objective but a collective obligation with group-based lending towards the turn of the last and responsibility for all stakeholders in the financial century and proliferation of microfinance institutions ecosystem. The importance of the theme can be have also helped link the unserved section of the underscored by the fact that at least seven out of the population with the formal banking system. seventeen United Nations Sustainable Development Interestingly, the above initiatives were taken Goals of 2030 view financial inclusion as a key enabler during a period when the term ‘financial inclusion’ for achieving sustainable development worldwide by was not prevalent in the country. The first reference improving the quality of lives of poor and marginalized to the term was made in RBI’s Annual Policy sections of the society. It is seen as a way to bridge the Statement for the Year 2005-06 by Dr Y.V. Reddy1, gap between the privileged and the under-privileged the then Governor of the Reserve Bank of India, who and a way to bring people out of poverty. An inclusive highlighted ‘financial exclusion’ that resulted due to financial system has the potential to reduce income certain banking practices. Banks were then urged to inequality and poverty, promote social cohesion and review their existing practices to align them with the objective of financial inclusion, leading to the genesis * Address delivered by Shri M Rajeshwar Rao, Deputy Governor, Reserve Bank of India on June 05, 2025, at HSBC's event for Financial Inclusion in Mumbai. Inputs provided by Jyoti Prakash Sharma, Jignasa Morthania 1 Annual Policy Statement for the Year 2005-06 by Dr. Y. Venugopal Reddy, and Yash Goel are gratefully acknowledged. Governor, Reserve Bank of India. RBI Bulletin June 2025 15SPEECH Moving the Boundaries of Financial Inclusion- A Regulatory Perspective of ‘no frills’ account, which are now known as Basic shown reasonable improvement, but there is a scope Savings Bank Deposit Accounts. for improvement in some aspects. Financial Inclusion in Indian Context Current Scenario The first step in promoting financial inclusion is To get a perspective on the current scenario, it understanding its nuances, which are as dynamic and would be worthwhile to dwell a bit on some of the diverse as the Indian economy itself, and thereafter recent developments in the journey of financial outline its ambit in the Indian context. Given its multi- inclusion in the country. Several policy measures faceted nature, various organisations and jurisdictions towards furthering financial inclusion have been have defined financial inclusion in different ways. In undertaken from time to time, but it was the launch India, the formal definition of financial inclusion2 was of Pradhan Mantri Jan Dhan Yojana (PMJDY) that given in January 2008 by the Committee on Financial became the watershed moment in this journey. The Inclusion chaired by Dr C Rangarajan as “the process Jan Dhan Yojana – Aadhar – Mobile i.e., JAM trinity of ensuring access to financial services and timely and provided a quantum leap in our endeavour to ensure adequate credit where needed by vulnerable groups access to banking services for all adults, making it such as weaker sections and low-income groups at the world’s largest financial inclusion program. As of an affordable cost”. Reflecting the priorities of that May 21, 20254, 55.44 crore Jan Dhan accounts, 56% time, the definition focused largely on the access of which belong to women, have over ₹2.5 lakh crore to financial services. Currently we have a scenario, worth of deposits, which speaks volumes about the where more than 95% households have access to a impact of the scheme. The provision of universal bank account3, which reflects remarkable progress access to bank accounts has not only increased the potential reach of other financial services but has on one out of three parameters of Financial Inclusion also enabled frictionless delivery of welfare programs Index developed by the Reserve Bank to measure the to the targeted segment through adoption of Direct extent of financial inclusion in the country. Benefit Transfer (DBT). While there has been a significant progress in Digital Payments expanding the banking reach, it is also important to ensure that inherent barriers to a gamut of financial Access to a bank account is a prerequisite products and services are eliminated and usage for availing other financial services, and a robust of these services expands to various segments of payments and settlements system is an indispensable yet underserved and un-served population in the enabler for proliferation of formal financial services. country. Efforts towards making financial services Over the past decade, the fundamentals of banking accessible become futile if they are not used by the have changed with the advent of digital modes intended population or are used without appropriate of banking like net banking and mobile banking awareness of its risks and benefits. Thus, the other as well as digital payments systems like Unified two parameters of RBI’s financial inclusion index, Payment Interface (UPI). In FY 2024-25, digital viz., usage and quality of the financial services cannot payments surged 35% Y-o-Y by volume to 60.81 crore be overlooked while defining or measuring financial transactions per day, with UPI accounting for 83.73% inclusion. Over the last few years this index has of such transactions5. The extraordinary uptake of UPI 2 Report of the Committee on Financial Inclusion. 4 https://pmjdy.gov.in/account 3 National Family Health Survey (NFHS - 5), 2019–21. 5 As per Reserve Bank of India’s Annual Report for 2024-25. 16 RBI Bulletin June 2025Moving the Boundaries of Financial Inclusion- A Regulatory Perspective SPEECH stands as a testament to the power of collaborative Recent Regulatory Initiatives and use-case-driven innovation in driving financial The RBI has been sensitive to need to bring about inclusion. A particularly compelling example of this improvement in the financial inclusion in the country. transformation can be seen in the informal sector— Some of the measures taken recently in this regard where today a street vendor or pop-up store owner include raising the limit for collateral-free agriculture nonchalantly places a QR code at the fore and receives loans to ₹2 lakh per borrower, enhancing various payment for services without any hassle for cash and loan limits under PSL, expansion of the list of eligible quietly integrating himself into the formal financial borrowers under the category of ‘Weaker Sections’ system with dignity and ease. alongwith removal of existing cap on loans by UCBs For further expanding and deepening the digital to women beneficiaries. The scope of co-lending is payments ecosystem in the country, a Payments proposed to be broadened by expanding the list of Infrastructure and Development Fund has been permitted regulated entities (REs) that can enter a co- constituted to encourage deployment of payment lending arrangement and extending the same beyond acceptance infrastructure. Further, all State and PSL loans. A comprehensive review of the Lead Bank Union Territory Level Bankers’ Committees have Scheme is also underway with an objective to enhance been advised to identify districts and assign them to the effectiveness and impact of the scheme. designated banks, with an endeavour to make these With respect to digital payments, permissible districts 100 per cent digitally enabled. The objective transaction limit on UPI Lite has been revised in FY is to provide every eligible individual in the identified 2025 from ₹500 to ₹1000 and on UPI 123PAY from district at least one mode of digital payments viz., ₹5,000 to ₹10,000 to encourage their wider adoption. cards, net banking, UPI, AEPS6, etc. It is understood Further, with a view to promote digital payments that as on March 31, 2025, 514 districts across 15 among individuals without bank accounts, UPI Circle states and 6 UTs are 100 percent digitally enabled. has been introduced which allows a secondary user to This marks a significant milestone in our journey make UPI transactions up to a limit from the primary towards a digitally inclusive economy. user’s bank account in a secure manner. Besides, RBI’s Financial Inclusion Index in an effort to enhance ease of access to digital infrastructure for persons with disabilities, payment RBI’s financial inclusion index, which captures system participants (PSPs) have been advised to the extent of financial inclusion across the country, review their payment systems and devices and carry with four iterations published till date, has increased out necessary modifications so that all such systems from 60.1 in March 2023 to 64.2 in March 2024, and devices can be easily accessed and used by persons showing a Y-o-Y increase of 6.82 per cent. While with disabilities. the progress is appreciable, credit gaps still exist in the system which may be attributed amongst Financial Literacy others to a lack of documentation available with the Meaningful financial inclusion also requires individuals/ entities in the informal system and of access and awareness in right proportions for awareness regarding the various government schemes. ensuring responsible and equitable service delivery There is as such a need to make concerted efforts to of financial services. Therefore, financial literacy fill them. and financial inclusion need to be considered as 6 Aadhaar Enabled Payment System. two sides of the same coin – promoting financial RBI Bulletin June 2025 17SPEECH Moving the Boundaries of Financial Inclusion- A Regulatory Perspective inclusion without adequate financial literacy would on-year increase7 in FY2023-24. This raises questions lead to underutilization of financial services and on the products, practices, and handling of grievances increased chances of errors and frauds. Conversely, at the level of the RE. REs, therefore, need to analyse educating the consumers without facilitating their the gaps and strengthen their processes to reverse the access to the formal financial system would result trend of increasing grievances. into unmet demand for financial services. The Mis-selling efforts towards augmenting financing literacy have While financial inclusion entails a bouquet of been institutionalised by setting up of the National financial services, pushing the same indiscriminately Centre of Financial Education (NCFE) jointly by the to unaware consumers may be detrimental to their financial sector regulators. RBI as a regulator has been well-being and undermine its stated intent. There at the forefront of financial literacy with the launch are reports of mis-selling of financial services of annual Financial Literacy Week campaigns targeted such as insurance products. The concern is that at specified sections of the population. Financial awareness empowers borrowers to assess and such mis-selling without regard to suitability and understand financial products, thereby supporting appropriateness would beget distrust in schemes informed decision-making. To facilitate informed aimed at providing a safety net to the low-income decision making by the customers and enhance households by creating artificial boundaries. We transparency by the lenders, the RBI has mandated are examining whether it necessitates framing of that all REs provide a standardised disclosure of key guidelines to address mis-selling of financial products terms and conditions in the form of Key Fact Statement and services by REs. (KFS) to all retail and MSME borrowers. Cyber Safety and Digital Literacy Challenges As digitalization becomes more pervasive, the Even as all the stakeholders in the financial need for increasing digital literacy becomes even more system, including the regulator and the REs, pronounced. Empowering individuals to use digital play their part in advancing financial inclusion, devices and platforms with confidence and security certain issues that act as impediments to the efforts is essential to ensuring inclusive participation in made in this regard have come to the fore and will the digital economy. Often, apprehensions related need to be addressed. Let me briefly highlight a few to uncertainty, the possibility of errors, or financial such issues. loss create psychological barriers that hinder the adoption of technological solutions such as ATMs, Grievance Redressal mobile banking, and other digital services. The Having an effective grievance redressal mechanism rising incidents of frauds through novel techniques is non-negotiable for financial sector enterprises makes it imperative that REs collaborate with other as non-resolution of consumer’s concerns not only stakeholders like SROs, NGOs, etc. to generate leads to erosion of customer base but also results awareness and promote safe digital practices among in loss of trust in the broader financial system and customers. deters new consumers from entering the system. It is At the same time, it is critical for REs to implement concerning that the complaints received at the Offices effective measures to combat digital frauds. One such of RBI Ombudsmen as well as Centralized Receipt and Processing Centres (CRPCs) marked a sharp 33% year- 7 Table 1.1 of the Annual Report of Ombudsman Scheme, 2023-24. 18 RBI Bulletin June 2025Moving the Boundaries of Financial Inclusion- A Regulatory Perspective SPEECH area warranting attention is the use of One-Time lenders having access to low-cost funds have been Passwords (OTPs) as a means of Additional Factor found to be charging margins significantly higher than Authentication (AFA). While this method has served the rest of the industry and which in several instances well in the past, the evolving threat landscape in the appear to be excessive. The lenders should look arena of cybersecurity now calls for the development beyond the conventional “high-yielding business” and adoption of more secure and resilient alternatives. tag for the sector and approach it with an empathic Further, REs must diligently adopt the designated 160 and developmental perspective, recognising the socio- number series8 for all service and transactional voice economic role that microfinance plays in empowering calls as prescribed by the Government. This initiative is vulnerable communities. critical to maintaining the integrity of communication The frequency of disruptions in the microfinance channels and protecting customers from phishing and sector has increased of late. Incidents of high borrower other forms of cyber-attacks. indebtedness, coupled with coercive recovery RBI has been running extensive multimedia practices, sometimes lead to tragic consequences. It is awareness campaigns using audio-visual messages in the collective interest of all stakeholders that such under the name ‘RBI Kehta Hai’ and text messages as disruptions are pre-emptively addressed and avoided. ‘RBI Says’. Further, RBI has introduced the bank.in and In this regard, REs must also enhance their credit fin.in domains exclusively for banks and non-bank appraisal frameworks to prevent over-leveraging entities to curb cyber security threats and malicious of borrowers. Additionally, they must eschew any activities. Also, to aid the customers in verifying Digital coercive or unethical recovery practices, ensuring that Lending Apps’ (DLAs) association with RE, the RBI has financial services are delivered in a manner that is created a public repository of DLAs deployed by the both responsible and sustainable. While the business REs which will soon be available on RBI’s website. model may be sound, the organisational structure and the incentive schemes framed to deliver the services Developments in Microfinance may be flawed resulting in perverse outcomes for Let me now focus on a few developments in customers. This calls for an introspection around the Microfinance sector. Microfinance has placed itself models. as a promising avenue for providing formal financial Way Forward services to the excluded sections of population. While microfinance has played an important role in Even as we reflect on some of these challenges, financial inclusion, there are some issues which need we need to be clear about the path that we must attention. The sector continues to suffer from vicious take to ensure greater financial inclusion. As we cycle of over-indebtedness, high interest rates and look to the future, the way forward for financial harsh recovery practices. While some moderation in inclusion lies in the strategic deployment of emerging interest rates charged on microfinance loans has been technologies to build a more accessible, equitable, and efficient financial ecosystem. Innovations such observed in recent quarters, pockets of high interest as AI, blockchain, and digital public infrastructure rates and elevated margins continue to persist. Even are revolutionizing how financial services are 8 To address the issue of unsolicited and spam calls from telemarketers, delivered, especially to the underserved and remote Department of Telecommunications (DoT) has allocated the 160-numbering series for solely making service and transactional calls to be used by banks, communities. One such innovation in this space is the financial institutions, and other service providers, to keep away from the use of the 140-numbering series that was allocated to telemarketers. Account Aggregator (AA) framework. By empowering RBI Bulletin June 2025 19SPEECH Moving the Boundaries of Financial Inclusion- A Regulatory Perspective individuals to securely share their financial data stability. As connectivity can pose challenges in remote with consent, the AA system enables more accurate and rural areas, REs can explore the development of credit assessments and potentially facilitates the lightweight mobile applications and web interfaces delivery of customized financial products. Building optimised for low-bandwidth environments. These on this foundation, the Unified Lending Interface measures will go a long way in extending the reach (ULI) standardizes and streamlines the digital lending of digital financial services to the last mile, thereby process by providing lenders with a host of alternate ensuring inclusive and accessible banking for all. data including digitised state land records, milk A lot has been achieved in the journey for achieving pouring data and satellite data. It’s RBI’s belief that financial inclusion thus far, yet a lot more needs to the JAM trinity will be followed by the new trinity of be done. It cannot be merely achieved by standalone JAM-UPI-ULI in revolutionizing digital infrastructure policy initiatives but by implementation of such and credit delivery and provide necessary fillip to initiatives both in letter and spirit by all stakeholders financial inclusion efforts, pushing it to new highs. in the financial ecosystem. Also, those who remain The development and implementation of India outside the ambit of formal finance today represent Stack has revolutionised the banking landscape in untapped potential that can meaningfully contribute India and has been instrumental in furthering financial to economic growth in the future. The dividends of inclusion by reducing infrastructural, geographical, such inclusion will not only accrue to the institutions and linguistic frictions and plugging leakages. REs involved but will also strengthen the foundation of have been encouraged to innovate in product design, a more resilient, equitable, and prosperous society. offering solutions that reflect the unique needs of Financial inclusion should not be viewed as an act their customer base; for instance, offering flexibility in of philanthropy, but rather as a strategic investment repayment schedules, variable savings contributions, in the nation’s economic and social development. and locally tailored financial products shaped by With the right mix of well thought of and carefully seasonal income cycles, occupational patterns, or crafted regulation, technological advancement, and behavioural tendencies. Such customisation can go institutional empathy, our collective efforts can a long way in further improving access, usage, and dismantle longstanding barriers and usher in a new quality of financial services. REs can bring some of era of inclusive and sustainable financial growth – these innovations under the theme neutral ‘On Tap’ one that leaves no citizen behind and resonates far Regulatory Sandbox framework, which provides a beyond set boundaries. structured environment for testing state-of-the-art solutions in the interest of consumers and financial Thank you. 20 RBI Bulletin June 2025ARTICLES State of the Economy Financial Conditions Index for India: A High-Frequency Approach Balance Sheet Channel of Monetary Policy Transmission: Insights from Indian Manufacturing Firms Drivers of CD Issuances: An Empirical Assessment Predicting CPI inflation in India: Combining Forecasts from a ‘Suite’ of Statistical and Machine Learning ModelsState of the Economy ARTICLE State of the Economy* also intensified. While food prices softened, non-food commodity prices have shown volatile movements The global economy is in a state of flux, reeling from accentuated by geopolitical tensions. Crude oil prices the twin shocks of trade policy uncertainties and a spike surged since June 13 on renewed tensions in the in geo-political tensions. In this state of elevated global Middle East while gold prices also rallied on safe- uncertainty, various high-frequency indicators for May haven demand. In contrast, the US dollar witnessed a 2025 point towards resilient economic activity in India depreciating trend, hitting a three-year low on June 12 across the industrial and services sectors. Agriculture following tariff uncertainty and fiscal debt concerns. showed a broad-based increase in production across Since June 13, the US dollar, however, strengthened most major crops during 2024-25. The domestic prices somewhat in response to rising geo-political risks. situation remains benign with headline inflation staying Headline inflation rates among Advanced Economies below the target for the fourth consecutive month in May. (AEs) and Emerging Markets and Developing Financial conditions remained conducive to facilitate an Economies (EMDEs) showed marked variations in efficient transmission of rate cuts to the credit market. their trajectories during April-May, driven mostly by country-specific factors. Amidst heightened concerns Introduction on their domestic growth outlook, several central The global economy is in a state of flux, reeling banks utilised the headroom provided by lower from the twin shocks of trade policy uncertainties inflation prints to further reduce policy rates. and a spike in geo-political tensions. The optimism On the domestic front, the provisional estimates from a temporary tariff freeze and trade deals has released in May have reaffirmed growth to be 6.5 per kept financial market sentiments buoyed in May and cent in 2024-25, with a significant sequential pick- early-June 2025. However, following the outbreak of up in Q4. Various high-frequency indicators for May the Iran-Israel conflict, heightened uncertainty and volatility have once again gripped financial markets. point to signs of resilient economic activity across Meanwhile, the OECD and World Bank reports the industrial and services sector. In fact, among the released in June have reaffirmed the possibility of countries surveyed for the Purchasing Managers’ a marked deterioration in the medium-term global Index (PMI), overall expansion in activity was the economic prospects amidst rising trade barriers and highest in India with the expansion in new export restrictions. orders witnessed in May being an outlier, amidst contraction seen in other major economies. Capacity Reflecting the trade policy uncertainties, high- utilisation by manufacturing firms remained above frequency indicators on global manufacturing activity its long-period average. High-frequency indicators of for the month of May contracted for the second aggregate demand for May also suggested a pick-up in consecutive month. Global supply chain pressures rural demand, especially given the strong performance * This article has been prepared by Rekha Misra, Asish Thomas George, of the agricultural sector. Forward-looking surveys Shashi Kant, Shahbaaz Khan, Biswajeet Mohanty, Durga G, Yamini Jhamb, Harshita Keshan, Harendra Kumar Behera, Sanjana Sejwal, Satyarth Singh, of consumer sentiments show stable consumer Aayushi Khandelwal, Amrita Basu, Radhika Singh, Love Kumar Shandilya, Prashant Kumar, Sritama Ray, Shivam, Parul Arora, Ashish Santosh confidence for the current period and improved Khobragade, Ayushi Agarwal, Shreya Bhan, Shubham Agnihotri, Avnish Kumar, Supriyo Mondal, Yuvraj Kashyap, Amit Pawar, Rajas Saroy and optimism about the future.1 All of these indicate Samridhi. The guidance and comments provided by Dr. Poonam Gupta, Deputy Governor, is gratefully acknowledged. Peer review by Pallavi Chavan, Snehal S Herwadkar, Joice John and Pawan Gopalakrishnan 1 Reserve Bank of India’s Urban Consumer Confidence Survey (UCCS) is also acknowledged. Views expressed in this article are those of the and Rural Consumer Confidence Survey (RCCS) for May 2025 (Annex Chart authors and do not represent the views of the Reserve Bank of India. A1 and A2). RBI Bulletin June 2025 21ARTICLE State of the Economy considerable resilience of the Indian economy, commercial borrowing (ECB) inflows continued to be notwithstanding the global economic, trade, and geo- healthy, although it moderated from March. Overall, political uncertainties. financial conditions remained conducive to facilitate an efficient transmission of rate cuts to the credit Domestic inflation remains benign with headline market. The external sector continued to be robust, inflation remaining below the target for the fourth with adequate forex reserve cover for imports and consecutive month in May. Record domestic crop external debt. production in 2024-25 agricultural season is translating into a sharp and sustained easing of food price Set against this backdrop, the remainder of the article is structured into four sections. Section II inflation. Steady core [Consumer Price Index (CPI) covers the rapidly evolving developments in the excluding food and fuel] inflation, with indications of global economy. Section III provides an assessment some softening after excluding the impact of volatile of domestic macroeconomic conditions. Section IV and elevated gold and silver prices, indicates that encapsulates financial conditions in India, while underlying inflationary pressures remain muted. Section V presents the concluding observations. Equity markets registered modest gains during May-June, notwithstanding fluctuating movements II. Global Setting caused by global cues on economic outlook, tariff- Global economic prospects remained fragile even related news and the evolving domestic scenario. as economic and financial uncertainty receded from With the flaring up of geopolitical tensions in the their heightened levels in April buoyed by optimism Middle East, the equity market registered a brief emanating from the US tariff freeze and bilateral trade sharp fall before witnessing a significant rebound deals (Chart II.1). Since June 13, however, uncertainty on June 20. Although credit growth decelerated in once again loomed large over the macroeconomic April – notably in the agriculture and services sectors landscape in the wake of renewed geopolitical – non-bank sources of credit, including external turbulence in the Middle East. Chart II.1: Uncertainty Indicators a. Economic Uncertainty b. Global VIX (Index) (Index) 8000 560 500.3 7000 480 6000 5000 5846.7 400 4000 320 3000 240 2000 160 1000 0 80 Sources: Chicago Board Options Exchange; and www.PolicyUncertainty.com. 22 RBI Bulletin June 2025 42-naJ 42-raM 42-yaM 42-luJ 42-peS 42-voN 52-naJ 52-raM 52-yaM 50 45 40 35 30 25 20.3 20 15 10 Trade Policy Uncertainty Index Economic Policy Uncertainty Index (RHS) 42-naJ-4 42-beF-11 42-raM-02 42-rpA-72 42-nuJ-4 42-luJ-21 42-guA-91 42-peS-62 42-voN-3 42-ceD-11 52-naJ-81 52-beF-52 52-rpA-4 52-yaM-21 52-nuJ-02State of the Economy ARTICLE The OECD’s Economic Outlook released in also been projected to decelerate to 1.8 per cent in June 2025 revised the global GDP growth forecast 2025, marking a downward revision of 1.3 percentage to 2.9 per cent for both 2025 and 2026. The growth points from the previous release. forecasts are lower from their March release by 20 The global composite PMI expanded to 51.2 basis points (bps) for 2025 and 10 bps for 2026. This in May, albeit at a modest pace. While global PMI revision stemmed from the assumption that bilateral services showed an expansion led by the business tariff regimes, as in mid-May, would persist unaltered services sector, the global manufacturing PMI throughout the remainder of 2025 and into 2026. The contracted for the second successive month in May deteriorating economic prospects were most acutely to a five-month low of 49.6 (Table II.2). Export orders visible for North America and parts of Asia, notably across manufacturing and services remained in the China (Table II.1). Moreover, the World Bank in its contraction zone for the second consecutive month in latest Global Economic Prospects (GEP), projected May. global GDP growth (using PPP weights) to decelerate In May 2025, there were marked variations in the to 2.9 per cent in 2025 but recover marginally to 3.0 global composite PMI readings across jurisdictions. per cent in 2026. The cumulative decline of 50 bps in While the US and the UK showed an improvement in projections [30 bps in 2025 and 20 bps in 2026] has business conditions, the Eurozone and Japan reported been primarily attributed to increased trade tensions a moderation (Chart II.2a). The significant expansion and heightened policy uncertainty. Global trade has in new export orders for India was an exception, Table II.1: GDP Growth Projections – Select AEs and EMDEs Organisation OECD World Bank Projection for 2025 2026 2025 2026 Month of Projection March June March June January June January June World* 3.1 2.9 3.0 2.9 3.2 2.9 3.2 3.0 Advanced Economies 1.7 1.2 1.8 1.4 US 2.2 1.6 1.6 1.5 2.3 1.4 2.0 1.6 UK 1.4 1.3 1.2 1.0 Euro Area 1.0 1.0 1.2 1.2 1.0 0.7 1.2 0.8 Japan 1.1 0.7 0.2 0.4 1.2 0.7 0.9 0.8 Emerging Market and Developing Economies 4.1 3.8 4.0 3.8 Russia 1.3 1.0 0.9 0.7 1.6 1.4 1.1 1.2 Emerging and Developing Asia India# 6.4 6.3 6.6 6.4 6.7 6.3 6.7 6.5 China 4.8 4.7 4.4 4.3 4.5 4.5 4.0 4.0 Latin America and the Caribbean 2.5 2.3 2.6 2.4 Mexico -1.3 0.4 -0.6 1.1 1.5 0.2 1.6 1.1 Brazil 2.1 2.1 1.4 1.6 2.2 2.4 2.3 2.2 Middle East and North Africa 3.4 2.7 4.1 3.7 Saudi Arabia 3.8 1.8 3.6 2.5 3.4 2.8 5.4 4.5 Sub-Saharan Africa 4.1 3.7 4.3 4.1 South Africa 1.6 1.3 1.7 1.4 1.8 0.7 1.9 1.1 Notes: 1. *: Projections by the World Bank are PPP weighted. 2. #: India’s data is on a fiscal year basis (April-March), while for all other countries it is for calendar years. Sources: OECD Economic Outlook, June 2025; and Global Economic Prospects, World Bank, June 2025. RBI Bulletin June 2025 23ARTICLE State of the Economy Table II.2: Global Purchasing Managers’ Index May-24 Jun-24 Jul-24 Aug-24 Sep-24 Oct-24 Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 PMI Composite 53.7 52.9 52.5 52.9 51.9 52.3 52.4 52.6 51.8 51.5 52.1 50.8 51.2 PMI Manufacturing 51 50.8 49.7 49.6 48.7 49.4 50.1 49.6 50.1 50.6 50.3 49.8 49.6 PMI Services 54 53.1 53.3 53.9 52.9 53.1 53.1 53.8 52.2 51.5 52.7 50.8 52.0 PMI Export Orders 50.6 49.7 49.6 49.0 48.5 48.9 49.3 48.7 49.6 49.7 50.1 47.5 48.0 PMI Export Orders: 50.4 49.3 49.4 48.4 47.5 48.3 48.6 48.2 49.4 49.6 50.1 47.3 48.0 Manufacturing PMI Export Orders: 51.0 50.7 50.6 50.8 51.6 50.7 51.4 50.4 50.2 50.2 50.1 48.3 47.9 Services 50 <<<<<<Contraction---------------------------------------------------------------Expansion>>>>>> Notes: 1. The Purchasing Managers’ Index (PMI), a diffusion index, captures the change in each variable compared to the prior month, noting whether each has risen/improved, fallen/deteriorated or remained unchanged. A PMI value >50 denote expansion; <50 denote contraction; and =50 denote ‘no change’. 2. Heat map is applied on data from April 2023 till May 2025. The map is colour coded–red denotes the lowest value, yellow denotes 50 (or the no change value), and green denotes the highest value in each of the PMI series. Source: S&P Global. with most major economies continuing to record a per cent month-on-month (m-o-m) in May, primarily contraction (Chart II.2b). driven by a decline in the prices of vegetable oil, sugar, and cereals (Chart II.3a). High frequency commodity Commodity prices continued their downward price data for June indicate a sharp pick-up in crude movement in May 2025, as indicated by both the Bloomberg Commodity Index and the World Bank oil prices from their end-May levels on account of Commodity Price Index. This downtrend was aided by escalating geopolitical tensions between Russia and lower food prices that offset an uptick in energy and Ukraine, as well as intensifying conflict between Israel industrial metal prices. Food prices2 moderated by 0.8 and Iran. Copper prices also saw an uptick in June, Chart II.2: Purchasing Managers’ Index: Comparison across Jurisdictions a. S&P Global Composite PMI b. PMI Export Orders (Index) (Index) 60 55 50 45 40 May-25 Apr-25 May-25 Apr-25 Note: A level of 50 indicates no change in activity, while a reading above 50 signals expansion and below 50 suggests contraction. Source: S&P Global. 2 Measured by the FAO’s Food Price Index. 24 RBI Bulletin June 2025 aidnI SU ylatI aissuR niapS ailartsuA KU enozoruE napaJ anihC ecnarF lizarB gnoK gnoH ynamreG adanaC labolG 60 55 50 45 40 35 aidnI ailartsuA ylatI ynamreG aissuR SU enozoruE ecnarF napaJ niapS modgniK detinU anihC adanaCState of the Economy ARTICLE Chart II.3: Commodity and Food Prices a. Commodity and Food Indices b. Gold - Copper - Brent Crude Oil Index (Jan 2024=100) Index (Jan 2024=100) 110 108.5 105 101.4 100 95 91.1 90 Bloomberg commodity index Food price index World Bank Commodity Price Index Sources: Bloomberg; World Bank Pink Sheet; and FAO. aided by US-China trade truce and speculation over Recent readings of inflation point to diverging potential US import duties on the metal. Gold prices trajectories in AEs as well as EMEs. While inflation have remained elevated so far in June, bolstered by in the Euro area moderated to below target in May safe-haven demand amidst concerns about mounting supported by lower energy prices, inflation in US debt and geopolitical risks (Chart II.3b). Amidst the UK edged up while that in Japan and the US ongoing trade tensions, the Global Supply Chain continued to remain sticky and above the target due Pressure Index (GSCPI) rose above its historical to pressures from inflation in the services sector average levels to 0.19 in May 2025 suggesting some (Chart II.4a). Among EMEs, while CPI inflation in stress in supply chain (Annex Chart A3). Brazil and Russia remained elevated above the target RBI Bulletin June 2025 25 42-naJ 42-beF 42-raM 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 160 165.6 145 130 116.8 115 99.5 100 85 70 Gold Copper Brent Crude oil 42-naJ-50 42-beF-21 42-raM-12 42-rpA-82 42-nuJ-50 42-luJ-31 42-guA-02 42-peS-72 42-voN-40 42-ceD-21 52-naJ-91 52-beF-62 52-rpA-50 52-yaM-31 52-nuJ-02 Chart II.4: Headline Inflation a. AEs b. EMEs (Per cent) (Per cent) 4.0 3.5 3.5 3.4 3.0 2.5 2.1 2.0 1.9 1.5 1.0 Brazil Russia China US (PCE) UK Euro area Japan South Africa India Sources: Bloomberg; and OECD. 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 10 9.9 9 8 7 6 5 5.3 4 2.8 3 2.8 2 1 0 -0.1 -1 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaMARTICLE State of the Economy rate, China continued to experience deflation amidst on concerns regarding higher near-term inflation and weak domestic demand and persistent employment increased term premia on account of the worsening uncertainty. Inflation in South Africa remained below US fiscal outlook, while EME spreads widened amidst target (Chart II.4b and Annex Chart A4). increased risk-off sentiment (Chart II.5b). In June (up to June 20, 2025), yields in the US remained volatile as In May, global equity markets regained their lost rising geopolitical tensions also resulted in higher safe ground, buoyed by improved sentiments on signs of de- haven demand. EME spreads continued to increase escalation of trade tensions and upbeat earnings report on intensifying geopolitical tensions. The US dollar (Chart II.5a). The uptrend continued in early June, supported by the announcement of a breakthrough in appreciated somewhat in the first half of May, fuelled trade negotiations between the US and China. With by a US–China tariff suspension but shed gains uncertainties receding from its heightened level of subsequently on growth slowdown fears and fiscal April, global VIX exhibited a decline in May, though concerns. In June (up to June 20, 2025), weak signals, punctuated with sporadic upticks within a tight range. emerging from the Institute for Supply Management However, the rally in global equities was subsequently (ISM) PMI, labour market and lower-than-expected CPI capped by a resurgence in geopolitical risks. The in the US, have continued to exert bearish pressure on global VIX also increased from around mid-June. the dollar though some appreciation was witnessed Yields on US government securities hardened in May after the Israel-Iran conflict on safe haven demand Chart II.5: Global Financial Markets a. Equity Indices (MSCI) b. Government Bond Yields (Index) (Per cent, left scale; index, right scale) 125 122.6 122.3 120 119.1 115 110 105 100 95 World AEs EMEs US Govt Bonds JPMorgan EMBI Global Spread (RHS) c. Currency Indices d. Portfolio Flows to EMEs (Index, left scale; Index, right scale) (US$ billion) MSCI EME currency index Dollar index (RHS) Debt Equity Total Sources: Bloomberg; and IIF. 26 RBI Bulletin June 2025 42-naJ-50 42-beF-21 42-raM-12 42-rpA-82 42-nuJ-50 42-luJ-31 42-guA-02 42-peS-72 42-voN-40 42-ceD-21 52-naJ-91 52-beF-62 52-rpA-50 52-yaM-31 52-nuJ-02 5.0 114 112.9 110 4.5 4.4 106 4.0 102 3.5 98 42-naJ-50 42-beF-21 42-raM-12 42-rpA-82 42-nuJ-50 42-luJ-31 42-guA-02 42-peS-72 42-voN-40 42-ceD-21 52-naJ-91 52-beF-62 52-rpA-50 52-yaM-31 52-nuJ-02 1,840 106 1,820 1831.0 104 1,800 102 1,780 100 1,760 1,740 98 96.1 1,720 96 1,700 94 42-naJ-50 42-beF-21 42-raM-12 42-rpA-82 42-nuJ-50 42-luJ-31 42-guA-02 42-peS-72 42-voN-40 42-ceD-21 52-naJ-91 52-beF-62 52-rpA-50 52-yaM-31 52-nuJ-02 10 5 0 -5 -0.6 -11.2 -10 -11.8 -15 -20 -25 42-naJ-5 42-beF-21 42-raM-12 42-rpA-82 42-nuJ-5 42-luJ-31 42-guA-02 42-peS-72 42-voN-4 42-ceD-21 52-naJ-91 52-beF-62 52-rpA-5 52-yaM-31 52-nuJ-02State of the Economy ARTICLE (Chart II.5c). Mirroring the dollar movement, the to persistent domestic inflation, raising the policy rate MSCI EME Currency Index has increased since May, to a near 20-year high. with equity markets recording inflows; however, a III. Domestic Developments reversal in trend has been witnessed since mid-June Amidst elevated global trade uncertainty, the (Chart II.5d). Indian economy remained resilient, registering the In the monetary policy meetings conducted during highest growth among the world’s major economies, May-June 2025, most central banks continued to with the latest estimates for Q4:2024-25 indicating a lower policy rates amidst heightened macroeconomic sharp pick-up in momentum. uncertainties. Among AEs, New Zealand and South Korea reduced their policy rates by 25 bps in May Aggregate Demand while ECB and Sweden reduced their policy rates by 25 The provisional estimates (PE) of national income bps in their June meetings. Switzerland also reduced released by the National Statistical Office (NSO) its key rate in June by 25 bps to zero amidst domestic on May 30, 2025 placed India’s real gross domestic deflation. On the other hand, Canada, Japan, the UK, product (GDP) growth at 6.5 per cent for 2024-25, and the US maintained status quo on policy rates in same as the second advance estimates (SAE). The dual June amidst uncertain macroeconomic outlook (Chart engines of India’s growth–private final consumption II.6). Several EME central banks undertook policy expenditure (PFCE) and gross fixed capital formation easing to support growth. In May, Indonesia and (GFCF)–contributed 4 percentage points and 2.4 South Africa reduced their policy rates by 25 bps each, percentage points, respectively, to GDP growth. while Mexico pared its benchmark interest rate by 50 bps. In June so far, Philippines cut its benchmark In terms of the quarterly trajectory, the Indian rate by 25 bps. In contrast, Brazil delivered 25 bps rate economy registered a growth of 7.4 per cent in hike in June, following a 50 bps increase in May due Q4:2024-25, notably higher than 6.4 per cent recorded Chart II.6: Policy Rates Type Countries RBI Bulletin June 2025 27 22-naJ 32-naJ 42-naJ 52-naJ 52-yaM 5202.60.02 Australia 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Canada 0 0 0 1 0 1 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1 0 -1 0 0 0 0 0 0 Euro area 0 0 0 0 0 0 1 0 1 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 Japan 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Advanced New Zealand 0 0 0 1 1 0 1 1 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1 -1 0 0 -1 0 0 0 0 Economies South Korea 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Sweden 0 0 0 0 0 0 1 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 Switzerland 0 0 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 United Kingdom 0 0 0 0 0 0 0 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 United States 0 0 0 0 1 1 1 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 Brazil 0 2 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 -1 -1 0 -1 -1 0 -1 -1 0 0 0 0 0 0 0 1 1 1 0 1 0 1 0 China 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 India 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1 Indonesia 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Emerging Malaysia 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Market Economies Mexico 0 1 1 0 1 1 0 1 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1 -1 0 -1 0 Philippines 0 0 0 0 0 0 1 1 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Saudi Arabia 0 0 0 0 1 1 1 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 South Africa 0 0 0 0 1 0 1 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Thailand 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Rate Change < -0.75 -0.75 to -0.50 -0.50 to -0.25 -0.25 to 0 0 to 0.25 0.25 to 0.50 0.50 to 0.75 > 0.75 Source: Bloomberg.ARTICLE State of the Economy (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:20)(cid:29)(cid:3)(cid:58)(cid:72)(cid:76)(cid:74)(cid:75)(cid:87)(cid:72)(cid:71)(cid:3)(cid:38)(cid:82)(cid:81)(cid:87)(cid:85)(cid:76)(cid:69)(cid:88)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:87)(cid:82)(cid:3)(cid:42)(cid:39)(cid:51)(cid:3)(cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75) (cid:523)(cid:19)(cid:135)(cid:148)(cid:133)(cid:135)(cid:144)(cid:150)(cid:131)(cid:137)(cid:135)(cid:3)(cid:146)(cid:145)(cid:139)(cid:144)(cid:150)(cid:149)(cid:524) (cid:21)(cid:19) (cid:20)(cid:24) (cid:25)(cid:17)(cid:23) (cid:26)(cid:17)(cid:23) (cid:20)(cid:19) (cid:25)(cid:17)(cid:24) (cid:24)(cid:17)(cid:25) (cid:24) (cid:19) (cid:16)(cid:24) (cid:16)(cid:20)(cid:19) (cid:52)(cid:20) (cid:52)(cid:21) (cid:52)(cid:22) (cid:52)(cid:23) (cid:52)(cid:20) (cid:52)(cid:21) (cid:52)(cid:22) (cid:52)(cid:23) (cid:21)(cid:19)(cid:21)(cid:22)(cid:16)(cid:21)(cid:23) (cid:21)(cid:19)(cid:21)(cid:23)(cid:16)(cid:21)(cid:24) (cid:51)(cid:85)(cid:76)(cid:89)(cid:68)(cid:87)(cid:72)(cid:3)(cid:73)(cid:76)(cid:81)(cid:68)(cid:79)(cid:3)(cid:70)(cid:82)(cid:81)(cid:86)(cid:88)(cid:80)(cid:83)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:72)(cid:91)(cid:83)(cid:72)(cid:81)(cid:71)(cid:76)(cid:87)(cid:88)(cid:85)(cid:72) (cid:42)(cid:82)(cid:89)(cid:72)(cid:85)(cid:81)(cid:80)(cid:72)(cid:81)(cid:87)(cid:3)(cid:73)(cid:76)(cid:81)(cid:68)(cid:79)(cid:3)(cid:70)(cid:82)(cid:81)(cid:86)(cid:88)(cid:80)(cid:83)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:72)(cid:91)(cid:83)(cid:72)(cid:81)(cid:71)(cid:76)(cid:87)(cid:88)(cid:85)(cid:72) (cid:50)(cid:87)(cid:75)(cid:72)(cid:85)(cid:86) (cid:42)(cid:85)(cid:82)(cid:86)(cid:86)(cid:3)(cid:73)(cid:76)(cid:91)(cid:72)(cid:71)(cid:3)(cid:70)(cid:68)(cid:83)(cid:76)(cid:87)(cid:68)(cid:79)(cid:3)(cid:73)(cid:82)(cid:85)(cid:80)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81) (cid:49)(cid:72)(cid:87)(cid:3)(cid:72)(cid:91)(cid:83)(cid:82)(cid:85)(cid:87)(cid:86) (cid:42)(cid:39)(cid:51)(cid:3)(cid:11)(cid:92)(cid:16)(cid:82)(cid:16)(cid:92)(cid:3)(cid:74)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75)(cid:15)(cid:3)(cid:83)(cid:72)(cid:85)(cid:3)(cid:70)(cid:72)(cid:81)(cid:87)(cid:12) (cid:49)(cid:82)(cid:87)(cid:72)(cid:29)(cid:3)(cid:50)(cid:87)(cid:75)(cid:72)(cid:85)(cid:86)(cid:3)(cid:76)(cid:81)(cid:70)(cid:79)(cid:88)(cid:71)(cid:72)(cid:3)(cid:70)(cid:75)(cid:68)(cid:81)(cid:74)(cid:72)(cid:3)(cid:76)(cid:81)(cid:3)(cid:86)(cid:87)(cid:82)(cid:70)(cid:78)(cid:15)(cid:3)(cid:89)(cid:68)(cid:79)(cid:88)(cid:68)(cid:69)(cid:79)(cid:72)(cid:86)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:86)(cid:87)(cid:68)(cid:87)(cid:76)(cid:86)(cid:87)(cid:76)(cid:70)(cid:68)(cid:79)(cid:3)(cid:71)(cid:76)(cid:86)(cid:70)(cid:85)(cid:72)(cid:83)(cid:68)(cid:81)(cid:70)(cid:76)(cid:72)(cid:86)(cid:17)(cid:3) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:29)(cid:3)(cid:49)(cid:54)(cid:50)(cid:17) in the preceding quarter. The pick-up in growth was High-frequency indicators for May present mixed mainly driven by fixed investment, which increased signals on aggregate demand. Urban demand showed signs of moderation as passenger vehicle sales sharply to 9.4 per cent from a low of 5.2 per cent in the declined with a sharp drop in entry-level segment. preceding quarter, owing to a sustained momentum in However, rural demand improved as evident from construction activity. Despite a challenging external the increase in the retail sales of two-wheelers.3 environment, the contribution of net exports to GDP During May 2025, household demand for work under was the highest since Q2:2020-21. The contribution of the Mahatma Gandhi National Rural Employment PFCE and government final consumption expenditure Guarantee Scheme (MGNREGS) picked up, following (GFCE), however, moderated (Chart III.1). the pursuit of alternative avenues for employment Table III.1: High-frequency Indicators–Rural and Urban Demand–Growth Rate May-24 Jun-24 Jul-24 Aug-24 Sep-24 Oct-24 Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 Urban Domestic Air Passenger Traffic 5.9 6.9 7.6 6.7 7.4 9.6 13.8 10.8 14.1 12.1 9.9 9.7 3.7 Demand Retail Passenger Vehicle Sales -1.0 -6.8 10.2 -4.5 -18.8 32.4 -13.7 -2.0 15.5 -10.3 6.3 1.6 -3.1 Retail Automobile Sales 2.6 0.7 13.8 2.9 -9.3 32.1 11.2 -12.5 6.6 -7.2 -0.7 3.0 5.1 Rural Retail Tractor sales -1.1 -28.4 -11.9 -11.4 14.7 3.1 29.9 25.8 5.2 -14.5 -5.7 7.6 2.8 Demand MGNREGA: Work Demand -14.3 -21.7 -19.5 -16.0 -13.4 -7.6 3.9 8.2 14.4 2.8 2.2 -6.5 4.5 Retail Two-wheeler Sales 2.5 4.7 17.2 6.3 -8.5 36.3 15.8 -17.6 4.2 -6.3 -1.8 2.3 7.3 <<Contraction ------------------------------------------------------------------------------------------ Expansion>> Notes: 1. The y-o-y growth (in per cent) has been calculated for all indicators. 2. Heat map, applied on data from April 2023 till May 2025, translates the data range for each indicator into a colour gradient scheme with red denoting the lowest values and green corresponding to the highest values of the respective data series. 3. The data on Domestic Air Passenger Traffic for May 2025 growth rate is calculated by aggregating daily data. Sources: Airports authority of India; Federation of Automobile Dealers Associations (FADA); and Ministry of Rural Development, GoI. 3 The retail sales of two-wheelers in rural areas increased by 9.9 per cent as compared to 3.6 per cent in urban areas in May, 2025 (FADA press release). 28 RBI Bulletin June 2025State of the Economy ARTICLE in the pre-sowing lean agricultural period and an with 14 per cent of firms reporting increased payrolls increase in MGNREGS wage rates (Table III.1). (Table III.2). Employment indicators in May 2025 present a Overall economic activity remained robust in mixed picture. As per monthly Periodic Labour Force May 2025, with key high-frequency indicators like Survey (PLFS), the all-India unemployment rate rose E-way bills, Goods and Services Tax (GST) revenue, toll collections, and digital payments showing to 5.6 per cent in May from 5.1 per cent last month, strong growth (Table III.3). GST revenue collections with a sharper increase in rural vis-à-vis urban areas. surpassed the ₹2 lakh crore mark for the second Increase in unemployment was partly driven by consecutive month in May, boosted by import-related seasonal agricultural patterns and extreme heat in GST receipts.5 Petroleum consumption expanded some regions, limiting outdoor work.4 Organised job for the first time in the last four months, driven by listings, as per the Naukri JobSpeak Index, moderated petrol. Unseasonal rains and premature onset of – dragged down by information technology (IT), retail, monsoon, however, led to a reduction in electricity and banking and financial services – while sectors demand.6 like insurance, real estate, oil and gas and emerging Government Finances technologies recorded growth. However, the PMI employment diffusion indices signalled strong job The provisional accounts (PA) for 2024-25 creation in organised manufacturing and services, released on May 30, 2025, confirmed that the fiscal Table III.2: High-frequency Indicators–Employment–Growth Rate May-24 Jun-24 Jul-24 Aug-24 Sep-24 Oct-24 Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 Unemployment rate 5.1 5.6 (PLFS: All-India) Unemployment rate 4.5 5.1 (PLFS: Rural) Unemployment rate 6.5 6.9 (PLFS:Urban) Naukri JobSpeak Index -1.8 -7.6 11.8 -3.4 6.0 10.0 2.0 8.7 3.9 4.0 -1.5 8.9 0.3 EPFO Net pay roll 17.2 -6.2 -5.8 -11.2 -16.2 -50.6 -9.0 -23.4 -17.6 -14.2 1.2 addition PMI Employment: 53.4 54.1 53.7 53.5 52.1 53.3 52.9 53.4 54.8 54.5 53.4 54.2 54.9 Manufacturing PMI Employment: 53.5 53.7 53.5 53.1 53.4 54.3 56.6 55.5 56.3 56.2 52.5 53.9 57.1 Services <<Contraction ------------------------------------------------------------------------------------------ Expansion>> Notes: 1. The y-o-y growth (in per cent) has been calculated for all indicators (except for PMI). 2. The heat map translates the data range for each indicator into a colour gradient scheme with red denoting the lowest values and green corresponding to the highest values of the respective data series. 3. Heat map is applied on data from April 2023 till May 2025, other than for EPFO Net Pay roll addition, where the data is till March 2025. 4. All PMI values are reported in index form. A PMI value >50 denote expansion; <50 denote contraction; and =50 denote ‘no change’. In the PMI heat maps, red denotes the lowest value, yellow denotes 50 (or the no change value), and green denotes the highest value in each of the PMI series. 5. All PLFS indicators are in Usual Status and for persons aged 15 years and above. Sources: Ministry of Statistics and Program Implementation (MoSPI), GoI; S&P Global; Employees’ Provident Fund Organisation and Info edge. 4 https://www.mospi.gov.in/sites/default/files/press_release/Press_note_MB05_Monthly_bulletin%20-Final_1.pdf 5 https://economictimes.indiatimes.com/news/economy/finance/gst-collections-jump-16-4-to-rs-2-01-lk-cr-in-may/articleshow/121547915. cms?from=mdr 6 https://www.thehindu.com/business/Industry/spot-electricity-prices-declined-substantially-in-may-amid-reduced-demand-indian-energy-exchange/ article69655753.ece RBI Bulletin June 2025 29ARTICLE State of the Economy Table III.3: High-frequency Indicators–Economic Activity–Growth Rate May-24 Jun-24 Jul-24 Aug-24 Sep-24 Oct-24 Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 GST E-way Bills 17 16.3 19.2 12.9 18.5 16.9 16.3 17.6 23.1 14.7 20.2 23.4 18.9 GST Revenue 10 7.6 10.3 10 6.5 8.9 8.5 7.3 12.3 9.1 9.9 12.6 16.4 Toll Collection 3.6 5.8 9.4 6.8 6.5 7.9 11.9 9.8 14.8 18.7 11.9 16.6 16.4 Electricity Demand 13.6 8 4 -5 -0.8 -0.4 3.7 5.1 1.3 2.4 5.7 2.8 -4.4 Petroleum Consumption 1.9 2.3 10.7 -3.1 -4.4 4.1 10.6 2 3 -5.2 -3.1 0 1.1 Of which: Petrol 3.4 4.6 10.5 8.6 3 8.7 9.6 11.1 6.7 5 5.7 5 9.2 Diesel 2.4 1 4.5 -2.5 -1.9 0.1 8.5 5.9 4.2 -1.3 0.9 4.3 2.2 Aviation Turbine Fuel 10.9 10.1 9.6 8.1 10.4 9.4 8.5 8.7 9.4 4.2 5.7 3.9 4.3 Digital Payments – Volume 40.1 40.6 36.7 34.9 36.3 40.3 30.1 33.1 33.0 26.7 30.8 30.0 27.5 Digital Payments – Value 18.6 13.5 22.1 16.7 21.5 27.5 9.5 19.6 18.6 9.5 17.3 18.4 12.9 <<Contraction ------------------------------------------------------------------------------------------ Expansion>> Notes: 1. Y-o-y growth (in per cent) has been calculated for all indicators. 2. The heat map, applied on data from April 2023 till May 2025, translates the data range for each indicator into a colour gradient scheme with red denoting the lowest values and green corresponding to the highest values of the respective data series. For digital payments data, zero growth is taken as the lower bound. Sources: Goods and Services Tax Network (GSTN); RBI; Central Electricity Authority (CEA); and Ministry of Petroleum and Natural Gas, GoI. indicators are more or less in line with the revised receipts paved the way for fiscal consolidation estimates (RE). The gross fiscal deficit (GFD) of the (Table III.4). union government stood at 4.8 per cent of GDP, lower On the receipts side, the gross and net tax than the initially budgeted estimate (BE) but slightly revenue posted healthy growth of 9.5 per cent and 7.4 above the revised estimate (RE). On the other hand, per cent, respectively. Gross tax revenue stood at 11.5 the revenue deficit (RD), at 1.7 per cent of GDP, was per cent of GDP in 2024-25 (PA) [Annex Chart A5]. lower than BE and RE. The moderation in revenue While the growth in the corporation tax was higher expenditure, along with robust growth in revenue than RE, the growth in income tax was slightly lower Table III.4: Key Fiscal Indicators of the Union Government (as a per cent of GDP) 2023-24 2024-25 2025-26 Actuals BE RE PA BE 1 2 3 4 5 6 Fiscal Deficit 5.49 4.94 4.74 4.77 4.40 Revenue Deficit 2.54 1.78 1.84 1.71 1.47 Primary Deficit 1.96 1.38 1.30 1.39 0.82 Gross Tax Revenue 11.50 11.77 11.64 11.48 11.96 Non-Tax Revenue 1.33 1.67 1.60 1.63 1.63 Revenue Expenditure 11.60 11.37 11.17 10.90 11.05 Capital Expenditure 3.15 3.40 3.08 3.18 3.14 Of which Capital Outlay 2.62 2.81 2.56 2.59 2.51 Note: GDP used for 2025-26 (BE) and 2024-25 (BE) are as per Union Budgets 2025-26 and 2024-25, respectively. For 2024-25 (RE) the GDP is as per Second Advance Estimates (SAE) released by NSO on February 28, 2025. For 2024-25 (PA), the GDP used is as per the Provisional Estimates (PE) released by NSO on May 30, 2025. Sources: Union Budget Documents; and Controller General of Accounts (CGA). 30 RBI Bulletin June 2025State of the Economy ARTICLE than RE. Although the union excise duty and custom Table III.5: States’ Key Fiscal Indicators duty collections were broadly in line with RE, their (Per cent of GDP/GSDP) growth rate contracted from the previous year. Apart 2023-24 2024-25 2025-26 Accounts PA BE from higher surplus transfer from the Reserve Bank, Revenue Receipts 13.3 12.4 14.4 higher dividend transfer from central public sector Tax Revenue 10.4 10.0 11.1 enterprises (CPSEs) pushed non-tax revenue growth Non-Tax Revenue 1.1 1.0 1.2 in 2024-25 above RE. Grants from the Centre 1.8 1.3 2.0 Revenue Expenditure 13.6 13.0 14.6 The total expenditure of the union government Capital Expenditure 2.7 2.7 3.2 registered a growth of 4.8 per cent in 2024-25 (PA) Of which: Capital Outlay 2.5 2.4 3.0 over 2023-24. As per cent of GDP, while revenue Revenue Deficit 0.3 0.6 0.2 expenditure declined in 2024-25 (PA) vis-à-vis RE, Gross Fiscal Deficit 3.0 3.2 3.3 capital expenditure remained broadly unchanged Primary Deficit 1.3 1.7 1.5 Notes: 1. PA: Provisional Accounts, BE: Budget Estimates; (Annex Chart A6). The growth in interest payments 2. Data for 2023-24 (Accounts), 2025-26 (BE) pertain to 31 States/ UTs. moderated, while that of subsidy outgo saw a 3. Data for 2024-25 (PA) pertain to 27 States/UTs. Data for 2024- contraction during 2024-25 (PA) in line with RE. 25(PA) are taken as a per cent of GSDP. Sources: Budget documents of States, Comptroller and Auditor General Furthermore, the ratio of revenue expenditure to (CAG). capital outlay (RECO) declined to 4.2, lower than Meanwhile, capital expenditure, as a per cent of RE (from 4.4 in 2023-24), which bodes well for the GSDP, remained stable, aided by a significant year- quality of public expenditure. end surge in most states. For 2025-26, states have Central government finances for April 2025 budgeted a GFD-GDP ratio of 3.3 per cent, along indicated an improvement in GFD and RD – both in with a rise in capital outlay to 3.0 per cent of GDP, absolute terms and as per cent of BE – vis-à-vis the reflecting a continued focus on enhancing the quality corresponding period of the previous year, aided by of expenditure within a calibrated fiscal path (Table substantial growth in non-tax revenue, and non-debt III.5). capital receipts (including disinvestment receipts). Trade While revenue expenditure recorded a contraction India’s merchandise exports contracted by (-) 2.2 due to a decline in interest payments, capital outlay per cent (y-o-y) to US$38.7 billion in May 2025 due to grew by 20.9 per cent. an unfavourable base effect (Chart III.2). Consolidated state government finances for 2024-25 (PA)7 witnessed some deterioration. The Exports of 13 out of 30 major commodities consolidated GFD to gross state domestic product (accounting for 59.0 per cent of the export basket in (GFD-GSDP) ratio of states rose in 2024-25 owing 2024-25) contracted on a y-o-y basis in May. Petroleum to a shortfall in tax revenue and lower grants from products, gems and jewellery, iron ore, engineering the centre. The moderation in revenue receipts goods and cotton yarn/fabrics contributed negatively outweighed the decline in revenue expenditure, while electronic goods, organic and inorganic leading to a widening of the revenue deficit. chemicals, drugs and pharmaceuticals, marine products and readymade garments (RMG) of all 7 Data for Provisional Accounts (PA) pertain to 27 states/union territories (UTs). textiles supported export growth in May. Exports RBI Bulletin June 2025 31ARTICLE State of the Economy (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:21)(cid:29)(cid:3)(cid:44)(cid:81)(cid:71)(cid:76)(cid:68)(cid:10)(cid:86)(cid:3)(cid:48)(cid:72)(cid:85)(cid:70)(cid:75)(cid:68)(cid:81)(cid:71)(cid:76)(cid:86)(cid:72)(cid:3)(cid:40)(cid:91)(cid:83)(cid:82)(cid:85)(cid:87)(cid:86) (cid:68)(cid:17)(cid:3)(cid:55)(cid:85)(cid:72)(cid:81)(cid:71)(cid:3)(cid:76)(cid:81)(cid:3)(cid:40)(cid:91)(cid:83)(cid:82)(cid:85)(cid:87)(cid:86) (cid:69)(cid:17)(cid:3)(cid:39)(cid:72)(cid:70)(cid:82)(cid:80)(cid:83)(cid:82)(cid:86)(cid:76)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:82)(cid:73)(cid:3)(cid:54)(cid:72)(cid:84)(cid:88)(cid:72)(cid:81)(cid:87)(cid:76)(cid:68)(cid:79)(cid:3)(cid:38)(cid:75)(cid:68)(cid:81)(cid:74)(cid:72)(cid:3)(cid:76)(cid:81)(cid:3)(cid:40)(cid:91)(cid:83)(cid:82)(cid:85)(cid:87)(cid:3)(cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75) (cid:523)(cid:24)(cid:22)(cid:840)(cid:3)(cid:132)(cid:139)(cid:142)(cid:142)(cid:139)(cid:145)(cid:144)(cid:481)(cid:3)(cid:142)(cid:135)(cid:136)(cid:150)(cid:3)(cid:149)(cid:133)(cid:131)(cid:142)(cid:135)(cid:482)(cid:3)(cid:137)(cid:148)(cid:145)(cid:153)(cid:150)(cid:138)(cid:3)(cid:139)(cid:144)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:481)(cid:3)(cid:148)(cid:139)(cid:137)(cid:138)(cid:150)(cid:3)(cid:149)(cid:133)(cid:131)(cid:142)(cid:135)(cid:524) (cid:523)(cid:28)(cid:486)(cid:145)(cid:486)(cid:155)(cid:481)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:524) (cid:23)(cid:24) (cid:23)(cid:19) (cid:23)(cid:19) (cid:22)(cid:19) (cid:22)(cid:24) (cid:22)(cid:19) (cid:21)(cid:19) (cid:21)(cid:24) (cid:20)(cid:19) (cid:21)(cid:19) (cid:20)(cid:24) (cid:19) (cid:16)(cid:21)(cid:17)(cid:21) (cid:20)(cid:19) (cid:16)(cid:20)(cid:19) (cid:24) (cid:19) (cid:16)(cid:21)(cid:19) (cid:49)(cid:82)(cid:81)(cid:16)(cid:51)(cid:50)(cid:47) (cid:51)(cid:50)(cid:47) (cid:60)(cid:16)(cid:82)(cid:16)(cid:92)(cid:15)(cid:3)(cid:74)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75)(cid:3)(cid:11)(cid:53)(cid:43)(cid:54)(cid:12) (cid:37)(cid:68)(cid:86)(cid:72)(cid:3)(cid:72)(cid:73)(cid:73)(cid:72)(cid:70)(cid:87) (cid:48)(cid:82)(cid:80)(cid:72)(cid:81)(cid:87)(cid:88)(cid:80) (cid:168)(cid:3)(cid:76)(cid:81)(cid:3)(cid:92)(cid:16)(cid:82)(cid:16)(cid:92)(cid:3)(cid:74)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75) (cid:49)(cid:82)(cid:87)(cid:72)(cid:29)(cid:3)(cid:51)(cid:50)(cid:47)(cid:29)(cid:3)(cid:51)(cid:72)(cid:87)(cid:85)(cid:82)(cid:79)(cid:72)(cid:88)(cid:80)(cid:15)(cid:3)(cid:82)(cid:76)(cid:79)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:79)(cid:88)(cid:69)(cid:85)(cid:76)(cid:70)(cid:68)(cid:81)(cid:87)(cid:86)(cid:17) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:86)(cid:29)(cid:3)(cid:51)(cid:44)(cid:37)(cid:30)(cid:3)(cid:39)(cid:42)(cid:38)(cid:44)(cid:9)(cid:54)(cid:30)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:53)(cid:37)(cid:44)(cid:3)(cid:86)(cid:87)(cid:68)(cid:73)(cid:73)(cid:3)(cid:72)(cid:86)(cid:87)(cid:76)(cid:80)(cid:68)(cid:87)(cid:72)(cid:86)(cid:17) to 10 out of 20 major destinations expanded in May 2024-25) contracted on y-o-y basis in May. Petroleum, 2025, including to the US, China and Singapore. crude and products, transport equipment, coke, coal and briquittes, gold and pearls, precious and semi- Merchandise imports also contracted by (-) precious stones pulled down import growth, while 1.7 per cent (y-o-y) to US$60.6 billion in May 2025 chemical material and products, electronic goods, (Chart III.3). machinery, silver, and non-ferrous metals supported Imports of 10 out of 30 major commodities import growth during May. Imports from 9 out of (accounting for 51.5 per cent of import basket in 20 major source countries contracted. Among major 32 RBI Bulletin June 2025 (cid:22)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:22)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:22)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:23)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:23)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:24)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:24)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:24)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:21)(cid:24) (cid:21)(cid:19) (cid:20)(cid:24) (cid:20)(cid:19) (cid:24) (cid:19) (cid:16)(cid:24) (cid:16)(cid:20)(cid:19) (cid:16)(cid:20)(cid:24) (cid:16)(cid:20)(cid:20) (cid:16)(cid:21)(cid:19) (cid:16)(cid:21)(cid:24) (cid:22)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:22)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) 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(cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:24)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:24)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:24)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48)State of the Economy ARTICLE (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:23)(cid:29)(cid:3)(cid:54)(cid:72)(cid:85)(cid:89)(cid:76)(cid:70)(cid:72)(cid:86)(cid:3)(cid:40)(cid:91)(cid:83)(cid:82)(cid:85)(cid:87)(cid:86)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:44)(cid:80)(cid:83)(cid:82)(cid:85)(cid:87)(cid:86)(cid:29)(cid:3)(cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75)(cid:3)(cid:53)(cid:68)(cid:87)(cid:72)(cid:86)(cid:3) (cid:19)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:3)(cid:523)(cid:155)(cid:486)(cid:145)(cid:486)(cid:155)(cid:524) (cid:22)(cid:19) (cid:21)(cid:24) (cid:21)(cid:19) (cid:20)(cid:24) (cid:20)(cid:19) (cid:27)(cid:17)(cid:27) (cid:24) (cid:19) (cid:19)(cid:17)(cid:28) (cid:16)(cid:24) (cid:16)(cid:20)(cid:19) (cid:16)(cid:20)(cid:24) (cid:40)(cid:91)(cid:83)(cid:82)(cid:85)(cid:87)(cid:86) (cid:44)(cid:80)(cid:83)(cid:82)(cid:85)(cid:87)(cid:86) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:29)(cid:3)(cid:53)(cid:37)(cid:44)(cid:17) trading partners, imports from China, the UAE, and Agriculture the US expanded in May. The third advance estimates (AE) released on Merchandise trade deficit narrowed to US$21.9 May 29, 2025 reflected a broad-based increase in billion in May 2025 from US$22.1 billion in May production over the previous year, across almost all 2024. Oil deficit narrowed to US$9.1 billion in May major crops, barring sugarcane and cotton (Chart III.6). from US$11.9 billion a year ago. Consequently, its The rise in crop production was mainly attributed share in total trade deficit declined to 41.6 per cent in to good rainfall along with comfortable reservoir May from 53.8 per cent a year ago. In contrast, non- positions throughout the year. oil deficit widened to US$12.8 billion in May from US$10.2 billion a year ago. In April 2025, net services export earnings expanded by 18.8 per cent (y-o-y). While imports increased modestly by 0.9 per cent to US$16.9 billion, exports rose by 8.8 per cent to US$32.8 billion, driven by software and business services (Chart III.4). Aggregate Supply On the supply side, real gross value added (GVA) at basic prices registered a growth of 6.4 per cent in 2024-25, unchanged from the SAE. In terms of quarterly estimates, Q4:2024-25 registered an acceleration of GVA to 6.8 per cent from 6.5 per cent in the preceding quarter. The momentum in quarterly GVA growth was driven by the industrial and services sector (Chart III.5). RBI Bulletin June 2025 33 (cid:22)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:22)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:22)(cid:21)(cid:16)(cid:81)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:74)(cid:88)(cid:36) (cid:22)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:22)(cid:21)(cid:16)(cid:87)(cid:70)(cid:50) (cid:22)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:22)(cid:21)(cid:16)(cid:70)(cid:72)(cid:39) (cid:23)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:23)(cid:21)(cid:16)(cid:69)(cid:72)(cid:41) (cid:23)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:23)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:81)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:74)(cid:88)(cid:36) (cid:23)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:87)(cid:70)(cid:50) (cid:23)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:23)(cid:21)(cid:16)(cid:70)(cid:72)(cid:39) (cid:24)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:24)(cid:21)(cid:16)(cid:69)(cid:72)(cid:41) (cid:24)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:24)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:24)(cid:29)(cid:3)(cid:58)(cid:72)(cid:76)(cid:74)(cid:75)(cid:87)(cid:72)(cid:71)(cid:3)(cid:38)(cid:82)(cid:81)(cid:87)(cid:85)(cid:76)(cid:69)(cid:88)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:87)(cid:82)(cid:3)(cid:42)(cid:57)(cid:36)(cid:3)(cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75) (cid:523)(cid:19)(cid:135)(cid:148)(cid:133)(cid:135)(cid:144)(cid:150)(cid:131)(cid:137)(cid:135)(cid:3)(cid:146)(cid:145)(cid:139)(cid:144)(cid:150)(cid:149)(cid:524) (cid:20)(cid:19) (cid:27) (cid:25)(cid:17)(cid:27) (cid:25)(cid:17)(cid:24) (cid:25)(cid:17)(cid:24) (cid:25) (cid:24)(cid:17)(cid:27) (cid:23) (cid:21) (cid:19) (cid:52)(cid:20) (cid:52)(cid:21) (cid:52)(cid:22) (cid:52)(cid:23) (cid:52)(cid:20) (cid:52)(cid:21) (cid:52)(cid:22) (cid:52)(cid:23) (cid:21)(cid:19)(cid:21)(cid:22)(cid:16)(cid:21)(cid:23) (cid:21)(cid:19)(cid:21)(cid:23)(cid:16)(cid:21)(cid:24) (cid:54)(cid:72)(cid:85)(cid:89)(cid:76)(cid:70)(cid:72)(cid:86) (cid:36)(cid:74)(cid:85)(cid:76)(cid:70)(cid:88)(cid:79)(cid:87)(cid:88)(cid:85)(cid:72)(cid:15)(cid:3)(cid:79)(cid:76)(cid:89)(cid:72)(cid:86)(cid:87)(cid:82)(cid:70)(cid:78)(cid:15)(cid:3)(cid:73)(cid:82)(cid:85)(cid:72)(cid:86)(cid:87)(cid:85)(cid:92)(cid:15)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:73)(cid:76)(cid:86)(cid:75)(cid:76)(cid:81)(cid:74) (cid:44)(cid:81)(cid:71)(cid:88)(cid:86)(cid:87)(cid:85)(cid:92) (cid:42)(cid:57)(cid:36)(cid:3)(cid:68)(cid:87)(cid:3)(cid:69)(cid:68)(cid:86)(cid:76)(cid:70)(cid:3)(cid:83)(cid:85)(cid:76)(cid:70)(cid:72)(cid:86)(cid:3)(cid:11)(cid:92)(cid:16)(cid:82)(cid:16)(cid:92)(cid:3)(cid:74)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75)(cid:15)(cid:3)(cid:83)(cid:72)(cid:85)(cid:3)(cid:70)(cid:72)(cid:81)(cid:87)(cid:12) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:29)(cid:3)(cid:53)(cid:37)(cid:44)(cid:17)ARTICLE State of the Economy crops. However, it was followed by a monsoon break (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:25)(cid:29)(cid:3)(cid:38)(cid:85)(cid:82)(cid:83)(cid:3)(cid:51)(cid:85)(cid:82)(cid:71)(cid:88)(cid:70)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:71)(cid:88)(cid:85)(cid:76)(cid:81)(cid:74)(cid:3)(cid:21)(cid:19)(cid:21)(cid:23)(cid:16)(cid:21)(cid:24) (cid:11)(cid:36)(cid:86)(cid:3)(cid:83)(cid:72)(cid:85)(cid:3)(cid:55)(cid:75)(cid:76)(cid:85)(cid:71)(cid:3)(cid:36)(cid:40)(cid:12) in the first half of June. Rainfall has picked up again (cid:523)(cid:16)(cid:139)(cid:142)(cid:142)(cid:139)(cid:145)(cid:144)(cid:3)(cid:150)(cid:145)(cid:144)(cid:144)(cid:135)(cid:149)(cid:481)(cid:3)(cid:142)(cid:135)(cid:136)(cid:150)(cid:3)(cid:149)(cid:133)(cid:131)(cid:142)(cid:135)(cid:482)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:481)(cid:3)(cid:148)(cid:139)(cid:137)(cid:138)(cid:150)(cid:3)(cid:149)(cid:133)(cid:131)(cid:142)(cid:135)(cid:524) leading to an increase in the reservoir storage to 32 (cid:24)(cid:19)(cid:19) (cid:20)(cid:19) (cid:28)(cid:17)(cid:20) (cid:23)(cid:24)(cid:19) per cent of its full capacity, which is higher than its (cid:23)(cid:24)(cid:19) (cid:27)(cid:17)(cid:21) (cid:27) (cid:26)(cid:17)(cid:23) (cid:23)(cid:19)(cid:19) (cid:25) decadal average9 (as on June 19, 2025). The cumulative (cid:22)(cid:24)(cid:19) (cid:23)(cid:17)(cid:20) (cid:22)(cid:17)(cid:26) (cid:23) deficit in south-west monsoon (SWM) rainfall (June (cid:22)(cid:19)(cid:19) (cid:21) 1-20, 2025) has reduced to just 1 per cent of the long- (cid:21)(cid:24)(cid:19) (cid:19) (cid:21)(cid:19)(cid:19) (cid:16)(cid:19)(cid:17)(cid:26) period average (LPA), with central and northwest India (cid:20)(cid:23)(cid:28) (cid:16)(cid:21) (cid:20)(cid:24)(cid:19) (cid:20)(cid:20)(cid:27) receiving above normal rainfall. (cid:20)(cid:19)(cid:19) (cid:16)(cid:23) (cid:24)(cid:19) (cid:25)(cid:21) (cid:23)(cid:22) (cid:21)(cid:24) (cid:16)(cid:24) (cid:22)(cid:17) (cid:20)(cid:25) (cid:16)(cid:25) The combined public stock of rice and wheat (cid:19) (cid:16)(cid:27) remains comfortable at 4.6 times the buffer norm and higher by 20.1 per cent over the last year on account of bumper rabi and kharif harvests (as on June 01, (cid:51)(cid:85)(cid:82)(cid:71)(cid:88)(cid:70)(cid:87)(cid:76)(cid:82)(cid:81) (cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75)(cid:3)(cid:82)(cid:89)(cid:72)(cid:85)(cid:3)(cid:73)(cid:76)(cid:81)(cid:68)(cid:79)(cid:3)(cid:72)(cid:86)(cid:87)(cid:76)(cid:80)(cid:68)(cid:87)(cid:72)(cid:86)(cid:3)(cid:21)(cid:19)(cid:21)(cid:22)(cid:16)(cid:21)(cid:23)(cid:3)(cid:11)(cid:53)(cid:43)(cid:54)(cid:12) 2025). On May 28, 2025, the government announced (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:29)(cid:3)(cid:48)(cid:76)(cid:81)(cid:76)(cid:86)(cid:87)(cid:85)(cid:92)(cid:3)(cid:82)(cid:73)(cid:3)(cid:36)(cid:74)(cid:85)(cid:76)(cid:70)(cid:88)(cid:79)(cid:87)(cid:88)(cid:85)(cid:72)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:41)(cid:68)(cid:85)(cid:80)(cid:72)(cid:85)(cid:86)(cid:183)(cid:3)(cid:58)(cid:72)(cid:79)(cid:73)(cid:68)(cid:85)(cid:72)(cid:17) minimum support prices (MSPs) for kharif marketing High-frequency indicators for the ongoing season (KMS) of 2025-26 for 14 major crops (Chart III.7). kharif agricultural season indicate largely favourable The announcement was in line with the government’s conditions for good sowing, though uncertainties efforts for the past few years to align MSPs in favour remain on the spatiotemporal distribution of of oilseeds, pulses, and nutri-cereals to encourage crop monsoon.8 The early onset of the monsoon has helped diversification, correct the demand-supply imbalance in reducing the incidence of heat waves on standing and promote sustainable agriculture. 8 As per the updated forecast by the Indian Meteorological Department (IMD) released on May 27, 2025, the southwest monsoon (SWM) rainfall is likely to be above normal this year at 106 per cent of the LPA. 9 The decadal average for the corresponding period is 22.9 per cent of full reservoir capacity. 34 RBI Bulletin June 2025 (cid:86)(cid:79)(cid:68)(cid:72)(cid:85)(cid:72)(cid:38)(cid:3)(cid:72)(cid:86)(cid:85)(cid:68)(cid:82)(cid:38)(cid:3) (cid:72)(cid:70)(cid:76)(cid:53)(cid:3) (cid:86)(cid:71)(cid:72)(cid:72)(cid:86)(cid:79)(cid:76)(cid:50) (cid:86)(cid:72)(cid:86)(cid:79)(cid:88)(cid:51)(cid:3) (cid:87)(cid:68)(cid:72)(cid:75)(cid:58) (cid:72)(cid:81)(cid:68)(cid:70)(cid:85)(cid:68)(cid:74)(cid:88)(cid:54) (cid:81)(cid:82)(cid:87)(cid:87)(cid:82)(cid:38) (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:26)(cid:29)(cid:3)(cid:48)(cid:76)(cid:81)(cid:76)(cid:80)(cid:88)(cid:80)(cid:3)(cid:54)(cid:88)(cid:83)(cid:83)(cid:82)(cid:85)(cid:87)(cid:3)(cid:51)(cid:85)(cid:76)(cid:70)(cid:72)(cid:86)(cid:3)(cid:73)(cid:82)(cid:85)(cid:3)(cid:46)(cid:48)(cid:54)(cid:3)(cid:21)(cid:19)(cid:21)(cid:24)(cid:16)(cid:21)(cid:25) (cid:523)(cid:3946)(cid:876)(cid:147)(cid:151)(cid:139)(cid:144)(cid:150)(cid:131)(cid:142)(cid:481)(cid:3)(cid:142)(cid:135)(cid:136)(cid:150)(cid:3)(cid:149)(cid:133)(cid:131)(cid:142)(cid:135)(cid:482)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:481)(cid:3)(cid:148)(cid:139)(cid:137)(cid:138)(cid:150)(cid:3)(cid:149)(cid:133)(cid:131)(cid:142)(cid:135)(cid:524) (cid:20)(cid:21)(cid:19)(cid:19)(cid:19) (cid:20)(cid:25) (cid:20)(cid:23) (cid:20)(cid:23) (cid:20)(cid:19)(cid:19)(cid:19)(cid:19) (cid:20)(cid:21) (cid:27)(cid:19)(cid:19)(cid:19) (cid:20)(cid:19) (cid:20)(cid:19) (cid:28) (cid:20)(cid:19) (cid:28) (cid:27) (cid:25)(cid:19)(cid:19)(cid:19) (cid:27) (cid:27) (cid:27) (cid:26) (cid:25) (cid:25) (cid:25) (cid:24) (cid:25) (cid:23)(cid:19)(cid:19)(cid:19) (cid:24) (cid:22) (cid:22) (cid:23) (cid:21)(cid:19)(cid:19)(cid:19) (cid:21) (cid:20) (cid:19) (cid:19) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:29)(cid:3)(cid:42)(cid:82)(cid:89)(cid:72)(cid:85)(cid:81)(cid:80)(cid:72)(cid:81)(cid:87)(cid:3)(cid:82)(cid:73)(cid:3)(cid:44)(cid:81)(cid:71)(cid:76)(cid:68)(cid:17) (cid:76)(cid:74)(cid:68)(cid:53) (cid:71)(cid:76)(cid:85)(cid:69)(cid:92)(cid:43)(cid:16)(cid:85)(cid:68)(cid:90)(cid:82)(cid:45) (cid:76)(cid:71)(cid:81)(cid:68)(cid:71)(cid:79)(cid:68)(cid:48)(cid:16)(cid:85)(cid:68)(cid:90)(cid:82)(cid:45) (cid:71)(cid:72)(cid:72)(cid:86)(cid:85)(cid:72)(cid:74)(cid:76)(cid:49) (cid:90)(cid:82)(cid:79)(cid:79)(cid:72)(cid:60)(cid:3)(cid:81)(cid:68)(cid:72)(cid:69)(cid:68)(cid:92)(cid:82)(cid:54) (cid:81)(cid:82)(cid:87)(cid:87)(cid:82)(cid:38)(cid:3)(cid:72)(cid:79)(cid:83)(cid:68)(cid:87)(cid:54)(cid:3)(cid:80)(cid:88)(cid:76)(cid:71)(cid:72)(cid:48) (cid:72)(cid:93)(cid:76)(cid:68)(cid:48) (cid:81)(cid:82)(cid:87)(cid:87)(cid:82)(cid:38)(cid:3)(cid:72)(cid:79)(cid:83)(cid:68)(cid:87)(cid:54)(cid:3)(cid:74)(cid:81)(cid:82)(cid:47) (cid:87)(cid:88)(cid:81)(cid:71)(cid:81)(cid:88)(cid:82)(cid:85)(cid:42) (cid:80)(cid:88)(cid:80)(cid:68)(cid:86)(cid:72)(cid:54) (cid:71)(cid:72)(cid:72)(cid:54)(cid:3)(cid:85)(cid:72)(cid:90)(cid:82)(cid:79)(cid:73)(cid:81)(cid:88)(cid:54) (cid:12)(cid:85)(cid:68)(cid:75)(cid:85)(cid:36)(cid:11)(cid:3)(cid:85)(cid:88)(cid:55) (cid:71)(cid:68)(cid:85)(cid:56) (cid:68)(cid:85)(cid:77)(cid:68)(cid:37) (cid:81)(cid:82)(cid:80)(cid:80)(cid:82)(cid:38)(cid:3)(cid:92)(cid:71)(cid:71)(cid:68)(cid:51) (cid:10)(cid:36)(cid:10)(cid:72)(cid:71)(cid:68)(cid:85)(cid:42)(cid:18)(cid:12)(cid:41)(cid:11)(cid:3)(cid:92)(cid:71)(cid:71)(cid:68)(cid:51) (cid:74)(cid:81)(cid:82)(cid:82)(cid:48) (cid:46)(cid:48)(cid:54)(cid:3)(cid:21)(cid:19)(cid:21)(cid:24)(cid:16)(cid:21)(cid:25) (cid:44)(cid:81)(cid:70)(cid:85)(cid:72)(cid:68)(cid:86)(cid:72)(cid:3)(cid:76)(cid:81)(cid:3)(cid:48)(cid:54)(cid:51)(cid:3)(cid:82)(cid:89)(cid:72)(cid:85)(cid:3)(cid:79)(cid:68)(cid:86)(cid:87)(cid:3)(cid:92)(cid:72)(cid:68)(cid:85)(cid:3)(cid:11)(cid:53)(cid:43)(cid:54)(cid:12)State of the Economy ARTICLE Industry and Services (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:27)(cid:29)(cid:3)(cid:49)(cid:82)(cid:80)(cid:76)(cid:81)(cid:68)(cid:79)(cid:3)(cid:54)(cid:68)(cid:79)(cid:72)(cid:86)(cid:3)(cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75) Quarterly results of listed private non-financial (cid:11)(cid:49)(cid:82)(cid:81)(cid:16)(cid:41)(cid:76)(cid:81)(cid:68)(cid:81)(cid:70)(cid:76)(cid:68)(cid:79)(cid:3)(cid:38)(cid:82)(cid:80)(cid:83)(cid:68)(cid:81)(cid:76)(cid:72)(cid:86)(cid:12) (cid:523)(cid:28)(cid:486)(cid:145)(cid:486)(cid:155)(cid:481)(cid:3)(cid:19)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:524) companies for Q4:2024-25 suggest slower revenue (cid:26)(cid:19) growth accompanied by increased profitability. (cid:25)(cid:19) At the aggregate level, sales growth of listed non- (cid:24)(cid:19) government non-financial companies witnessed (cid:23)(cid:19) a slight moderation as compared to the previous (cid:22)(cid:19) quarter, with listed private manufacturing companies (cid:21)(cid:19) (cid:20)(cid:20)(cid:17)(cid:24) (cid:20)(cid:19)(cid:17)(cid:28) experiencing an easing in sales performance amidst (cid:20)(cid:19) (cid:26)(cid:17)(cid:26) (cid:27)(cid:17)(cid:25) (cid:25)(cid:17)(cid:27) (cid:25)(cid:17)(cid:25) subdued demand conditions (Chart III.8).10 Amid (cid:19) macroeconomic and global uncertainties, sales (cid:52)(cid:20) (cid:52)(cid:21) (cid:52)(cid:22) (cid:52)(cid:23) (cid:52)(cid:20) (cid:52)(cid:21) (cid:52)(cid:22) (cid:52)(cid:23) (cid:52)(cid:20) (cid:52)(cid:21) (cid:52)(cid:22) (cid:52)(cid:23) growth improved for IT companies, whereas non-IT (cid:21)(cid:19)(cid:21)(cid:21)(cid:16)(cid:21)(cid:22) (cid:21)(cid:19)(cid:21)(cid:22)(cid:16)(cid:21)(cid:23) (cid:21)(cid:19)(cid:21)(cid:23)(cid:16)(cid:21)(cid:24) services companies experienced a slowdown during (cid:48)(cid:68)(cid:81)(cid:88)(cid:73)(cid:68)(cid:70)(cid:87)(cid:88)(cid:85)(cid:76)(cid:81)(cid:74) (cid:44)(cid:55) (cid:54)(cid:72)(cid:85)(cid:89)(cid:76)(cid:70)(cid:72)(cid:86)(cid:3)(cid:11)(cid:49)(cid:82)(cid:81)(cid:16)(cid:44)(cid:55)(cid:12) the same period. (cid:49)(cid:82)(cid:87)(cid:72)(cid:29)(cid:3)(cid:55)(cid:75)(cid:72)(cid:3)(cid:74)(cid:85)(cid:68)(cid:83)(cid:75)(cid:3)(cid:76)(cid:86)(cid:3)(cid:69)(cid:68)(cid:86)(cid:72)(cid:71)(cid:3)(cid:82)(cid:81)(cid:3)(cid:20)(cid:15)(cid:25)(cid:24)(cid:28)(cid:3)(cid:80)(cid:68)(cid:81)(cid:88)(cid:73)(cid:68)(cid:70)(cid:87)(cid:88)(cid:85)(cid:76)(cid:81)(cid:74)(cid:15)(cid:3)(cid:20)(cid:27)(cid:24)(cid:3)(cid:44)(cid:55)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:27)(cid:22)(cid:28)(cid:3)(cid:81)(cid:82)(cid:81)(cid:16)(cid:44)(cid:55)(cid:3)(cid:79)(cid:76)(cid:86)(cid:87)(cid:72)(cid:71) (cid:70)(cid:82)(cid:80)(cid:83)(cid:68)(cid:81)(cid:76)(cid:72)(cid:86)(cid:17) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:86)(cid:29)(cid:3)(cid:38)(cid:68)(cid:83)(cid:76)(cid:87)(cid:68)(cid:79)(cid:76)(cid:81)(cid:72)(cid:3)(cid:71)(cid:68)(cid:87)(cid:68)(cid:69)(cid:68)(cid:86)(cid:72)(cid:30)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:53)(cid:37)(cid:44)(cid:3)(cid:86)(cid:87)(cid:68)(cid:73)(cid:73)(cid:3)(cid:70)(cid:68)(cid:79)(cid:70)(cid:88)(cid:79)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:86)(cid:17) Although major industries continued to record double-digit sales growth, weaker performance month low of 2.7 per cent in April 2025, with a major of petroleum industry weighed on the overall drag emanating from mining and quarrying, while performance of the manufacturing sector. Excluding manufacturing posted a modest growth. Within the petroleum, sales growth in the manufacturing sector use-based categories, capital goods and consumer remained steady at 9.0 per cent (Chart III.9). durables expanded while consumer non-durables Industrial activity, as measured by the Index and primary goods dragged down growth. The growth of Industrial Production (IIP), slowed to an eight- of Eight Core Industries (ECI) Index also slowed to a (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:28)(cid:29)(cid:3)(cid:48)(cid:68)(cid:81)(cid:88)(cid:73)(cid:68)(cid:70)(cid:87)(cid:88)(cid:85)(cid:76)(cid:81)(cid:74)(cid:3)(cid:54)(cid:72)(cid:70)(cid:87)(cid:82)(cid:85)(cid:3)(cid:178)(cid:3)(cid:44)(cid:81)(cid:71)(cid:88)(cid:86)(cid:87)(cid:85)(cid:92)(cid:16)(cid:90)(cid:76)(cid:86)(cid:72)(cid:3)(cid:54)(cid:68)(cid:79)(cid:72)(cid:86)(cid:3)(cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75) (cid:523)(cid:28)(cid:486)(cid:145)(cid:486)(cid:155)(cid:481)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:524) (cid:52)(cid:22)(cid:29)(cid:21)(cid:19)(cid:21)(cid:23)(cid:16)(cid:21)(cid:24) (cid:52)(cid:23)(cid:29)(cid:21)(cid:19)(cid:21)(cid:23)(cid:16)(cid:21)(cid:24) (cid:49)(cid:82)(cid:87)(cid:72)(cid:29)(cid:3)(cid:49)(cid:88)(cid:80)(cid:69)(cid:72)(cid:85)(cid:86)(cid:3)(cid:76)(cid:81)(cid:3)(cid:83)(cid:68)(cid:85)(cid:72)(cid:81)(cid:87)(cid:75)(cid:72)(cid:86)(cid:72)(cid:86)(cid:3)(cid:85)(cid:72)(cid:83)(cid:85)(cid:72)(cid:86)(cid:72)(cid:81)(cid:87)(cid:3)(cid:86)(cid:75)(cid:68)(cid:85)(cid:72)(cid:3)(cid:76)(cid:81)(cid:3)(cid:86)(cid:68)(cid:79)(cid:72)(cid:86)(cid:3)(cid:71)(cid:88)(cid:85)(cid:76)(cid:81)(cid:74)(cid:3)(cid:52)(cid:23)(cid:29)(cid:21)(cid:19)(cid:21)(cid:23)(cid:16)(cid:21)(cid:24)(cid:17) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:86)(cid:29)(cid:3)(cid:38)(cid:68)(cid:83)(cid:76)(cid:87)(cid:68)(cid:79)(cid:76)(cid:81)(cid:72)(cid:3)(cid:71)(cid:68)(cid:87)(cid:68)(cid:69)(cid:68)(cid:86)(cid:72)(cid:30)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:53)(cid:37)(cid:44)(cid:3)(cid:86)(cid:87)(cid:68)(cid:73)(cid:73)(cid:3)(cid:70)(cid:68)(cid:79)(cid:70)(cid:88)(cid:79)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:86)(cid:17) 10 Based on quarterly results of 2,936 listed non-government non-financial (NGNF) companies. RBI Bulletin June 2025 35 (cid:26)(cid:17)(cid:25)(cid:20) (cid:19)(cid:17)(cid:19)(cid:21) (cid:26)(cid:17)(cid:22)(cid:20) (cid:24)(cid:17)(cid:23)(cid:20) (cid:27)(cid:17)(cid:20)(cid:20) (cid:22)(cid:17)(cid:23)(cid:20) (cid:25)(cid:17)(cid:20)(cid:20) (cid:22)(cid:17)(cid:22)(cid:20) (cid:28)(cid:17)(cid:20)(cid:20) (cid:23)(cid:17)(cid:19)(cid:20) (cid:22)(cid:17)(cid:28) (cid:20)(cid:17)(cid:28) (cid:27)(cid:17)(cid:19)(cid:16) (cid:22)(cid:17)(cid:24) (cid:22)(cid:17)(cid:19)(cid:20) (cid:19)(cid:17)(cid:20) (cid:20)(cid:17)(cid:20)(cid:16) (cid:28)(cid:17)(cid:20)(cid:16) (cid:21)(cid:17)(cid:21)(cid:16) (cid:25)(cid:17)(cid:27)(cid:16) (cid:26)(cid:17)(cid:26) (cid:25)(cid:17)(cid:25) (cid:20)(cid:17)(cid:28) (cid:19)(cid:17)(cid:28) (cid:21)(cid:24) (cid:21)(cid:19) (cid:20)(cid:24) (cid:20)(cid:19) (cid:24) (cid:19) (cid:16)(cid:24) (cid:16)(cid:20)(cid:19) (cid:16)(cid:20)(cid:24) (cid:92)(cid:85)(cid:72)(cid:81)(cid:76)(cid:75)(cid:70)(cid:68)(cid:48)(cid:3)(cid:79)(cid:68)(cid:70)(cid:76)(cid:85)(cid:87)(cid:70)(cid:72)(cid:79)(cid:40) (cid:12)(cid:8)(cid:27)(cid:17)(cid:25)(cid:11) (cid:86)(cid:79)(cid:68)(cid:87)(cid:72)(cid:48)(cid:3)(cid:86)(cid:88)(cid:82)(cid:85)(cid:85)(cid:72)(cid:41)(cid:16)(cid:81)(cid:82)(cid:49) (cid:12)(cid:8)(cid:28)(cid:17)(cid:23)(cid:11) (cid:86)(cid:79)(cid:68)(cid:70)(cid:76)(cid:87)(cid:88)(cid:72)(cid:70)(cid:68)(cid:80)(cid:85)(cid:68)(cid:75)(cid:51) (cid:12)(cid:8)(cid:25)(cid:11) (cid:86)(cid:87)(cid:70)(cid:88)(cid:71)(cid:82)(cid:85)(cid:51)(cid:3)(cid:71)(cid:82)(cid:82)(cid:41) (cid:12)(cid:8)(cid:25)(cid:17)(cid:27)(cid:11) (cid:86)(cid:79)(cid:68)(cid:70)(cid:76)(cid:80)(cid:72)(cid:75)(cid:38) (cid:12)(cid:8)(cid:19)(cid:20)(cid:11) (cid:86)(cid:72)(cid:79)(cid:76)(cid:69)(cid:82)(cid:80)(cid:82)(cid:87)(cid:88)(cid:36) (cid:12)(cid:8)(cid:23)(cid:17)(cid:25)(cid:20)(cid:11) (cid:87)(cid:81)(cid:72)(cid:80)(cid:72)(cid:38) (cid:12)(cid:8)(cid:28)(cid:17)(cid:23)(cid:11) (cid:86)(cid:72)(cid:79)(cid:76)(cid:87)(cid:91)(cid:72)(cid:55) (cid:12)(cid:8)(cid:23)(cid:17)(cid:22)(cid:11) (cid:79)(cid:72)(cid:72)(cid:87)(cid:54)(cid:3)(cid:71)(cid:81)(cid:68)(cid:3)(cid:81)(cid:82)(cid:85)(cid:44) (cid:12)(cid:8)(cid:28)(cid:17)(cid:20)(cid:20)(cid:11) (cid:86)(cid:87)(cid:70)(cid:88)(cid:71)(cid:82)(cid:85)(cid:51)(cid:3)(cid:80)(cid:88)(cid:72)(cid:79)(cid:82)(cid:85)(cid:87)(cid:72)(cid:51) (cid:12)(cid:8)(cid:26)(cid:17)(cid:20)(cid:20)(cid:11) (cid:74)(cid:81)(cid:76)(cid:85)(cid:88)(cid:87)(cid:70)(cid:68)(cid:73)(cid:88)(cid:81)(cid:68)(cid:48) (cid:74)(cid:81)(cid:76)(cid:71)(cid:88)(cid:79)(cid:70)(cid:91)(cid:40)(cid:3)(cid:74)(cid:81)(cid:76)(cid:85)(cid:88)(cid:87)(cid:70)(cid:68)(cid:73)(cid:88)(cid:81)(cid:68)(cid:48) (cid:10)(cid:80)(cid:88)(cid:72)(cid:79)(cid:82)(cid:85)(cid:87)(cid:72)(cid:51)(cid:10)(cid:3)ARTICLE State of the Economy Table III.6: High Frequency Indicators–Industry–Growth Rate May-24 Jun-24 Jul-24 Aug-24 Sep-24 Oct-24 Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 IIP-Headline 6.3 4.9 5.0 0.0 3.2 3.7 5.0 3.7 5.2 2.7 3.9 2.7 IIP Manufacturing 5.1 3.5 4.7 1.2 4.0 4.4 5.5 3.7 5.8 2.8 4.0 3.4 IIP Capital Goods 2.6 3.6 11.7 0.0 3.5 2.9 8.9 10.5 10.2 8.2 3.6 20.3 PMI Manufacturing 57.5 58.3 58.1 57.5 56.5 57.5 56.5 56.4 57.7 56.3 58.1 58.2 57.6 PMI Export Order 57.3 56.2 57.2 54.4 52.9 53.6 54.6 54.7 58.6 56.3 54.9 57.6 56.9 PMI Manufacturing: Future Output 67.4 64.0 64.1 62.1 61.6 62.1 65.5 62.5 65.1 64.9 64.4 64.6 63.1 Eight Core Index 6.9 5.0 6.3 -1.5 2.4 3.8 5.8 5.1 5.1 3.4 4.5 1.0 0.7 Electricity Generation: Conventional 14.5 9.7 6.8 -3.8 -1.3 0.5 2.7 4.5 -1.3 2.4 4.8 -1.9 -8.2 Electricity Generation: Renewable 8.6 2.0 14.2 -3.7 12.5 14.9 19.0 17.9 31.9 12.2 25.2 28.0 Automobile Production 15.6 15.4 16.8 4.4 10.1 10.0 8.0 1.3 9.4 2.3 6.5 -1.7 5.2 Passenger Vehicle Production 7.0 0.8 1.2 0.7 -3.4 -4.0 6.5 9.2 3.7 4.5 11.2 10.8 5.4 Tractor Production 11.5 3.0 8.1 -1.0 2.7 0.4 24.7 20.9 23.7 -7.8 18.5 20.5 9.1 Two-wheelers Production 17.8 18.7 21.1 4.9 12.9 13.3 8.8 -0.6 10.3 1.6 5.6 -4.1 4.7 Three-wheelers Production 4.5 7.8 6.0 9.0 3.9 -6.7 -5.5 7.6 16.2 6.5 6.0 4.1 16.9 Crude Steel Production 4.6 3.4 5.8 2.6 0.3 4.2 4.5 8.3 7.4 6.0 8.5 5.6 9.5 Finished Steel Production 10.1 4.4 6.0 2.7 0.7 4.0 2.8 5.3 6.7 6.7 10.0 5.1 5.5 Import of Capital Goods 8.3 15.1 11.8 12.3 10.9 7.0 4.7 6.1 15.5 -0.5 8.6 21.5 14.3 <<Contraction ------------------------------------------------------------------------------------------ Expansion>> Notes: 1. The y-o-y growth (in per cent) has been calculated for all indicators (except for PMI). 2. The heat map translates the data range for each indicator into a colour gradient scheme with red denoting the lowest values and green cor- responding to the highest values of the respective data series. 3. Heat map is applied on data from April 2023 till May 2025 other than for IIP, and Electricity Generation: Renewable, where the data is till April 2025. 4. All PMI values are reported in index form. A PMI value >50 denote expansion; <50 denote contraction; and =50 denote ‘no change’. In the PMI heat maps, red denotes the lowest value, yellow denotes 50 (or the no change value), and green denotes the highest value in each of the PMI series. Sources: Ministry of Statistics and Programme Implementation (MoSPI); S&P Global; Central Electricity Authority (CEA), Ministry of Power; Society of Indian Automobile Manufacturers (SIAM); Tractor and Mechanisation Association; Office of Economic Adviser, GoI; Joint Plant Committee; Directorate General of Commercial Intelligence & Statistics; and Ministry of Commerce and Industry. nine-month low of 0.7 per cent y-o-y in May 2025 as further to below their historical average levels due to compared to 6.9 per cent in May 2024. improvements in both suppliers’ delivery time and Available high-frequency indicators for May point semiconductor supplies and a decline in new orders to resilient industrial activity, with steady expansion (Annex Chart A7). in PMI manufacturing and strong growth in capital In pursuit of its net zero targets, India’s push goods and steel output. Automobile production for renewable energy capacity, gathered further rebounded in May, with two-wheeler output momentum in FY 2024-25. The total installed recovering from last month’s contraction and three- renewable energy capacity increased by 29.52 wheeler production recording a sharp acceleration. gigawatts, driven mainly by the rise in the installed However, conventional electricity generation showed intermittent weakness for the second consecutive capacity under solar, wind and hydro energy projects month (Table III.6). Supply chain pressures eased (Chart III.10). 36 RBI Bulletin June 2025State of the Economy ARTICLE (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:20)(cid:19)(cid:29)(cid:3)(cid:36)(cid:81)(cid:81)(cid:88)(cid:68)(cid:79)(cid:3)(cid:55)(cid:82)(cid:87)(cid:68)(cid:79)(cid:3)(cid:44)(cid:81)(cid:86)(cid:87)(cid:68)(cid:79)(cid:79)(cid:72)(cid:71)(cid:3)(cid:53)(cid:72)(cid:81)(cid:72)(cid:90)(cid:68)(cid:69)(cid:79)(cid:72)(cid:3)(cid:40)(cid:81)(cid:72)(cid:85)(cid:74)(cid:92)(cid:3)(cid:11)(cid:53)(cid:40)(cid:12)(cid:3)(cid:38)(cid:68)(cid:83)(cid:68)(cid:70)(cid:76)(cid:87)(cid:92)(cid:3)(cid:38)(cid:82)(cid:80)(cid:83)(cid:82)(cid:86)(cid:76)(cid:87)(cid:76)(cid:82)(cid:81) (cid:523)(cid:10)(cid:139)(cid:137)(cid:131)(cid:153)(cid:131)(cid:150)(cid:150)(cid:149)(cid:524) (cid:21)(cid:24)(cid:19) (cid:21)(cid:21)(cid:19)(cid:17)(cid:20)(cid:19) (cid:20)(cid:28)(cid:19)(cid:17)(cid:24)(cid:26) (cid:21)(cid:19)(cid:19) (cid:20)(cid:24)(cid:19) (cid:20)(cid:19)(cid:19) (cid:24)(cid:19) (cid:19) (cid:54)(cid:82)(cid:79)(cid:68)(cid:85) (cid:43)(cid:92)(cid:71)(cid:85)(cid:82)(cid:3)(cid:11)(cid:76)(cid:81)(cid:70)(cid:79)(cid:88)(cid:71)(cid:76)(cid:81)(cid:74)(cid:3)(cid:86)(cid:80)(cid:68)(cid:79)(cid:79)(cid:3)(cid:75)(cid:92)(cid:71)(cid:85)(cid:82)(cid:12) (cid:58)(cid:76)(cid:81)(cid:71)(cid:3)(cid:51)(cid:82)(cid:90)(cid:72)(cid:85) (cid:37)(cid:76)(cid:82)(cid:16)(cid:51)(cid:82)(cid:90)(cid:72)(cid:85) (cid:55)(cid:82)(cid:87)(cid:68)(cid:79) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:29)(cid:3)(cid:38)(cid:72)(cid:81)(cid:87)(cid:85)(cid:68)(cid:79)(cid:3)(cid:40)(cid:79)(cid:72)(cid:70)(cid:87)(cid:85)(cid:76)(cid:70)(cid:76)(cid:87)(cid:92)(cid:3)(cid:36)(cid:88)(cid:87)(cid:75)(cid:82)(cid:85)(cid:76)(cid:87)(cid:92)(cid:3)(cid:11)(cid:38)(cid:40)(cid:36)(cid:12)(cid:17) India’s services sector sustained a strong growth led by a higher growth in containerised cargo, iron momentum in May, driven by a robust export demand ore and petroleum, oil and lubricants (POL). Growth and a record surge in hiring (Table III.7). Port traffic in construction sector indicators – steel consumption expanded for the sixth consecutive month in May, and cement production – inched up in May. RBI Bulletin June 2025 37 (cid:24)(cid:20)(cid:16)(cid:23)(cid:20)(cid:19)(cid:21) (cid:25)(cid:20)(cid:16)(cid:24)(cid:20)(cid:19)(cid:21) (cid:26)(cid:20)(cid:16)(cid:25)(cid:20)(cid:19)(cid:21) (cid:27)(cid:20)(cid:16)(cid:26)(cid:20)(cid:19)(cid:21) (cid:28)(cid:20)(cid:16)(cid:27)(cid:20)(cid:19)(cid:21) (cid:19)(cid:21)(cid:16)(cid:28)(cid:20)(cid:19)(cid:21) (cid:20)(cid:21)(cid:16)(cid:19)(cid:21)(cid:19)(cid:21) (cid:21)(cid:21)(cid:16)(cid:20)(cid:21)(cid:19)(cid:21) (cid:22)(cid:21)(cid:16)(cid:21)(cid:21)(cid:19)(cid:21) (cid:23)(cid:21)(cid:16)(cid:22)(cid:21)(cid:19)(cid:21) (cid:24)(cid:21)(cid:16)(cid:23)(cid:21)(cid:19)(cid:21) Table III.7: High Frequency Indicators–Services–Growth Rate May-24 Jun-24 Jul-24 Aug-24 Sep-24 Oct-24 Nov-24 Dec-24 Jan-25 Feb-25 Mar-25 Apr-25 May-25 PMI Services 60.2 60.5 60.3 60.9 57.7 58.5 58.4 59.3 56.5 59.0 58.5 58.7 58.8 International Air Passenger Traffic 19.6 11.3 8.8 11.1 11.2 10.3 10.7 9.0 11.1 7.7 6.8 13.0 4.8 Domestic Air Cargo 10.3 10.3 8.8 0.6 14.0 8.9 0.3 4.3 6.9 -2.5 4.9 16.6 International Air Cargo 19.2 19.6 24.4 20.7 20.5 18.4 16.1 10.5 7.1 -6.3 3.3 8.6 Port Cargo Traffic 3.8 6.8 5.9 6.7 5.8 -3.4 -4.9 3.4 7.6 3.6 13.3 7.0 4.3 Retail Commercial Vehicle Sales -1.6 -4.7 5.9 -6.0 -10.4 6.4 -6.1 -5.2 8.2 -8.6 2.7 -1.0 -3.7 Hotel Occupancy -2.6 -3.1 3.6 0.7 2.1 -5.3 11.1 -0.2 1.2 0.6 1.9 7.2 Tourist Arrivals -2.8 5.7 -1.3 -4.2 0.4 -1.4 -0.1 -6.6 -0.2 -8.6 Steel Consumption 14.1 18.8 14.4 10.0 11.8 8.9 9.5 5.2 10.9 10.9 13.6 6.0 7.8 Cement Production -0.6 1.8 5.1 -2.5 7.6 3.1 13.1 10.3 14.3 10.7 12.2 6.3 9.2 <<Contraction ------------------------------------------------------------------------------------------ Expansion>> Notes: 1. The y-o-y growth (in per cent) has been calculated for all indicators (except for PMI). 2. The heat map translates the data range for each indicator into a colour gradient scheme with red denoting the lowest values and green corresponding to the highest values of the respective data series. 3. Heat map is applied on data from April 2023 till May 2025 other than for Hotel Occupancy, Domestic Air Cargo and International Air Passenger Traffic, where the data is till April 2025. The latest data for tourist arrivals is till February 2025. 4. All PMI values are reported in index form. A PMI value >50 denote expansion; <50 denote contraction; and =50 denote ‘no change’. In the PMI heat maps, red denotes the lowest value, yellow denotes 50 (or the no change value), and green denotes the highest value in each of the PMI series. Sources: Federation of Automobile Dealers Associations (FADA); Indian Ports Association; Airports Authority of India; HVS Anarock; Ministry of Tourism, GoI; Joint Plant Committee; Office of Economic Adviser; and S&P Global.ARTICLE State of the Economy Inflation Fuel and light inflation softened marginally to 2.8 per cent in May from 2.9 per cent in April. While Headline inflation, as measured by y-o-y kerosene prices continued to remain in deflation changes in the all-India consumer price index (CPI),11 moderated to 2.8 per cent in May 2025 (the lowest and inflation for electricity moderated, it increased since February 2019) from 3.2 per cent in April (Chart for LPG, firewood, and chips. III.11). The decline in headline inflation by 34 bps Core CPI inflation remained steady at 4.2 per cent came from a negative base effect of 54 bps, which in May, same as in April. An increase in inflation in more than offset a positive price momentum of 20 its subgroups, such as pan, tobacco and intoxicants, bps. A positive momentum was recorded across all housing, transport and communication, and groups within CPI.12 personal care and effects, was offset by a moderation Food inflation (y-o-y) decelerated to 1.5 per cent in household goods and services, and recreation and in May, the lowest in 73 months. Within subgroups, amusement. Inflation in clothing and footwear, and vegetables, pulses, and meat and fish continued health remained steady. to record deflation. A moderation in inflation was In terms of regional distribution, rural and also observed in cereals, eggs, sugar, and fruits. urban inflation eased to 2.6 per cent and 3.1 per Inflation, however, picked up in milk and products, oils and fats, and non-alcoholic beverages. Spices cent, respectively, in May 2025. At the state level, continued to record deflation, albeit at a slower pace, inflation ranged from 0.6 per cent to 6.8 per cent. while inflation in prepared meals remained steady Majority of the states experienced inflation between (Chart III.12). 2 - 4 per cent (Chart III.13). (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:20)(cid:20)(cid:29)(cid:3)(cid:55)(cid:85)(cid:72)(cid:81)(cid:71)(cid:86)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:39)(cid:85)(cid:76)(cid:89)(cid:72)(cid:85)(cid:86)(cid:3)(cid:82)(cid:73)(cid:3)(cid:38)(cid:51)(cid:44)(cid:3)(cid:44)(cid:81)(cid:73)(cid:79)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81) (cid:68)(cid:17)(cid:3)(cid:38)(cid:51)(cid:44)(cid:3)(cid:3)(cid:44)(cid:81)(cid:73)(cid:79)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:11)(cid:92)(cid:16)(cid:82)(cid:16)(cid:92)(cid:12) (cid:69)(cid:17)(cid:3)(cid:38)(cid:82)(cid:81)(cid:87)(cid:85)(cid:76)(cid:69)(cid:88)(cid:87)(cid:76)(cid:82)(cid:81)(cid:86) (cid:523)(cid:19)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:524) (cid:523)(cid:19)(cid:135)(cid:148)(cid:133)(cid:135)(cid:144)(cid:150)(cid:131)(cid:137)(cid:135)(cid:3)(cid:146)(cid:145)(cid:139)(cid:144)(cid:150)(cid:149)(cid:524) (cid:20)(cid:21) (cid:20)(cid:19) (cid:27) (cid:25) (cid:23)(cid:17)(cid:21) (cid:23) (cid:21)(cid:17)(cid:27) (cid:21) (cid:21)(cid:17)(cid:27) (cid:20)(cid:17)(cid:24) (cid:19) (cid:16)(cid:21) (cid:16)(cid:23) (cid:16)(cid:25) (cid:41)(cid:88)(cid:72)(cid:79)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:79)(cid:76)(cid:74)(cid:75)(cid:87) (cid:38)(cid:51)(cid:44)(cid:3)(cid:43)(cid:72)(cid:68)(cid:71)(cid:79)(cid:76)(cid:81)(cid:72)(cid:3)(cid:11)(cid:92)(cid:16)(cid:82)(cid:16)(cid:92)(cid:15)(cid:3)(cid:83)(cid:72)(cid:85)(cid:3)(cid:70)(cid:72)(cid:81)(cid:87)(cid:12) (cid:41)(cid:82)(cid:82)(cid:71)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:69)(cid:72)(cid:89)(cid:72)(cid:85)(cid:68)(cid:74)(cid:72)(cid:86) (cid:38)(cid:51)(cid:44)(cid:3)(cid:72)(cid:91)(cid:70)(cid:79)(cid:88)(cid:71)(cid:76)(cid:81)(cid:74)(cid:3)(cid:73)(cid:82)(cid:82)(cid:71)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:73)(cid:88)(cid:72)(cid:79) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:86)(cid:29)(cid:3)(cid:49)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:68)(cid:79)(cid:3)(cid:54)(cid:87)(cid:68)(cid:87)(cid:76)(cid:86)(cid:87)(cid:76)(cid:70)(cid:68)(cid:79)(cid:3)(cid:50)(cid:73)(cid:73)(cid:76)(cid:70)(cid:72)(cid:3)(cid:11)(cid:49)(cid:54)(cid:50)(cid:12)(cid:30)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:53)(cid:37)(cid:44)(cid:3)(cid:86)(cid:87)(cid:68)(cid:73)(cid:73)(cid:3)(cid:72)(cid:86)(cid:87)(cid:76)(cid:80)(cid:68)(cid:87)(cid:72)(cid:86)(cid:17) 11 As per the provisional data released by the National Statistical Office (NSO) on June 12, 2025. 12 The positive momentum recorded in CPI Food, Fuel and Core was 10, 80 and 30 bps, respectively. 38 RBI Bulletin June 2025 (cid:22)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:22)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:22)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:23)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:23)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:24)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:24)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:24)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:27) (cid:26) (cid:25) (cid:24) (cid:23) (cid:22) (cid:21)(cid:17)(cid:27) (cid:21) (cid:20) (cid:19) (cid:16)(cid:20) (cid:41)(cid:82)(cid:82)(cid:71)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:69)(cid:72)(cid:89)(cid:72)(cid:85)(cid:68)(cid:74)(cid:72)(cid:86) (cid:38)(cid:51)(cid:44)(cid:3)(cid:72)(cid:91)(cid:70)(cid:79)(cid:88)(cid:71)(cid:76)(cid:81)(cid:74)(cid:3)(cid:73)(cid:82)(cid:82)(cid:71)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:73)(cid:88)(cid:72)(cid:79) (cid:41)(cid:88)(cid:72)(cid:79)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:79)(cid:76)(cid:74)(cid:75)(cid:87) (cid:38)(cid:51)(cid:44)(cid:3)(cid:43)(cid:72)(cid:68)(cid:71)(cid:79)(cid:76)(cid:81)(cid:72)(cid:3)(cid:11)(cid:92)(cid:16)(cid:82)(cid:16)(cid:92)(cid:15)(cid:3)(cid:83)(cid:72)(cid:85)(cid:3)(cid:70)(cid:72)(cid:81)(cid:87)(cid:12) (cid:22)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:22)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:22)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:23)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:23)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:24)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:24)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:24)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48)State of the Economy ARTICLE (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:20)(cid:21)(cid:29)(cid:3)(cid:36)(cid:81)(cid:81)(cid:88)(cid:68)(cid:79)(cid:3)(cid:44)(cid:81)(cid:73)(cid:79)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:68)(cid:70)(cid:85)(cid:82)(cid:86)(cid:86)(cid:3)(cid:54)(cid:88)(cid:69)(cid:16)(cid:74)(cid:85)(cid:82)(cid:88)(cid:83)(cid:86)(cid:3) (cid:523)(cid:28)(cid:486)(cid:145)(cid:486)(cid:155)(cid:481)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:524) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:86)(cid:29)(cid:3)(cid:49)(cid:54)(cid:50)(cid:30)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:53)(cid:37)(cid:44)(cid:3)(cid:86)(cid:87)(cid:68)(cid:73)(cid:73)(cid:3)(cid:72)(cid:86)(cid:87)(cid:76)(cid:80)(cid:68)(cid:87)(cid:72)(cid:86)(cid:17) High-frequency food price data for June so far Edible oil prices, on the other hand, have firmed up- (up to June 20, 2025) shows a moderation in prices of driven by soybean, sunflower, and mustard oil, while pulses while prices of cereals have risen marginally. palm and groundnut oil prices have moderated. Among the key vegetables, prices of onion have recorded further correction, while potato and tomato (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:44)(cid:44)(cid:44)(cid:17)(cid:20)(cid:22)(cid:29)(cid:3)(cid:54)(cid:83)(cid:68)(cid:87)(cid:76)(cid:68)(cid:79)(cid:3)(cid:39)(cid:76)(cid:86)(cid:87)(cid:85)(cid:76)(cid:69)(cid:88)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:82)(cid:73)(cid:3)(cid:44)(cid:81)(cid:73)(cid:79)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:29) prices have increased (Chart III.14). (cid:48)(cid:68)(cid:92)(cid:3)(cid:21)(cid:19)(cid:21)(cid:24)(cid:3)(cid:11)(cid:38)(cid:51)(cid:44)(cid:16)(cid:38)(cid:82)(cid:80)(cid:69)(cid:76)(cid:81)(cid:72)(cid:71)(cid:12) (cid:523)(cid:28)(cid:486)(cid:145)(cid:486)(cid:155)(cid:481)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:524) Retail selling prices of petrol and diesel have remained broadly unchanged in June so far (up to June 20, 2025). Kerosene prices declined while LPG prices remained unchanged (Table III.8). The PMIs for May 2025 recorded an uptick in the rate of expansion of input prices for manufacturing and services. Selling price pressures, however, firmed up in services but moderated for manufacturing firms (Annex Chart A8). Rural labour wage growth continued to (cid:31)(cid:21) (cid:21)(cid:16)(cid:23) (cid:23)(cid:16)(cid:25) (cid:25)(cid:16)(cid:27) increase in April 2025, driven by occupations in (cid:49)(cid:82)(cid:87)(cid:72)(cid:29)(cid:3)(cid:48)(cid:68)(cid:83)(cid:3)(cid:76)(cid:86)(cid:3)(cid:73)(cid:82)(cid:85)(cid:3)(cid:76)(cid:79)(cid:79)(cid:88)(cid:86)(cid:87)(cid:85)(cid:68)(cid:87)(cid:76)(cid:89)(cid:72)(cid:3)(cid:83)(cid:88)(cid:85)(cid:83)(cid:82)(cid:86)(cid:72)(cid:86)(cid:3)(cid:82)(cid:81)(cid:79)(cid:92)(cid:17) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:86)(cid:29)(cid:3)(cid:49)(cid:54)(cid:50)(cid:30)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:53)(cid:37)(cid:44)(cid:3)(cid:86)(cid:87)(cid:68)(cid:73)(cid:73)(cid:3)(cid:72)(cid:86)(cid:87)(cid:76)(cid:80)(cid:68)(cid:87)(cid:72)(cid:86)(cid:17) the agricultural sector. Within agriculture, a pick-up RBI Bulletin June 2025 39ARTICLE State of the Economy Chart III.14: DCA Essential Commodity Prices a. Cereals b. Pulses Index (Jan 2024 = 100) Index (Jan 2024 = 100) 115 120 110 110 105 104.2 101.8 100 100 95.6 99.0 90 95 81.6 90 80 Wheat Rice Gram dal Tur/ Arhar dal Moong dal c. Vegetables d. Edible Oils Index (Jan 2024 = 100) Index (Jan 2024 = 100) Potato Onion Tomato Mustard oil Sunflower oil Groundnut oil Sources: Department of Consumer Affairs (DCA), Government of India (GoI); and RBI staff estimates. in wage rates for harvesting, picking and horticulture agricultural wage growth has remained stable since workers drove the overall wage growth. Non- January 2025 (Chart III.15). Table III.8: Petroleum Products Prices Item Unit Domestic Prices Month-over- month (per cent) Jun-24 May- Jun- May- Jun- 25 25^ 25 25^ Petrol ₹/litre 100.89 101.08 101.12 0.1 0.0 Diesel ₹/litre 90.68 90.51 90.53 0.0 0.0 Kerosene ₹/litre 46.61 41.51 40.19 -4.5 -3.2 (subsidised) LPG ₹/cylinder 813.25 863.25 863.25 0.0 0.0 (non-subsidised) Notes: 1. ^: For the period June 1-20, 2025. 2. Other than kerosene, prices represent the average Indian Oil Corporation Limited (IOCL) prices in four major metros (Delhi, Kolkata, Mumbai and Chennai). For kerosene, prices denote the average of the subsidised prices in Kolkata, Mumbai and Chennai. Sources: IOCL; Petroleum Planning and Analysis Cell (PPAC); and RBI staff estimates. 40 RBI Bulletin June 2025 42-naJ-02 42-beF-02 42-raM-02 42-rpA-02 42-yaM-02 42-nuJ-02 42-luJ-02 42-guA-02 42-peS-02 42-tcO-02 42-voN-02 42-ceD-02 52-naJ-02 52-beF-02 52-raM-02 52-rpA-02 52-yaM-02 52-nuJ-02 42-naJ-02 42-beF-02 42-raM-02 42-rpA-02 42-yaM-02 42-nuJ-02 42-luJ-02 42-guA-02 42-peS-02 42-tcO-02 42-voN-02 42-ceD-02 52-naJ-02 52-beF-02 52-raM-02 52-rpA-02 52-yaM-02 52-nuJ-02 250 200 150 116.0 100 104.4 50 70.8 0 42-naJ-02 42-beF-02 42-raM-02 42-rpA-02 42-yaM-02 42-nuJ-02 42-luJ-02 42-guA-02 42-peS-02 42-tcO-02 42-voN-02 42-ceD-02 52-naJ-02 52-beF-02 52-raM-02 52-rpA-02 52-yaM-02 52-nuJ-02 119.8 120 117.3 110 100 100.7 90 42-naJ-02 42-beF-02 42-raM-02 42-rpA-02 42-yaM-02 42-nuJ-02 42-luJ-02 42-guA-02 42-peS-02 42-tcO-02 42-voN-02 42-ceD-02 52-naJ-02 52-beF-02 52-raM-02 52-rpA-02 52-yaM-02 52-nuJ-02 Chart III.15: Rural Nominal Wage (Y-o-y, per cent) 8.0 7.5 7.6 7.0 6.5 6.4 6.0 5.5 5.5 5.0 4.5 4.0 Source: Labour Bureau, Ministry of Labour and Employment. 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA Agricultural Labourers Non Agricultural Labourers Average Rural WageState of the Economy ARTICLE IV. Financial Conditions Banks’ recourse to the marginal standing facility (MSF) was marginally lower, averaging ₹0.01 lakh System liquidity continued to be in surplus crore during the period May 16 to June 20, 2025, as during May and June (up to June 20, 2025). While against ₹0.02 lakh crore during the period April 16 to the increase in currency in circulation (CiC) has May 15, 2025. High SDF balances, coupled with tepid exerted some pressure on banking system liquidity in response to daily VRR auctions in the recent period FY:2025-26 so far, it has been offset by the expansion amidst muted credit offtake, suggest comfortable in liquidity from RBI’s durable liquidity measures liquidity conditions. In view of this, the Reserve Bank since January 2025. decided to discontinue daily VRR auctions effective The Reserve Bank injected a cumulative amount June 11, 2025. of ₹0.81 lakh crore into the banking system through The RBI also announced a reduction in the cash 18 fine-tuning variable rate repo (VRR) operations with maturities ranging from 1 to 3 days during the reserve ratio (CRR) by 100 bps to 3.0 per cent of net period May 16 to June 10, 2025. Reflecting these demand and time liabilities (NDTL) in a staggered developments, the average daily net absorption under manner during the latter half of the year. This the liquidity adjustment facility (LAF) stood at ₹2.47 reduction will be carried out in four equal tranches of lakh crore during the period May 16 to June 20, 2025, 25 bps each with effect from the fortnights beginning as compared to ₹1.42 lakh crore during the period September 6, October 4, November 1 and November April 16 to May 15, 2025 (Chart IV.1). Amidst surplus 29, 2025. The reduction in CRR would release primary liquidity conditions, the average balances under the liquidity of about ₹2.5 lakh crore into the banking standing deposit facility (SDF) continued to remain system by December 2025. Besides providing durable elevated and stood at ₹2.62 lakh crore during the liquidity, it will reduce the cost of funds for banks, period May 16 to June 20, 2025, as compared to ₹1.77 thereby facilitating monetary policy transmission to lakh crore during the period April 16 to May 15, 2025. the credit market. Chart IV.1: Liquidity Operations (₹ lakh crore) 4.5 3.5 2.5 1.5 0.5 -0.5 -1.5 -2.5 -3.5 -4.5 Daily SDF Variable rate reverse repo Net LAF MSF Variable rate repo Total absorption Source: RBI. RBI Bulletin June 2025 41 42-tcO-11 42-tcO-02 42-tcO-92 42-voN-7 42-voN-61 42-voN-52 42-ceD-4 42-ceD-31 42-ceD-22 42-ceD-13 52-naJ-9 52-naJ-81 52-naJ-72 52-beF-5 52-beF-41 52-beF-32 52-raM-4 52-raM-31 52-raM-22 52-raM-13 52-rpA-9 52-rpA-81 52-rpA-72 52-yaM-6 52-yaM-51 52-yaM-42 52-nuJ-2 52-nuJ-11 52-nuJ-02ARTICLE State of the Economy Money Market between the three-month CP and 91-day T-bill yields – narrowed to 79 bps during this period from 85 bps In the overnight money market, rates have in the preceding period, indicating improved funding reflected the evolving liquidity conditions. The conditions and lower credit risk in the short-term weighted average call rate (WACR) – the operating market. target of monetary policy – moderated further and hovered near the floor of the LAF corridor. The spread Government Securities (G-Sec) Market of WACR over the policy repo rate averaged (-) 20 bps In the fixed income segment, bond yields traded during the period May 16 to June 20, 2025, as against with a softening bias relative to the preceding month, (-) 14 bps during the period April 16 to May 15, 2025 on account of lower-than-expected CPI inflation (Chart IV.2a). Overnight rates in the collateralised prints and RBI’s OMOs. The yield on the 10-year segments, the triparty repo and market repo, moved G-sec benchmark declined to 6.25 per cent on June 5, in tandem with the WACR. 2025 from 6.27 per cent on May 15, 2025. Since then, however, it has edged up and was placed at 6.38 per The comfortable liquidity surplus in the banking cent on June 20, 2025 (Chart IV.3a). system has reinforced transmission of policy repo rate cuts to the term money market segments. Yields In comparison to a month ago, the domestic yield on three-month treasury bills (T-bills), certificates of curve shifted downwards across the short end of the deposit (CDs), and three-month commercial papers term structure, while it shifted upwards at the long (CPs) issued by non-banking financial companies end (Chart IV.3b). Between May 16 and June 20, 2025, (NBFCs) moderated during the period May 16 to June the average term spread (10-year G-sec yield minus 91- 20, 2025, as compared to the period April 16 to May day T-bills yield) increased by 29 bps over the period 15, 2025 (Chart IV.2b). The average risk premium April 16 to May 15, 2025, indicating a steepening of in the money market – measured by the spread the yield curve. Chart IV.2: Policy Corridor and Money Market Rates a. Policy Corridor and Call Rate b. Money Market Rates (Per cent) (Per cent) 7.5 7.0 6.5 6.0 5.5 5.27 5.0 Tri-party repo MMaarrkkeett rreeppoo 33--mmoonntthh TT--bbiillll Repo rate WACR MSF SDF 3-month CD 3-month CP (NBFC) Sources: RBI; CCIL; and Bloomberg. 42 RBI Bulletin June 2025 42-tcO-11 42-tcO-52 42-voN-8 42-voN-22 42-ceD-6 42-ceD-02 52-naJ-3 52-naJ-71 52-naJ-13 52-beF-41 52-beF-82 52-raM-41 52-raM-82 52-rpA-11 52-rpA-52 52-yaM-9 52-yaM-32 52-nuJ-6 52-nuJ-02 8.5 8.0 7.5 7.0 6.5 6.16 6.0 5.88 5.5 5.33 5.0 42-tcO-11 42-tcO-52 42-voN-8 42-voN-22 42-ceD-6 42-ceD-02 52-naJ-3 52-naJ-71 52-naJ-13 52-beF-41 52-beF-82 52-raM-41 52-raM-82 52-rpA-11 52-rpA-52 52-yaM-9 52-yaM-32 52-nuJ-6 52-nuJ-02State of the Economy ARTICLE Chart IV.3: Developments in the G-sec Market a. Movement in G-sec yield b. G-sec Yield Curve (Per cent) (Per cent, left scale; basis points, right scale) 7.3 7.0 6.7 6.38 6.4 6.1 6.01 5.8 5.86 5.5 Tenor (years) Change (June 20, 2025 over May 20, 2025) (RHS) 3 year 5 year 10 year 20-05-2025 20-06-2025 Sources: Bloomberg; FBIL; and RBI staff estimates. Corporate Bond Market Money and Credit Corporate bond issuances remained high at ₹0.93 Adjusting for the first-round impact of change in lakh crore in April 2025, nearly three times the funds CRR, reserve money (RM) recorded a growth of 7.3 raised in April 2024. The sharp fall in bond yields per cent (y-o-y) as on June 13, 2025 (8.1 per cent a year amidst a slow pass-through to lending rates has ago). During the current financial year, the growth in prompted corporates to increasingly take recourse to currency in circulation (CiC), the largest component the bond market for mobilizing resources. Corporate of RM, was significantly higher at 7.3 per cent (y-o-y), bond yields and the corresponding risk premia as compared with 5.9 per cent a year ago (Chart (except for AAA one-year) generally softened across IV.4). On the sources side (assets), growth in foreign tenors and rating spectrums during the period May currency assets accelerated to 5.6 per cent (y-o-y) as 16 - June 19, 2025 (Table IV.1). on June 13, 2025. Gold – the other major component Table IV.1: Corporate Bonds - Rates and Spread Spread (bps) Interest Rates (per cent) (Over Corresponding Risk-free Rate) Instrument Apr 16, 2025 – May 16, 2025 – Variation Apr 16, 2025 – May 16, 2025 – Variation May 15, 2025 June 19, 2025 May 15, 2025 June 19, 2025 1 2 3 (4 = 3-2) 5 6 (7 = 6-5) Corporate Bonds AAA (1-year) 6.96 6.77 -19 97 112 15 AAA (3-year) 7.14 6.87 -27 103 100 -3 AAA (5-year) 7.22 6.93 -29 101 89 -12 AA (3-year) 7.99 7.69 -30 188 183 -5 BBB- (3-year) 11.64 11.36 -28 550 549 -1 Note: Yields and spreads are computed as averages for the respective periods. Sources: FIMMDA; and Bloomberg. RBI Bulletin June 2025 43 42-tcO-11 42-tcO-52 42-voN-80 42-voN-22 42-ceD-60 42-ceD-02 52-naJ-30 52-naJ-71 52-naJ-13 52-beF-41 52-beF-82 52-raM-41 52-raM-82 52-rpA-11 52-rpA-52 52-yaM-90 52-yaM-32 52-nuJ-60 52-nuJ-02 7.5 40 7.02 30 7.0 6.84 20 10 6.5 0 6.0 -10 -20 5.5 -30 5.0 -40 1 2 3 4 5 6 7 8 9 01 11 21 31 41 51 61 71 81 91 02ARTICLE State of the Economy Chart IV.4: Growth in RM and M 3 (Y-o-y, per cent, left scale; ratio, right scale) 12 5.8 11 5.7 10 9 5.6 8 5.5 7 6 5.4 5 4 5.3 Money Multiplier (RHS) Reserve money (CRR adjusted) Money Supply Sources: RBI. of net foreign assets (NFA) – grew by 58.9 per cent, Scheduled commercial banks (SCBs) credit mainly due to increase in gold prices, leading to a growth14 moderated to 9.9 per cent, as on May 30, 2025 steady rise in its share in NFA, from 8.3 per cent as of (16.2 per cent a year ago) due to weaker momentum as end-March 2024 to 12.7 per cent as of June 13, 2025. well as unfavourable base effects (Chart IV.5a). SCBs’ As on May 30, 2025, money supply (M3) rose by 9.5 deposit growth (excluding the impact of the merger) per cent (y-o-y) [10.9 per cent a year ago].13 decelerated from 10.6 per cent, as on March 21, 2025 to 10.1 per cent, as on May 30, 2025, with the base 13 Excluding the impact of the merger of a non-bank with a bank (with effect from July 1, 2023). 14 Data are based on fortnightly Section 42 returns. Data exclude the impact of the merger of a non-bank with a bank. 44 RBI Bulletin June 2025 42-naJ-21 42-beF-61 42-raM-22 42-rpA-62 42-yaM-13 42-luJ-5 42-guA-9 42-peS-31 42-tcO-81 42-voN-22 42-ceD-72 52-naJ-13 52-raM-7 52-rpA-11 52-yaM-61 Chart IV.5: SCBs: Credit and Deposit Growth a. Credit b. Deposit (Y-o-y, per cent, left scale; percentage points, right scale) (Y-o-y, per cent, left scale; percentage points, right scale) 18 3 2 16 0.4 1 14 0 12 -1 10 9.9 -2 -1.2 8 -3 Note: SCBs’ data is inclusive of RRBs. Data exclude the impact of the merger of a non-bank with a bank. Source: Fortnightly Section 42 Returns, RBI. 42-rpA-5 42-yaM-3 42-yaM-13 42-nuJ-82 42-luJ-62 42-guA-32 42-peS-02 42-tcO-81 42-voN-51 42-ceD-31 52-naJ-01 52-beF-7 52-raM-7 52-rpA-4 52-yaM-2 52-yaM-03 14 3 1.3 2 13 1 12 0 11 -1 -1.4 -2 10 -3 10.1 9 -4 SCBs' credit momentum effect (RHS) SCBs' credit base effect (RHS) SCBs' credit growth 42-rpA-5 42-yaM-3 42-yaM-13 42-nuJ-82 42-luJ-62 42-guA-32 42-peS-02 42-tcO-81 42-voN-51 42-ceD-31 52-naJ-01 52-beF-7 52-raM-7 52-rpA-4 52-yaM-2 52-yaM-03 SCBs' deposit momentum effect (RHS) SCBs' deposit base effect (RHS) SCBs' deposit growthState of the Economy ARTICLE and momentum effects offsetting each other (Chart declined by 6 bps and 17 bps, respectively, during IV.5b). Banks are increasingly relying on CDs to meet the period February-April 2025 (Table IV.2). On the funding needs as competition intensified in the bulk deposit side, the weighted average domestic term deposit space. deposit rates (WADTDRs) on fresh and outstanding deposits moderated by 27 bps and 1 bp, respectively, Average bank credit growth to various sectors during the same period. of the economy softened significantly during the period April 2024 to April 2025.15 Growth in non- During the current easing cycle (February-April food bank credit declined to 11.2 per cent during the 2025), the decline in the WALR on fresh rupee loans fortnight ending April 18, 2025, from 15.3 per cent was marginally higher for public sector banks (PSBs) during the corresponding fortnight of the previous as compared to private sector banks (PVBs). For year.16 This was primarily driven by a moderation in outstanding loans, the transmission was higher for growth of credit to services sector and agriculture and PVBs (Chart IV.6a). In case of deposits, PSBs reduced allied activities. Personal loans growth also showed their fresh term deposit rates by a higher magnitude deceleration over a year ago, though on a sequential as compared to PVBs (Chart IV.6b). basis, it witnessed an uptick after witnessing a Equity Markets softening in the last four months (Annex Chart A9). Indian equity markets remained range-bound Deposit and Lending Rates in the second half of May amidst weak global cues, The 50-bps cut in the policy repo rate during following the downgrade in US sovereign credit rating, February-April 2025 reflected in banks’ repo-linked caution on the possible India-US trade deal, and external benchmark-based lending rates (EBLRs) and profit booking. Markets rose subsequently following marginal cost of funds-based lending rate (MCLR). the announcement of a record surplus transfer by Consequently, the weighted average lending rate the Reserve Bank to the government. Global tariff (WALR) on fresh and outstanding rupee loans of SCBs and geopolitical uncertainty imparted volatility Table IV.2: Transmission to Banks’ Deposit and Lending Rates (Variation in bps) Term Deposit Rates Lending Rates Period Repo Rate WADTDR- WADTDR- EBLR 1-Yr. MCLR WALR - Fresh WALR- Fresh Deposits Outstanding (Median) Rupee Loans Outstanding Deposits Rupee Loans Tightening Period +250 253 199 250 178 181 115 May 2022 to Jan 2025 Easing Phase -50 -27 -1 -50 -20 -6 -17 Feb 2025 to May* 2025 Notes: Data on EBLR pertain to 32 domestic banks. *: Data on WADTDR and WALR pertain to April 2025. WALR: Weighted Average Lending Rate; WADTDR: Weighted Average Domestic Term Deposit Rate; MCLR: Marginal Cost of Funds-based Lending Rate; EBLR: External Benchmark-based Lending Rate. Source: RBI. 15 Data are provisional. Sectoral non-food credit data is based on sector-wise and industry-wise bank credit (SIBC) return, which covers select banks accounting for about 95 per cent of total non-food credit extended by all SCBs, pertaining to the last reporting Friday of the month. Data exclude the impact of the merger of a non-bank with a bank. 16 For further details, refer to Sectoral Deployment of Bank Credit – April 2025 [https://www.rbi.org.in/Scripts/BS_PressReleaseDisplay.aspx?prid=60554] RBI Bulletin June 2025 45ARTICLE State of the Economy Chart IV.6: Transmission across Bank Groups (February 2025 - April 2025) a. Lending Rates b. Deposit Rate (Basis points) (Basis points) 0 10 0 1 -10 0 -13 -12 -15 -20 -18 -10 -8 -30 -20 -33 -40 -30 -28 -33 -50 -40 -53 -44 -60 -50 WALR WALR WADTDR WADTDR (Fresh rupee loans) (Outstanding rupee loans) (Fresh deposits) (Outstanding deposits ) PSBs PVBs Foreign banks PSBs PVBs Foreign banks Source: RBI. thereafter; however, larger-than-expected policy rate the BSE Sensex increasing by 2.7 per cent to close easing by the Reserve Bank led to an upward swing at 82,408 (Chart IV.7). The broader market indices in markets, boosting the banking and financial sector outperformed the benchmark, with the BSE Midcap stocks. Markets turned volatile subsequently amidst and BSE Smallcap indices gaining by 6.1 per cent and geopolitical tensions in the Middle East. Overall, 10.5 per cent, respectively, during May-June (up to Indian equity markets registered modest gains during the period May-June (up to June 20, 2025), with June 20, 2025). Chart IV.7: BSE Sensex and Institutional Flows (Index, left scale; ₹ thousand crores, right scale) 88000 90 80 85000 70 82000 60 50 79000 40 30 76000 20 73000 10 0 70000 -10 -20 67000 -30 64000 -40 -50 61000 -60 58000 -70 -80 55000 -90 Note: FPI and MF flows are represented on 15-days rolling sum basis. Source: Bloomberg. 46 RBI Bulletin June 2025 32-tcO 32-voN 32-ceD 42-naJ 42-beF 42-raM 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-baF 52-raM 52-rpA 52-yaM 52-nuJ FPI flows (RHS) Mutual fund flows (RHS) SensexState of the Economy ARTICLE Chart IV.8: Foreign Direct Investment Flows a. Gross and Net FDI b. Sector-wise Outward FDI (April 2025) (US$ billion) (US$ miliion) 100 81.0 71.3 50 10.1 7.2 8.8 0 2.3 3.9 1.9 -4.1 -1.7 -44.5 -51.5 -1.2 -3.2 -50 -16.7 -27.3 -100 Source: RBI. Foreign portfolio investors (FPIs) remained net India ranked 16th globally in FDI inflows and recorded buyers to the tune of ₹24,966 crore during May-June US$114 billion in greenfield investment in digital (up to June 20, 2025). Domestic institutional investors economy sectors over the last five years (2020-2024), (DIIs), including mutual funds and insurance the highest among all countries in the Global South.17 companies, also remained net buyers in the domestic Foreign portfolio investment (FPI) recorded equity markets to the tune of ₹1,24,429 crore during net inflows of US$1.7 billion in May 2025, driven May-June (up to June 20, 2025). External Sources of Finance Gross inward foreign direct investment (FDI) amounted to US$8.8 billion in April 2025, higher than US$5.9 billion in March 2025 and US$7.2 billion in April 2024 (Chart IV.8a). Manufacturing and business services accounted for nearly half of the gross FDI inflows in this month. Net outward FDI also increased, along with a moderation in repatriation. Top sectors for outward FDI included electricity, gas and water, and financial, insurance and business services, while major destinations included Singapore, Mauritius, and Germany (Chart IV.8b). Together, these movements resulted in net FDI inflows of US$3.9 billion in April 2025, more than double the level in April 2024. Furthermore, RBI Bulletin June 2025 47 42-3202 52-4202 42-rpA 52-rpA 0 500 1000 Electricity, Gas And Water Financial,Insurance And Business Services Transport, Storage And Communication Services Manufacturing Wholsale, Retail Trade, Restaurants And Hotels Agriculture And Mining Community, Social And Personal Services Construction Net outward FDI Repatriation/Disinvestment Miscellaneous Gross FDI Net FDI Chart IV.9: Foreign Portfolio Investments (US$ billion) 15 10 5 0 -5 -10 -15 Equity Debt Total Notes: 1. Debt also includes investments under the hybrid instruments. 2. *: Data up to June 20. Source: National Securities Depository Limited (NSDL). 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM *52-nuJ 17 World Investment Report, UNCTAD, 2025.ARTICLE State of the Economy by the equity segment (Chart IV.9). Equities gained Chart IV.10: External Commercial Borrowings - for the third consecutive month as the India- Registrations and Flows (US$ billion) Pakistan ceasefire, the US-China trade truce, and 15 better-than-expected corporate earnings results in Q4:2024-25 lifted investor sentiment and spurred 10 portfolio rebalancing towards Indian assets. Telecommunication, services, and capital goods 3.20 5 emerged as the top recipient sectors. The debt 2.92 segment, which had experienced outflows in the 0 previous month, observed a pause in net withdrawals in May, even as the yield differential between Indian -5 and US government bonds remained below 2 per cent for most of the month. External commercial borrowing (ECB) registrations Source: Form ECB, RBI. slowed to US$2.9 billion during April 2025, down from US$11 billion in March 2025 and US$4.3 billion in Foreign Exchange Market April 2024. Despite the slowdown, inflows outpaced The Indian rupee (INR) appreciated by 0.4 per outflows, resulting in positive net flows of US$3.2 cent (m-o-m) vis-à-vis the US dollar and exhibited billion in April 2025 (Chart IV.10). Notably, 72 per low volatility during May 2025 (Chart IV.11). cent of the total ECBs raised during April 2025 were Uncertainty surrounding the US trade and its fiscal intended for capital expenditure (capex), including policy contributed to a general strengthening of EME on-lending and sub-lending for capex. currencies vis-à-vis the US dollar. 48 RBI Bulletin June 2025 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA Registrations Net inflows Chart IV.11: Movements in Major Currencies against the US Dollar in May 2025 (Per cent, m-o-m, left scale; per cent, right scale) 5 2.0 4 1.5 3 2 0.4 1.0 1 0.5 0 -1 0.0 Notes: 1. Appreciation/depreciation (m-o-m) calculated using monthly average exchange rates. 2. US dollar (DXY) measures the movements of the US dollar against a basket of major currencies (Euro, Japanese yen, British pound, Canadian dollar, Swedish krona, Swiss franc). 3. For each currency, volatility is measured as the coefficient of variation (100*Standard Deviation/Mean) using daily exchange rate data for the month of May 2025. Sources: FBIL; Thomson Reuters; and RBI staff estimates. dnar nacirfA htuoS now naeroK tiggnir naisyalaM osep nacixeM thab dnaliahT osep enippilihP haipur naisenodnI xednI ycnerruC EME laer nailizarB dnuop KU nauy esenihC oruE eepur naidnI gnod esemanteiV ney esenapaJ rallod gnoK gnoH )YXD( ralloD SU Percentage change (+ appreciation/ - depreciation) Volatility (RHS)State of the Economy ARTICLE Chart IV.12: Movements in the 40-Currency Real Effective Exchange Rate a. Monthly Changes b. Decomposition of Monthly Changes (Index (2015-16 = 100), left scale; per cent, right scale) (Per cent) 110 4 108 106 2 104 101.1 102 100 0 98 0.3 96 -2 94 92 90 -4 Source: RBI. In real effective terms, the INR appreciated As on June 13, 2025, India’s foreign exchange (m-o-m) by 0.3 per cent in May 2025 as India’s reserves stood at US$699 billion, providing a cover inflation (on a m-o-m basis) was 0.9 percentage for more than 11 months of goods imports,18 and points higher than the weighted average inflation of for 97 per cent of external debt outstanding at end- its major trading partners, more than offsetting the December 2024 (Chart IV.13). depreciation in the nominal effective exchange rate (NEER) [Chart IV.12]. 18 However, the import cover for goods and services was around nine months. RBI Bulletin June 2025 49 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM 4 2 0.9 0.3 0 -0.6 -2 -4 Change in REER (RHS) REER 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 52-naJ 52-beF 52-raM 52-rpA 52-yaM Relative price effect Nominal exchange rate effect Chart IV.13: India’s Foreign Exchange Reserves (US$ billion, left scale; months, right scale) Foreign exchange reserves Import cover (RHS) Notes: 1. *: As on June 13, 2025. 2. The import cover data for December 2024 to June 2025 is based on annualised merchandise imports for the quarter ending December 2024, as per the balance of payments statistics. Source: RBI. 0.996 750 14 11.5 12 650 10 8 550 6 4 450 2 350 0 32-raM 32-nuJ 32-peS 32-ceD 42-raM 42-nuJ 42-peS 42-ceD 52-raM 52-rpA 52-yaM *52-nuJARTICLE State of the Economy V. Conclusion investment. A likely undershoot of inflation to below the target rate, at the margin, during the current Protracted trade policy uncertainties and rising trade barriers pose the risk of significantly scarring financial year and evidence of further anchoring the global economy. The intensifying geopolitical of inflation expectations provided the MPC with tensions too may further debilitate the already- the policy space to decisively focus on growth by weakened growth impulses. In this context, the frontloading the rate cut.19 trade policy outcomes in July, after the temporary The MPC also decided to change the stance tariff hiatus is over, and the future course of geo- from accommodative to neutral, considering the political events would likely shape the medium-term very limited space to further support growth in economic prospects. current circumstances after the cumulative 100 bps Amidst a challenging global environment reduction in the policy repo rate since February 2025. and heightened uncertainty, the Monetary Policy Going forward, as noted by the MPC in its resolution, Committee (MPC) in its meeting held during the MPC decided to remain data-dependent to chart June 4-6, 2025, decided by a majority vote (5-1) to reduce the policy repo rate by 50 bps to 5.50 per the future course of monetary policy and strike the cent to stimulate domestic private consumption and appropriate growth-inflation balance. 19 The MPC retained the real GDP growth projection for FY 2025-26 at 6.5 per cent. The headline CPI inflation projection for FY 2025-26 was revised downwards by 30 bps to 3.7 per cent. As per the survey of professional forecasters held in May 2025, headline CPI inflation is projected at 3.8 per cent for 2025-26 and at 4.2 per cent for 2026-27. The May 2025 round of the inflation expectations survey of households showed one-year ahead inflation expectations moderating by 20 bps. The May 2025 round of the rural consumer confidence survey also showed a moderation in the one year ahead inflation expectations by 40 bps (Annex Charts 10 and 11). 50 RBI Bulletin June 2025State of the Economy ARTICLE Annex (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:36)(cid:20)(cid:29)(cid:3)(cid:53)(cid:88)(cid:85)(cid:68)(cid:79)(cid:3)(cid:38)(cid:82)(cid:81)(cid:86)(cid:88)(cid:80)(cid:72)(cid:85)(cid:3)(cid:38)(cid:82)(cid:81)(cid:73)(cid:76)(cid:71)(cid:72)(cid:81)(cid:70)(cid:72)(cid:3)(cid:44)(cid:81)(cid:71)(cid:76)(cid:70)(cid:72)(cid:86) (cid:523)(cid:12)(cid:144)(cid:134)(cid:135)(cid:154)(cid:524) (cid:20)(cid:22)(cid:19) (cid:20)(cid:21)(cid:25)(cid:17)(cid:21) (cid:20)(cid:21)(cid:19) (cid:20)(cid:20)(cid:19) (cid:20)(cid:19)(cid:19) (cid:20)(cid:19)(cid:19)(cid:17)(cid:19) (cid:28)(cid:19) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:29)(cid:3)(cid:53)(cid:38)(cid:38)(cid:54)(cid:15)(cid:3)(cid:53)(cid:37)(cid:44)(cid:17) RBI Bulletin June 2025 51 (cid:22)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:22)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:23)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:23)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:24)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:24)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:24)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:36)(cid:21)(cid:29)(cid:3)(cid:56)(cid:85)(cid:69)(cid:68)(cid:81)(cid:3)(cid:38)(cid:82)(cid:81)(cid:86)(cid:88)(cid:80)(cid:72)(cid:85)(cid:3)(cid:38)(cid:82)(cid:81)(cid:73)(cid:76)(cid:71)(cid:72)(cid:81)(cid:70)(cid:72)(cid:3)(cid:44)(cid:81)(cid:71)(cid:76)(cid:70)(cid:72)(cid:86) (cid:523)(cid:12)(cid:144)(cid:134)(cid:135)(cid:154)(cid:524) (cid:20)(cid:22)(cid:19) 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(cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:29)(cid:3)(cid:41)(cid:72)(cid:71)(cid:72)(cid:85)(cid:68)(cid:79)(cid:3)(cid:53)(cid:72)(cid:86)(cid:72)(cid:85)(cid:89)(cid:72)(cid:3)(cid:37)(cid:68)(cid:81)(cid:78)(cid:3)(cid:82)(cid:73)(cid:3)(cid:49)(cid:72)(cid:90)(cid:3)(cid:60)(cid:82)(cid:85)(cid:78)(cid:17) (cid:22)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:22)(cid:21)(cid:16)(cid:69)(cid:72)(cid:41) (cid:22)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:22)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:22)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:22)(cid:21)(cid:16)(cid:81)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:74)(cid:88)(cid:36) (cid:22)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:22)(cid:21)(cid:16)(cid:87)(cid:70)(cid:50) (cid:22)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:22)(cid:21)(cid:16)(cid:70)(cid:72)(cid:39) (cid:23)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:23)(cid:21)(cid:16)(cid:69)(cid:72)(cid:41) (cid:23)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:23)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:81)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:74)(cid:88)(cid:36) (cid:23)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:87)(cid:70)(cid:50) (cid:23)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:23)(cid:21)(cid:16)(cid:70)(cid:72)(cid:39) (cid:24)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:24)(cid:21)(cid:16)(cid:69)(cid:72)(cid:41) (cid:24)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:24)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:24)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48)ARTICLE State of the Economy (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:36)(cid:23)(cid:29)(cid:3)(cid:44)(cid:81)(cid:73)(cid:79)(cid:68)(cid:87)(cid:76)(cid:82)(cid:81)(cid:3)(cid:42)(cid:68)(cid:83)(cid:3)(cid:11)(cid:36)(cid:70)(cid:87)(cid:88)(cid:68)(cid:79)(cid:3)(cid:143)(cid:139)(cid:144)(cid:151)(cid:149)(cid:3)(cid:55)(cid:68)(cid:85)(cid:74)(cid:72)(cid:87)(cid:12) (cid:523)(cid:19)(cid:135)(cid:148)(cid:133)(cid:135)(cid:144)(cid:150)(cid:131)(cid:137)(cid:135)(cid:3)(cid:146)(cid:145)(cid:139)(cid:144)(cid:150)(cid:149)(cid:524) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:86)(cid:29)(cid:3)(cid:37)(cid:79)(cid:82)(cid:82)(cid:80)(cid:69)(cid:72)(cid:85)(cid:74)(cid:30)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:53)(cid:37)(cid:44)(cid:3)(cid:86)(cid:87)(cid:68)(cid:73)(cid:73)(cid:3)(cid:72)(cid:86)(cid:87)(cid:76)(cid:80)(cid:68)(cid:87)(cid:72)(cid:86)(cid:17) 52 RBI Bulletin June 2025State of the Economy ARTICLE (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:36)(cid:24)(cid:29)(cid:3)(cid:55)(cid:85)(cid:72)(cid:81)(cid:71)(cid:3)(cid:76)(cid:81)(cid:3)(cid:53)(cid:72)(cid:89)(cid:72)(cid:81)(cid:88)(cid:72)(cid:3)(cid:53)(cid:72)(cid:70)(cid:72)(cid:76)(cid:83)(cid:87)(cid:86)(cid:3)(cid:82)(cid:73)(cid:3)(cid:87)(cid:75)(cid:72)(cid:3)(cid:56)(cid:81)(cid:76)(cid:82)(cid:81)(cid:3)(cid:42)(cid:82)(cid:89)(cid:72)(cid:85)(cid:81)(cid:80)(cid:72)(cid:81)(cid:87) (cid:11)(cid:36)(cid:83)(cid:85)(cid:76)(cid:79)(cid:16)(cid:48)(cid:68)(cid:85)(cid:70)(cid:75)(cid:15)(cid:3)(cid:21)(cid:19)(cid:21)(cid:23)(cid:16)(cid:21)(cid:24)(cid:12) (cid:523)(cid:19)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:3)(cid:145)(cid:136)(cid:3)(cid:10)(cid:7)(cid:19)(cid:524) (cid:20)(cid:23) (cid:20)(cid:20)(cid:17)(cid:24) (cid:20)(cid:20)(cid:17)(cid:24) (cid:20)(cid:21)(cid:17)(cid:19) (cid:20)(cid:21) (cid:20)(cid:19) (cid:27) (cid:25) (cid:23) (cid:20)(cid:17)(cid:22) (cid:20)(cid:17)(cid:25) (cid:20)(cid:17)(cid:25) (cid:21) (cid:19) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:86)(cid:29)(cid:3)(cid:56)(cid:81)(cid:76)(cid:82)(cid:81)(cid:3)(cid:37)(cid:88)(cid:71)(cid:74)(cid:72)(cid:87)(cid:3)(cid:39)(cid:82)(cid:70)(cid:88)(cid:80)(cid:72)(cid:81)(cid:87)(cid:86)(cid:30)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:38)(cid:42)(cid:36)(cid:17) RBI Bulletin June 2025 53 (cid:28)(cid:20)(cid:16)(cid:27)(cid:20)(cid:19)(cid:21) (cid:19)(cid:21)(cid:16)(cid:28)(cid:20)(cid:19)(cid:21) (cid:20)(cid:21)(cid:16)(cid:19)(cid:21)(cid:19)(cid:21) (cid:21)(cid:21)(cid:16)(cid:20)(cid:21)(cid:19)(cid:21) (cid:22)(cid:21)(cid:16)(cid:21)(cid:21)(cid:19)(cid:21) (cid:23)(cid:21)(cid:16)(cid:22)(cid:21)(cid:19)(cid:21) (cid:12)(cid:36)(cid:51)(cid:11)(cid:3)(cid:24)(cid:21)(cid:16)(cid:23)(cid:21)(cid:19)(cid:21) (cid:12)(cid:40)(cid:37)(cid:11)(cid:3)(cid:25)(cid:21)(cid:16)(cid:24)(cid:21)(cid:19)(cid:21) (cid:42)(cid:85)(cid:82)(cid:86)(cid:86)(cid:3)(cid:87)(cid:68)(cid:91)(cid:3)(cid:85)(cid:72)(cid:89)(cid:72)(cid:81)(cid:88)(cid:72) (cid:49)(cid:82)(cid:81)(cid:16)(cid:87)(cid:68)(cid:91)(cid:3)(cid:85)(cid:72)(cid:89)(cid:72)(cid:81)(cid:88)(cid:72) (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:36)(cid:25)(cid:29)(cid:3)(cid:55)(cid:85)(cid:72)(cid:81)(cid:71)(cid:3)(cid:76)(cid:81)(cid:3)(cid:40)(cid:91)(cid:83)(cid:72)(cid:81)(cid:71)(cid:76)(cid:87)(cid:88)(cid:85)(cid:72)(cid:3)(cid:82)(cid:73)(cid:3)(cid:87)(cid:75)(cid:72)(cid:3)(cid:56)(cid:81)(cid:76)(cid:82)(cid:81)(cid:3)(cid:42)(cid:82)(cid:89)(cid:72)(cid:85)(cid:81)(cid:80)(cid:72)(cid:81)(cid:87) (cid:11)(cid:36)(cid:83)(cid:85)(cid:76)(cid:79)(cid:16)(cid:48)(cid:68)(cid:85)(cid:70)(cid:75)(cid:15)(cid:3)(cid:21)(cid:19)(cid:21)(cid:23)(cid:16)(cid:21)(cid:24)(cid:12) (cid:523)(cid:19)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:3)(cid:145)(cid:136)(cid:3)(cid:10)(cid:7)(cid:19)(cid:524) (cid:21)(cid:19) (cid:20)(cid:24) (cid:20)(cid:20)(cid:17)(cid:25) (cid:20)(cid:19)(cid:17)(cid:28) (cid:20)(cid:20)(cid:17)(cid:19) (cid:20)(cid:19) (cid:24) (cid:22)(cid:17)(cid:21) (cid:22)(cid:17)(cid:21) (cid:22)(cid:17)(cid:20) (cid:19) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:86)(cid:29)(cid:3)(cid:56)(cid:81)(cid:76)(cid:82)(cid:81)(cid:3)(cid:37)(cid:88)(cid:71)(cid:74)(cid:72)(cid:87)(cid:3)(cid:39)(cid:82)(cid:70)(cid:88)(cid:80)(cid:72)(cid:81)(cid:87)(cid:86)(cid:30)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:38)(cid:42)(cid:36)(cid:17) (cid:28)(cid:20)(cid:16)(cid:27)(cid:20)(cid:19)(cid:21) (cid:19)(cid:21)(cid:16)(cid:28)(cid:20)(cid:19)(cid:21) (cid:20)(cid:21)(cid:16)(cid:19)(cid:21)(cid:19)(cid:21) (cid:21)(cid:21)(cid:16)(cid:20)(cid:21)(cid:19)(cid:21) (cid:22)(cid:21)(cid:16)(cid:21)(cid:21)(cid:19)(cid:21) (cid:23)(cid:21)(cid:16)(cid:22)(cid:21)(cid:19)(cid:21) (cid:12)(cid:36)(cid:51)(cid:11)(cid:3)(cid:24)(cid:21)(cid:16)(cid:23)(cid:21)(cid:19)(cid:21) (cid:12)(cid:40)(cid:37)(cid:11)(cid:3)(cid:25)(cid:21)(cid:16)(cid:24)(cid:21)(cid:19)(cid:21) (cid:53)(cid:72)(cid:89)(cid:72)(cid:81)(cid:88)(cid:72)(cid:3)(cid:72)(cid:91)(cid:83)(cid:72)(cid:81)(cid:71)(cid:76)(cid:87)(cid:88)(cid:85)(cid:72) (cid:38)(cid:68)(cid:83)(cid:76)(cid:87)(cid:68)(cid:79)(cid:3)(cid:72)(cid:91)(cid:83)(cid:72)(cid:81)(cid:71)(cid:76)(cid:87)(cid:88)(cid:85)(cid:72)ARTICLE State of the Economy (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:36)(cid:26)(cid:29)(cid:3)(cid:44)(cid:81)(cid:71)(cid:72)(cid:91)(cid:3)(cid:82)(cid:73)(cid:3)(cid:54)(cid:88)(cid:83)(cid:83)(cid:79)(cid:92)(cid:3)(cid:38)(cid:75)(cid:68)(cid:76)(cid:81)(cid:3)(cid:51)(cid:85)(cid:72)(cid:86)(cid:86)(cid:88)(cid:85)(cid:72)(cid:86)(cid:3)(cid:73)(cid:82)(cid:85)(cid:3)(cid:44)(cid:81)(cid:71)(cid:76)(cid:68) (cid:523)(cid:22)(cid:150)(cid:131)(cid:144)(cid:134)(cid:131)(cid:148)(cid:134)(cid:3)(cid:134)(cid:135)(cid:152)(cid:139)(cid:131)(cid:150)(cid:139)(cid:145)(cid:144)(cid:3)(cid:136)(cid:148)(cid:145)(cid:143)(cid:3)(cid:131)(cid:152)(cid:135)(cid:148)(cid:131)(cid:137)(cid:135)(cid:524) (cid:22) (cid:21) (cid:20) (cid:19) (cid:16)(cid:20) (cid:16)(cid:19)(cid:17)(cid:23)(cid:24) (cid:16)(cid:21) (cid:16)(cid:22) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:29)(cid:3)(cid:53)(cid:37)(cid:44)(cid:3)(cid:86)(cid:87)(cid:68)(cid:73)(cid:73)(cid:3)(cid:72)(cid:86)(cid:87)(cid:76)(cid:80)(cid:68)(cid:87)(cid:72)(cid:86)(cid:17)(cid:3) 54 RBI Bulletin June 2025 (cid:20)(cid:20)(cid:16)(cid:85)(cid:68)(cid:48) (cid:20)(cid:20)(cid:16)(cid:74)(cid:88)(cid:36) (cid:21)(cid:20)(cid:16)(cid:81)(cid:68)(cid:45) (cid:21)(cid:20)(cid:16)(cid:81)(cid:88)(cid:45) (cid:21)(cid:20)(cid:16)(cid:89)(cid:82)(cid:49) (cid:22)(cid:20)(cid:16)(cid:85)(cid:83)(cid:36) (cid:22)(cid:20)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:20)(cid:16)(cid:69)(cid:72)(cid:41) (cid:23)(cid:20)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:20)(cid:16)(cid:70)(cid:72)(cid:39) (cid:24)(cid:20)(cid:16)(cid:92)(cid:68)(cid:48) (cid:24)(cid:20)(cid:16)(cid:87)(cid:70)(cid:50) (cid:25)(cid:20)(cid:16)(cid:85)(cid:68)(cid:48) (cid:25)(cid:20)(cid:16)(cid:74)(cid:88)(cid:36) (cid:26)(cid:20)(cid:16)(cid:81)(cid:68)(cid:45) (cid:26)(cid:20)(cid:16)(cid:81)(cid:88)(cid:45) (cid:26)(cid:20)(cid:16)(cid:89)(cid:82)(cid:49) (cid:27)(cid:20)(cid:16)(cid:85)(cid:83)(cid:36) (cid:27)(cid:20)(cid:16)(cid:83)(cid:72)(cid:54) (cid:28)(cid:20)(cid:16)(cid:69)(cid:72)(cid:41) (cid:28)(cid:20)(cid:16)(cid:79)(cid:88)(cid:45) (cid:28)(cid:20)(cid:16)(cid:70)(cid:72)(cid:39) (cid:19)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:19)(cid:21)(cid:16)(cid:87)(cid:70)(cid:50) (cid:20)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:20)(cid:21)(cid:16)(cid:74)(cid:88)(cid:36) (cid:21)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:21)(cid:21)(cid:16)(cid:81)(cid:88)(cid:45) (cid:21)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:22)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:22)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:69)(cid:72)(cid:41) (cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:70)(cid:72)(cid:39) (cid:24)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:36)(cid:27)(cid:29)(cid:3)(cid:51)(cid:48)(cid:44)(cid:29)(cid:3)(cid:44)(cid:81)(cid:83)(cid:88)(cid:87)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:50)(cid:88)(cid:87)(cid:83)(cid:88)(cid:87)(cid:3)(cid:51)(cid:85)(cid:76)(cid:70)(cid:72)(cid:86) (cid:68)(cid:17)(cid:3)(cid:48)(cid:68)(cid:81)(cid:88)(cid:73)(cid:68)(cid:70)(cid:87)(cid:88)(cid:85)(cid:76)(cid:81)(cid:74) (cid:69)(cid:17)(cid:3)(cid:54)(cid:72)(cid:85)(cid:89)(cid:76)(cid:70)(cid:72)(cid:86) (cid:12)(cid:144)(cid:134)(cid:135)(cid:154)(cid:3)(cid:523)(cid:891)(cid:886)(cid:949)(cid:17)(cid:145)(cid:3)(cid:133)(cid:138)(cid:131)(cid:144)(cid:137)(cid:135)(cid:524) (cid:12)(cid:144)(cid:134)(cid:135)(cid:154)(cid:3)(cid:523)(cid:891)(cid:886)(cid:949)(cid:17)(cid:145)(cid:3)(cid:133)(cid:138)(cid:131)(cid:144)(cid:137)(cid:135)(cid:524) (cid:25)(cid:24) (cid:25)(cid:19) (cid:24)(cid:23)(cid:17)(cid:28) (cid:24)(cid:24)(cid:17)(cid:20) (cid:24)(cid:24) (cid:24)(cid:23)(cid:17)(cid:21) (cid:24)(cid:22)(cid:17)(cid:27) (cid:24)(cid:19) (cid:23)(cid:24) (cid:49)(cid:82)(cid:87)(cid:72)(cid:29)(cid:3)(cid:36)(cid:3)(cid:79)(cid:72)(cid:89)(cid:72)(cid:79)(cid:3)(cid:82)(cid:73)(cid:3)(cid:24)(cid:19)(cid:3)(cid:76)(cid:81)(cid:71)(cid:76)(cid:70)(cid:68)(cid:87)(cid:72)(cid:86)(cid:3)(cid:81)(cid:82)(cid:3)(cid:70)(cid:75)(cid:68)(cid:81)(cid:74)(cid:72)(cid:3)(cid:76)(cid:81)(cid:3)(cid:68)(cid:70)(cid:87)(cid:76)(cid:89)(cid:76)(cid:87)(cid:92)(cid:15)(cid:3)(cid:90)(cid:75)(cid:76)(cid:79)(cid:72)(cid:3)(cid:68)(cid:3)(cid:85)(cid:72)(cid:68)(cid:71)(cid:76)(cid:81)(cid:74)(cid:3)(cid:68)(cid:69)(cid:82)(cid:89)(cid:72)(cid:3)(cid:24)(cid:19)(cid:3)(cid:86)(cid:76)(cid:74)(cid:81)(cid:68)(cid:79)(cid:86)(cid:3)(cid:72)(cid:91)(cid:83)(cid:68)(cid:81)(cid:86)(cid:76)(cid:82)(cid:81)(cid:15)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:69)(cid:72)(cid:79)(cid:82)(cid:90)(cid:3)(cid:24)(cid:19)(cid:3)(cid:86)(cid:88)(cid:74)(cid:74)(cid:72)(cid:86)(cid:87)(cid:86)(cid:3)(cid:70)(cid:82)(cid:81)(cid:87)(cid:85)(cid:68)(cid:70)(cid:87)(cid:76)(cid:82)(cid:81)(cid:484) (cid:54)(cid:82)(cid:88)(cid:85)(cid:70)(cid:72)(cid:29)(cid:3)(cid:54)(cid:9)(cid:51)(cid:3)(cid:42)(cid:79)(cid:82)(cid:69)(cid:68)(cid:79)(cid:17) (cid:22)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:22)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:22)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:23)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:23)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:24)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:24)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:24)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:25)(cid:24) (cid:25)(cid:19) (cid:24)(cid:24) (cid:24)(cid:19) (cid:23)(cid:24) (cid:44)(cid:81)(cid:83)(cid:88)(cid:87)(cid:3)(cid:51)(cid:85)(cid:76)(cid:70)(cid:72)(cid:86) (cid:50)(cid:88)(cid:87)(cid:83)(cid:88)(cid:87)(cid:3)(cid:51)(cid:85)(cid:76)(cid:70)(cid:72)(cid:86) (cid:44)(cid:81)(cid:83)(cid:88)(cid:87)(cid:3)(cid:51)(cid:85)(cid:76)(cid:70)(cid:72)(cid:86) (cid:51)(cid:85)(cid:76)(cid:70)(cid:72)(cid:86)(cid:3)(cid:38)(cid:75)(cid:68)(cid:85)(cid:74)(cid:72)(cid:71) (cid:22)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:22)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:22)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:23)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:23)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:24)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:24)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:24)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48)State of the Economy ARTICLE (cid:38)(cid:75)(cid:68)(cid:85)(cid:87)(cid:3)(cid:36)(cid:28)(cid:29)(cid:3)(cid:54)(cid:72)(cid:70)(cid:87)(cid:82)(cid:85)(cid:68)(cid:79)(cid:3)(cid:39)(cid:72)(cid:83)(cid:79)(cid:82)(cid:92)(cid:80)(cid:72)(cid:81)(cid:87)(cid:3)(cid:82)(cid:73)(cid:3)(cid:37)(cid:68)(cid:81)(cid:78)(cid:3)(cid:38)(cid:85)(cid:72)(cid:71)(cid:76)(cid:87) (cid:68)(cid:17)(cid:3)(cid:36)(cid:74)(cid:85)(cid:76)(cid:70)(cid:88)(cid:79)(cid:87)(cid:88)(cid:85)(cid:72)(cid:3)(cid:38)(cid:85)(cid:72)(cid:71)(cid:76)(cid:87)(cid:3)(cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75) (cid:69)(cid:17)(cid:3)(cid:44)(cid:81)(cid:71)(cid:88)(cid:86)(cid:87)(cid:85)(cid:92)(cid:3)(cid:38)(cid:85)(cid:72)(cid:71)(cid:76)(cid:87)(cid:3)(cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75) (cid:3)(cid:523)(cid:155)(cid:486)(cid:145)(cid:486)(cid:155)(cid:481)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:524) (cid:3)(cid:523)(cid:155)(cid:486)(cid:145)(cid:486)(cid:155)(cid:481)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:524) (cid:21)(cid:24) (cid:21)(cid:19) (cid:20)(cid:24) (cid:20)(cid:19) (cid:28)(cid:17)(cid:21) (cid:24) (cid:19) (cid:70)(cid:17)(cid:3)(cid:54)(cid:72)(cid:85)(cid:89)(cid:76)(cid:70)(cid:72)(cid:86)(cid:3)(cid:38)(cid:85)(cid:72)(cid:71)(cid:76)(cid:87)(cid:3)(cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75) (cid:71)(cid:17)(cid:3)(cid:51)(cid:72)(cid:85)(cid:86)(cid:82)(cid:81)(cid:68)(cid:79)(cid:3)(cid:38)(cid:85)(cid:72)(cid:71)(cid:76)(cid:87)(cid:3)(cid:42)(cid:85)(cid:82)(cid:90)(cid:87)(cid:75) (cid:3)(cid:523)(cid:155)(cid:486)(cid:145)(cid:486)(cid:155)(cid:481)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:524) (cid:3)(cid:523)(cid:155)(cid:486)(cid:145)(cid:486)(cid:155)(cid:481)(cid:3)(cid:146)(cid:135)(cid:148)(cid:3)(cid:133)(cid:135)(cid:144)(cid:150)(cid:524) RBI Bulletin June 2025 55 (cid:22)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:22)(cid:21)(cid:16)(cid:81)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:74)(cid:88)(cid:36) (cid:22)(cid:21)(cid:16)(cid:87)(cid:70)(cid:50) (cid:22)(cid:21)(cid:16)(cid:70)(cid:72)(cid:39) (cid:23)(cid:21)(cid:16)(cid:69)(cid:72)(cid:41) (cid:23)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:23)(cid:21)(cid:16)(cid:81)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:74)(cid:88)(cid:36) (cid:23)(cid:21)(cid:16)(cid:87)(cid:70)(cid:50) (cid:23)(cid:21)(cid:16)(cid:70)(cid:72)(cid:39) (cid:24)(cid:21)(cid:16)(cid:69)(cid:72)(cid:41) (cid:24)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:20)(cid:21) (cid:20)(cid:19) (cid:27) (cid:25)(cid:17)(cid:26) (cid:25) (cid:23) (cid:21) (cid:19) (cid:22)(cid:21)(cid:16)(cid:85)(cid:83)(cid:36) (cid:22)(cid:21)(cid:16)(cid:81)(cid:88)(cid:45) (cid:22)(cid:21)(cid:16)(cid:74)(cid:88)(cid:36) (cid:22)(cid:21)(cid:16)(cid:87)(cid:70)(cid:50) (cid:22)(cid:21)(cid:16)(cid:70)(cid:72)(cid:39) 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(cid:23)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:23)(cid:21)(cid:16)(cid:79)(cid:88)(cid:45) (cid:23)(cid:21)(cid:16)(cid:83)(cid:72)(cid:54) (cid:23)(cid:21)(cid:16)(cid:89)(cid:82)(cid:49) (cid:24)(cid:21)(cid:16)(cid:81)(cid:68)(cid:45) (cid:24)(cid:21)(cid:16)(cid:85)(cid:68)(cid:48) (cid:24)(cid:21)(cid:16)(cid:92)(cid:68)(cid:48) (cid:38)(cid:88)(cid:85)(cid:85)(cid:72)(cid:81)(cid:87) (cid:20)(cid:3)(cid:92)(cid:72)(cid:68)(cid:85)(cid:3)(cid:68)(cid:75)(cid:72)(cid:68)(cid:71)Financial Conditions Index for India: A High-Frequency Approach ARTICLE Financial Conditions Index for because of news events, macroeconomic data releases and market microstructure issues. Thus, the FCI is India: A High-Frequency a valuable input for monetary policy as it provides Approach lead information on real economic activity, over and above the direct effects of monetary policy (Hatzius by Pulastya Bandyopadhyay, Avnish Kumar, et al., 2010). It can, therefore, serve as a guide on the effective stance of policy (Bowe et al., 2023). Pankaj Kumar and Indranil Bhattacharyya^ One of the key takeaways of the Global Financial This article attempts to construct a financial Crisis (GFC) was that financial innovation had made conditions index (FCI) for India at daily frequency, it difficult to capture broad financial conditions in using select indicators from the money, G-sec, corporate a small number of variables covering traditional bond, equity, and forex markets. The primary objective financial markets. Thus, FCI emerged as a key tool in is to construct a composite indicator that tracks overall assessing macro-financial conditions in the post-GFC conditions in financial markets at a high frequency. The era. Apart from gauging the state of financial markets, FCI assesses the degree of relatively tight or easy financial FCI has been used by policymakers and practitioners market conditions with reference to its historical average to predict the future state of the economy as well since 2012. The estimated FCI traces movements in as the risks associated with economic forecasts. financial conditions in India across both periods of The use of FCI in the conduct of monetary policy, relative calm as well as crisis episodes. The index suggests forecasting models and stress testing is still limited that in the aftermath of the pandemic, exceptionally among emerging market economy (EME) central easy financial condition was driven by the combined banks compared to their advanced economy (AE) impact of amiable conditions across all market segments. counterparts. Most studies in the Indian context Financial conditions continued to remain relatively easy relied on monthly or quarterly data to construct FCI, since mid-2023 before firming up from November 2024. thus constraining their use in reacting to sudden In the current financial year, however, it has remained market developments, real time policy making and congenial riding on a buoyant equity market and a forecasting. money market suffused with liquidity. In view of the above, this article attempts to construct a new FCI for India at daily frequency using Introduction select indicators from various market segments. A financial conditions index (FCI) is a summary The primary objective is to construct a summative measure that encapsulates the information contained measure that is able to track overall conditions in in a broad array of financial variables and helps financial markets. The paper is structured in the to gauge the relative tightness or ease in overall following manner: Section II presents an overview financial conditions. Monetary policy actions impact of the existing literature on construction of FCIs in financial conditions through the usual channels of the global as well as the Indian context. The choice of monetary transmission although financial conditions, variables and the empirical methodology are discussed independent of policy decisions, often change in Section III. Section IV evaluates the robustness of the derived measure and discusses its features and ^ The authors are from the Reserve Bank of India. They are grateful to an anonymous referee for comments and Priyanka Sachdeva for data support. drivers while Section V presents some concluding The views expressed in this article are those of the authors and do not represent the views of the Reserve Bank of India. observations. RBI Bulletin June 2025 57ARTICLE Financial Conditions Index for India: A High-Frequency Approach II. Related Literature Board’s index of coincident indicators (D’Antonio, 2008). The Bloomberg FCI index, on the other hand, The following discussion provides an overview of is an equally weighted sum of three major sub-indices the existing literature on financial condition indices, including indicators from money, bond, and equity with a focus on the methodological approaches markets (Rosenberg, 2009). Vector autoregressions and followed by global as well as Indian studies in this impulse-response functions were used to construct area. A vast literature has proliferated exploring the an FCI for the US; in addition to the usual indicators, construction of FCIs across AEs; however, EMEs in credit availability from bank lending survey was also general and India in particular have relatively drawn used to construct the FCI (Swiston, 2008). limited attention. As mentioned before, the concept of FCI gained prominence in the aftermath of the GFC. An FCI for the Asian economies was constructed International institutions and multilateral bodies like based on an unrestricted VAR using financial variables the International Monetary Fund (IMF), Organization viz., private sector credit growth, real lending rates, for Economic Co-operation and Development (OECD), interest rate spreads, lending standards, equity price Bank for International Settlements (BIS) and several AE movements and real effective exchange rate changes central banks have since refined and institutionalised (IMF, 2010). Subsequently, IMF staff economists have FCIs as part of their macro-financial surveillance combined this method with a dynamic factor model toolkit. (DFM) to further develop an index for the Asian economies (Osorio et al., 2011). These institutions Early work derived FCIs for the G7 countries as a have periodically improved the methodology to weighted average of the short-term real interest rate, construct their individual FCIs. Several studies on the effective real exchange rate, and real property and the US, the Euro Area, Sweden, Germany and Norway share prices by looking at reduced form coefficient further refined the methodology and updated their estimates and vector autoregression (VAR) impulse indices (Hatzius et al., 2010; Brave and Butters, 2011; responses (Goodhart and Hofmann, 2001). A Goldman Alsterlind et al., 2020; Metiu, 2022; Bowe et al., 2023). Sachs FCI was constructed as a weighted sum of a short-term bond yield, a long-term corporate yield, In the Indian context, the work on FCI gained exchange rate, and a stock market variable (Dudley and traction over the past decade. A financial conditions Hatzius, 2000; Dudley et al., 2005). Deutsche Bank uses index was first developed for India using monthly data principal component analysis (PCA) for constructing on money, bond, foreign exchange and stock markets, the index from a set of seven financial variables that using a PCA approach (Shankar, 2014). Subsequently, included the exchange rate, bond, stock, and housing a monthly financial conditions composite indicator market indicators (Hooper et al., 2007). Developed in was constructed based on ten indicators by using 2008, the OECD FCI is a weighted sum of six financial PCA to extract the top factors containing maximum variables with their weights being in proportion to their information (Roy et al., 2015). VAR-based weighted impact on GDP (Guichard and Turner, 2008; Guichard sum approach for five indicators as well as PCA using et al., 2009). Similarly, Citi Financial Conditions a larger set of ten indicators was used to estimate FCI Index is a weighted sum of six financial variables, at a monthly frequency (Khundrakpam et al., 2017). viz., corporate spreads, money supply, equity values, Similarly, a VAR-based weighted sum approach and mortgage rates, the trade-weighted dollar, and energy a DFM of five indicators were employed to compute prices. The weights were determined according to FCI at a quarterly frequency (Kumar et al., 2022). In reduced form forecasting equations of the Conference contrast, the CII-IBA Financial Conditions Index (FCI) is 58 RBI Bulletin June 2025Financial Conditions Index for India: A High-Frequency Approach ARTICLE based on a quarterly Financial Conditions Expectation form demand equations. On the other hand, the PCA Survey of major banks and financial institutions on extracts a common factor from a group of several their expectations of key financial and economic financial variables. PCA is purely a static estimation variables that determine financial conditions in the tool and does not incorporate information along Indian economy. the time dimension for constructing the index. In contrast, DFM allows for the incorporation of time- The construction of FCIs differ across studies in series dynamics of some finite order to extract the terms of the aim of the measure, indicators selected, latent factors (Brave and Butters, 2011). data frequency and econometric methodologies. The III. Constructing a Financial Conditions Index range of indicators included in the construction of various FCIs differ across studies, although there III.1 Selection of Variables are some commonalities. Most FCIs include some The existing literature provides valuable insights measures of interest rates, risk premia, equity market for selecting appropriate variables in the construction performance, exchange rates and volatility measures. of FCI. An FCI for India is constructed using twenty In terms of methodology, while early studies mostly financial market indicators at daily frequency. The used the weighted-sum approach and PCA, recent chosen indicators represent five market segments, literature has relied mostly on DFM or time-varying viz., (i) the money market; (ii) the Government parameter models to construct FCIs. In the weighted- securities (G-sec) market; (iii) the corporate bond sum approach, the weight of the chosen indicator market; (iv) the forex market; and (v) the equity is generally assigned based on the impact it has market (Chart 1). To some extent, the selection of on the target variable such as the real GDP. These variables is also influenced by the primary objective estimates or weights have been generated in a variety of this study, i.e., to construct a high frequency FCI, of ways, including simulations using large-scale thus necessitating the use of financial indicators that macroeconomic models, VAR models, or reduced- are readily available at a daily frequency. Chart 1: Financial Market Indicators Financial Conditions Index Money G-sec Corporate Forex Equity Market Market Bond Market Market Market 1. WAMMR 1. Yield Curve 1. 5-Yr AAA 1. India US 1. India VIX spread level Corp Bond 10-yr yield 2. PE level relative 2. WAMMR 2. Yield Curve Spread differential to 2-yr moving volatility slope 2. 5-Yr AA Corp 2. USD-INR 1M average 3. Net LAF / 3. Yield Curve Bond Spread ATM 3. BSE Sensex NDTL curvature 3. 3-Yr AAA volatility return 4. 3M CP Corp Bond 3. Currency 4. BSE Mid-Cap (NBFC) over Spread return return T-Bill 4. 3-Yr AA Corp 4. 1M forward 5. BSE Small-Cap Bond Spread premia return RBI Bulletin June 2025 59ARTICLE Financial Conditions Index for India: A High-Frequency Approach a. Money Market alter the borrowing cost for the government as well as other market players. Hence, indicators which capture The money market assumes special significance the dynamics of G-sec market are included in the in gauging financial market conditions as it is the FCI. G-sec market is represented by the latent factors fulcrum of monetary policy operations – most central of the sovereign yield curve i.e., level, slope, and banks operationalise monetary policy via the overnight curvature. The level2 of the yield curve has a positive money market. Monetary policy actions and stance association with financial conditions as an increase in get seamlessly conveyed to the overnight market, interest rate increases financing costs, thus tightening which then propagates through the money market financial conditions. The slope3 of the yield curve is spectrum. Hence, the operating target of monetary the term spread that captures the difference between policy in India, i.e., the weighted average call rate long term and short-term yields. Theoretically, if long- (WACR) becomes an important indicator of the money term rates are notably higher than short-term rates, market. The rates in the collateralised segment of the it indicates that market expects short-term rates to overnight market track the movements in WACR. Also, increase in the near future, leading to tighter financial the volume in collateralised money market – triparty conditions. Similarly, higher curvature4 implying repo and market repo – are significantly higher, which greater concavity of the yield curve and higher interest necessitates their inclusion; hence, the weighted rates in the middle of the term structure suggests average money market rate1 (WAMMR) is considered tighter financial conditions, besides reflecting market for our analysis. The WAMMR captures the cost of segmentation and preferred habitat of investors. overnight funds for banks and non-banks; however, Contrary to theoretical prediction, however, higher it is not the level of WAMMR but its deviation from slope and curvature contribute to easier financial the policy repo rate which is reflective of financial conditions in our empirical exercise, as they mostly conditions in the overnight money market. Hence, reflect very low short-term rates. we include WAMMR spread over the policy repo rate c. Corporate Bond Market as one of the indicators. Volatility in WAMMR and liquidity conditions [net balances under the liquidity The corporate bond market provides an alternative adjustment facility (LAF) adjusted for net demand avenue to raise medium and long-term funds for and time liabilities (NDTL)] are also considered. In private sector participants. Hence, bond yields serve order to capture the credit risk at the short end of the as a barometer for the health of the credit market. The interest rate spectrum, the spread of 3-month CP rate credit spreads – difference between corporate bond over 3-month T-bill rate is also included. yields and G-sec yields of corresponding maturity – offer insights into financial conditions. The change b. G-sec Market in credit spreads often signal change in credit risk The importance of the G-sec market lies in perceptions and investor sentiments about economic providing the risk-free term structure for pricing of conditions. This segment is represented by credit risk financial instruments issued by other sectors of the indicators across various ratings and tenors. Increase in economy. It also provides an avenue for raising the credit risk premia reflects higher risk associated with financing requirements of the government in meeting the private sector vis-à-vis the government. A higher the budgetary gap. Any change in G-sec yields would 2 Average yield of 91-day t-bill, and 3, 5, 10 and 30-year dated securities. 1 WAMMR is the weighted average of overnight money market rates with 3 Difference in yield between 10-year g-sec and 91-day t-bill. the weights being the respective volumes in each segment. 4 Measured as 2*(10-year yield) – (91-day t-bill yield + 30-year yield). 60 RBI Bulletin June 2025Financial Conditions Index for India: A High-Frequency Approach ARTICLE credit risk premium is indicative of tighter financial which may boost consumer spending and business conditions making borrowing more expensive for investment. Therefore, higher return in the equity corporates. market is associated with easier financial conditions. The PE ratio is indicative of how much investors are d. Forex Market willing to pay per rupee of earnings. Higher values Forex market indicators include India-US yield are realised when market sentiments are buoyant. differential, INR return5, 1-month forward premia Decline in the PE ratio and increase in volatility are and 1-month at-the-money (ATM) implied volatility to associated with tighter financial conditions. Hence, capture financial conditions in the foreign exchange the confluence of widening spreads in money and market. Higher India-US yield differential and rupee bond market, elevated market volatility, diminishing depreciation are assumed to be associated with tighter asset returns and shrinking volumes is reflective of a financial conditions in our analysis. This is because tightening in overall financial conditions. an increase in yield differential reflects relatively III.2 Empirical Methodology higher domestic interest rate, which compensates for the expected rupee depreciation and country risk This study uses daily data of twenty financial premium under the interest rate parity condition. market indicators for the period January 1, 2012 to The impact of rupee depreciation works through May 30, 2025 to construct FCI for India. All indicators trade and finance channels. Since, the trade channel are factored into the index in such a manner so that works with a lag and is found to be weaker, we have an increase in these indicate a tightening of financial considered the finance channel to be predominant in conditions. Accordingly, the transformations are the short run. Rupee depreciation leads to an increase carried out for select indicators so that a higher value in debt servicing cost, thus leading to tighter financial of the transformed variable indicates tighter financial conditions. Further, 1-month ATM implied volatility is conditions (Appendix Table 1). We employ both PCA a measure of market expectations of future volatility and DFM approach to estimate the FCI. of the currency exchange rate. Higher values depict (i) PCA Approach more volatility and hence more uncertainty. Increase in 1-month ATM volatility and forward premia is We use PCA to extract the common factor from the associated with tighter financial conditions. selected twenty indicators. PCA is a statistical technique used to reduce the dimensionality of a dataset by e. Equity Market transforming a large set of correlated variables into The equity market is represented mostly by price a smaller set of uncorrelated components. These PCs indicators capturing returns and volatility. The equity are linear combinations of the original variables that market indicators are return [Sensex, midcap and small capture the maximum variance in the data, thereby cap return, price to earnings (PE) ratio] and volatility retaining most of the information embedded in the (India VIX). Conditions in the stock market affect data while reducing its dimensionality. The loadings the ability of corporates to raise fresh capital. Higher associated with each principal component – derived returns attract greater FII and FPI inflows, which affect from the eigenvectors of the data’s covariance or valuations and have a positive impact on the overall correlation matrix – are used to construct indices or market sentiment. Higher stock prices enhance wealth, scores that summarize the information contained in 5 Y-o-Y change in INR/USD rate [appreciation (+) / depreciation (-)]. the original variables. RBI Bulletin June 2025 61ARTICLE Financial Conditions Index for India: A High-Frequency Approach lag polynomials λ(L) and ψ(L) are N q and q q Table 1: Contribution of Market Segments in the FCI matrices, respectively, and η is a q vector of Market Segment Contribution (in per cent) t × × serially uncorrelated mean zero innovations to the G-Sec 16.4 × 1 Corporate Bond 26.0 factors. The idiosyncratic disturbances are assumed Forex 21.6 to be uncorrelated with factor innovations at all leads Equity 23.0 and lags, that is E(ξ η ) for all k. The ith row of Money 13.0 t Source: Authors’ calculations. λ(L) is the dynamic fatc–ktor loading for the ith series ’ = 0 X . The qunobserved (latent) factors f are the source it t In our analysis, the first principal component of co-movement across observed indicators, which is explains about 40 per cent of the total variation in the the identification strategy to estimate this state-space chosen indicators. The variable loadings (Appendix model. We estimate the DFM for a single common Table 2) are observed to be on expected lines for most factor, which is the FCI, and allow for two lags in indicators, except for those of the slope and curvature Equation (2).6 Following the literature, we employ a of the yield curve. Contrary to theoretical prediction, two-step estimator in which the first step involves higher slope and curvature contribute to easier estimating the parameters of the model using an financial conditions in our empirical exercise, as ordinary least square (OLS) on principal components they mostly reflect lower rates at the short end of the and, in the next step, the factors are estimated using yield curve. The contributions of the various market the Kalman filter and smoother (Doz et al., 2011). The segments in the FCI are found to be well distributed factor loadings for the chosen indicators are presented (Table 1). in Appendix Table 3. In our empirical exercise, the FCI Since PCA is purely a static estimation tool and estimated using PCA broadly tracks the FCI estimated does not incorporate information along the time using the DFM approach. We present our results for dimension, we also use DFM to estimate the FCI. the FCI obtained from the DFM. (ii) DFM Approach IV. Evaluation of the FCI DFM is widely used to extract a common set FCI is a broader metric of the state of financial of underlying trends which captures the bulk of markets as it captures the interaction of financial covariation among a large set of time series indicators. conditions and economic activity. The index gives DFM lends itself naturally to the problem of index a sense of how tight or loose financial markets are construction, as in a DFM with a single underlying relative to their historical average. The FCI provides a unobserved factor, the estimate of the latent factor metric based on its historical average; in this context, stands for an index of the co-movement in the a zero value of FCI corresponds to a financial system indicators (Stock and Watson, 2016). We use a DFM operating at the historical average level of all the framework for the construction of the FCI: financial indicators included in the FCI, i.e., essentially, X λ(L)f ξ (1) t t t a “neutral” financial condition. A higher positive value f = ψ(L) f + η (2) of the FCI is indicative of tighter financial conditions. t t t -1 To present our results, we use the standardised FCI. w =h ere, X +is a N vector of observed time t Standardisation helps in interpreting the changes in series variables, variations in which are explained × 1 financial condition in terms of standard deviation by a reduced number of unobserved (latent) factors and mean-zero idiosyncratic components ξ. The 6 The model is estimated using the “dfms” package in R. t 62 RBI Bulletin June 2025Financial Conditions Index for India: A High-Frequency Approach ARTICLE Chart 2: FCI and its Drivers Taper 3.0 Tantrum COVID IL&FS Crisis Crisis 2.0 1.0 0.0 -1.0 -2.0 -3.0 Source: Authors’ calculations. units. For example, within our sample period, of crisis as well as periods of relative calm are well financial condition was at its tightest at end-July 2013 captured by the index. during the taper tantrum episode, with the estimated The peaks in FCI are associated with major events standardised FCI at 2.826 – almost a 3-standard like the taper tantrum in 2013, stress in the non- deviation tightening relative to the historical average. banking financial companies (NBFC) sector during the On the other hand, the FCI stood at -2.197 at mid-June Infrastructure Leasing and Financial Services (IL&FS) 2021 – indicating the exceptionally easy financial episode and the onset of the COVID-19 pandemic. conditions post-Covid. Chart 2 plots the estimated FCI and the drivers7 of the financial conditions. To During May to July 2013, apprehensions of the likely assess the reliability of the newly constructed index, tapering of US bond purchases under quantitative the following analysis examines the performance of easing (QE) triggered outflows of portfolio investment the index through a narrative approach. from EMEs including India, particularly from the The Index through History debt segment. This prompted increase in credit risk premiums in bond market and pressures on INR. The One way to evaluate the newly constructed index exceptional tightening of financial conditions during as a measure of financial conditions is to follow a the taper tantrum was primarily driven by bond and narrative approach and link it to significant events in the Indian financial system over the sample period. forex market (Chart 2). During the IL&FS episode, The estimated FCI closely tracks the evolution of bond and equity markets were the major drivers of financial conditions in India over the years and tightening financial conditions. Default by IL&FS captures the key turning points. Specific periods in September 2018 led to panic in the bond market amidst tight liquidity conditions in the system, 7 To decompose the changes in the FCI into contribution by the indicators, we regress the estimated FCI on the indicators and estimate thereby increasing the credit risk premium. The the coefficients using OLS. Contribution of a market is derived as the sum of the contributions of its constituent indicators. tremors were felt in the equity market also as retail RBI Bulletin June 2025 63 2102-10-30 2102-50-81 2102-01-10 3102-20-41 3102-60-03 3102-11-31 4102-30-92 4102-80-21 4102-21-62 5102-50-11 5102-90-42 6102-20-70 6102-60-22 6102-11-50 7102-30-12 7102-80-40 7102-21-81 8102-50-30 8102-90-61 9102-10-03 9102-60-51 9102-01-92 0202-30-31 0202-70-72 0202-21-01 1202-40-52 1202-90-80 2202-10-22 2202-60-70 2202-01-12 3202-30-60 3202-70-02 3202-21-30 4202-40-71 4202-80-13 5202-10-41 5202-50-03 Withdrawal of Ultra Accommodation Accommodative phase gninethgiT gnisaE G-sec Corp bond Forex Equity Money FCI (standardised)ARTICLE Financial Conditions Index for India: A High-Frequency Approach investors started selling shares of other NBFCs and change in the policy rate and the stance, followed by a redemption pressures grew on mutual funds. buoyant equity and G-Sec market. The next peak in the index is evident during the FCI and Economic Activity early COVID-19 period. The onset of the COVID-19 Apart from being a composite indicator of pandemic resulted in seizure of economic and financial conditions, the utility of FCI also lies in trading activity that triggered market turmoil on an its ability to predict or serve as the lead indicator of unprecedented scale. The tightening of financial economic activity. Fluctuations in financial conditions conditions at the beginning of the Covid period was are transmitted to the real economy; accordingly, driven by a sharp sell-off in the equity and corporate any change in FCI should correspond to variations bond markets. The exceptionally easy financial in real economic indicators. In our preliminary condition that followed this tightening was driven analysis to evaluate the robustness of FCI, we check by the combined impact of easing across all market the efficacy of FCI as the lead indicator of economic segments, facilitated by the conventional and activity proxied by the growth of index of industrial unconventional measures of the Reserve Bank during production (IIP). In doing so, we check whether there 2021-2022. The conditions continued to remain is any correlation between the FCI and IIP growth. relatively easy since mid-2023 before firming up from Chart (3) illustrates that IIP growth and FCI exhibit November 2024 on account of the relative tightness in a generally inverse relationship over the observed equity, bond and money markets triggered by the rising period, as also evidenced by a Pearson correlation US exceptionalism after the presidential elections. coefficient of (-) 0.32. After peaking in early March 2025, the FCI has since reverted to its historical average, suggesting close to Moreover, results from Granger causality test neutral financial conditions. The major drivers of the indicate that FCI granger causes IIP growth, suggesting easing during this period were easy money market a unidirectional predictive relationship between the conditions due to large liquidity injection by the RBI, two (Appendix Table 4). Chart 3: FCI and IIP Growth 20.0 2.5 2.0 15.0 1.5 10.0 1.0 5.0 0.5 0.0 0.0 -0.5 -5.0 -1.0 -10.0 -1.5 -15.0 -2.0 -20.0 -2.5 IIP FCI (RHS) Note: Data on IIP growth during Covid is not captured in the chart. Source: RBI; and Authors’ calculations. 64 RBI Bulletin June 2025 tnec reP 31-rpA 31-peS 41-beF 41-luJ 41-ceD 51-yaM 51-tcO 61-raM 61-guA 71-naJ 71-nuJ 71-voN 81-rpA 81-peS 91-beF 91-luJ 91-ceD 02-yaM 02-tcO 12-raM 12-guA 22-naJ 22-nuJ 22-voN 32-rpA 32-peS 42-beF 42-luJ 42-ceD xednIFinancial Conditions Index for India: A High-Frequency Approach ARTICLE V. Conclusion New Monetary Policy Regime, Global Economics Paper No. 44. The newly constructed FCI for India assesses the degree of relatively tight or easy financial market Dudley, W., J. Hatzius, and E. McKelvey, (April 8, conditions with reference to its historical average 2005), Financial Conditions Need to Tighten Further, since 2012. The FCI is based on twenty financial US Economics Analyst, Goldman Sachs Economic market indicators at daily frequency for a long period Research. and closely tracks the turning points in financial Goodhart, C. and B. Hofmann (2001), “Asset Prices, conditions, as observed across major episodes in the Financial Conditions, and the Transmission of sample period. Further work in this regard would Monetary Policy”, Proceedings, Federal Reserve Bank incorporate quantity variables and lower frequency of San Francisco, issue Mar. indicators, and the predictive power of financial Guichard, S. and D. Turner, (September 2008), conditions as a lead indicator of future economic “Quantifying the effect of financial conditions on activity will be evaluated with the objective of US activity”, OECD Economics Department Working onboarding this index as a regular input for monetary Papers. policy formulation in India. Guichard, Stephanie, David Haugh and David Turner References: (2009), “Quantifying the effect of financial conditions Alsterlind, J., Lindskog, M. & von Brömsen, T. (2020), in the Euro Area, Japan, United Kingdom and United “An index for financial conditions in Sweden”, Staff States”, OECD Economics Department Working memo, Sveriges Riksbank. Papers, No. 677. Brave, Scott A. and R. Andrew Butters (2011), Hatzius, J., Hooper, P., Mishkin, F.S., Schoenholtz, “Monitoring financial stability: a financial conditions K.L., and Watson, M.W. (2010). Financial Conditions approach”, Economic Perspectives, issue Q I, pp. 22- Indexes: A Fresh Look After the Financial Crisis. NBER 43. Working Paper No. 16150. Bowe, F., Gerdrup, K.R., Maffei-Faccioli, N., and Olsen, Hooper, P., T. Mayer and T. Slok, (June 11, 2007). H. (2023). A high-frequency financial conditions index “Financial Conditions: Central Banks Still Ahead for Norway. Staff Memo No. 1, Norges Bank. of Markets”, Deutsche Bank, Global Economic Perspectives. D’Antonio, P., Appendix, pages 26–28, in DiClemente, R. and K. Schoenholtz (September 26, 2008), “A View International Monetary Fund (2010). “A Financial of the U.S. Subprime Crisis”, EMA Special Report, Conditions Index for Asia”, In Regional Economic Citigroup Global Markets Inc. Outlook: Asia and Pacific. Washington, DC. October. Doz, C., Giannone, D. and Reichlin, L. (2011). A Khundrakpam, J.K., Kavediya, R., and Anthony, J.M. two-step estimator for large approximate dynamic (2017). Estimating Financial Conditions Index for factor models based on Kalman filtering. Journal of India. Journal of Emerging Market Finance, 16(1), 61- Econometrics, 164(2011), 188-205. 89. Dudley, W., and J. Hatzius (June 8, 2000), The Goldman Kumar, S., Gulati, S., and Deepmala (2022). Sachs Financial Conditions Index: The Right Tool for a Transmission of Financial Conditions to Fixed RBI Bulletin June 2025 65ARTICLE Financial Conditions Index for India: A High-Frequency Approach Investment in India: An Empirical Investigation. RBI Shankar, A. (2014), “A Financial Conditions Index for Bulletin, November, 115–126. India”, RBI Working Paper Series No. 08. Osorio, Carolina, Runchana Pongsaparn, and D. Filiz Stock, J.H., and Watson, M.W. (2016), “Dynamic Factor Unsal (2011). A Quantitative Assessment of Financial Models, Factor-Augmented Vector Autoregressions, Conditions in Asia. IMF Working Paper 11/173. and Structural Vector Autoregressions in Washington, DC: International Monetary Fund. Macroeconomics”, Handbook of Macroeconomics, Rosenberg, M., (2009), “Financial Conditions Watch”, Volume 2, 415-525. Bloomberg. Swiston, Andrew (2008), “A U.S. financial conditions Roy, I., Biswas, D., and Sinha, A. (2015). Financial Conditions Composite Indicator (FCCI) for India. IFC index: putting credit where credit is due”, IMF Bulletin No. 39, BIS. Working Paper Series, No. 08/161. 66 RBI Bulletin June 2025Financial Conditions Index for India: A High-Frequency Approach ARTICLE Appendix Table 1: Financial Indicators Sr. No. Indicator Transformation Source Money Market 1. WAMMR Spread over Repo rate N RBI 2. 3M CP Spread over 3M T-bill Rate N Bloomberg 3. Net LAF adjusted for NDTL In negative terms RBI 4. WAMMR Volatility N RBI G-Sec Market 5. Yield curve level N Bloomberg 6. Yield curve slope N Bloomberg 7. Yield curve curvature N Bloomberg Corporate bond Market 8. Spread of 3-year AAA CB over 3-yr G-sec N Bloomberg 9. Spread of 3-year AA CB over 3-yr G-sec N Bloomberg 10. Spread of 5-year AAA CB over 5-yr G-sec N Bloomberg 11. Spread of 5-year AA CB over 5-yr G-sec N Bloomberg Equity Market 12. BSE Sensex return In negative terms Bloomberg 13. BSE Mid-Cap return In negative terms Bloomberg 14. BSE Small-Cap return In negative terms Bloomberg 15. PE level relative to 2yr moving average Reciprocal of PE level Bloomberg 16. India VIX N Forex Market 17. India US 10yr yield differential N Bloomberg 18. USD-INR 1M ATM volatility N Bloomberg 19. Currency return In negative terms Bloomberg 20. 1M forward premia N Bloomberg Note: All indicators are transformed in a manner such that an increase in these indicate relative tightening of financial conditions. ‘N’ denotes no transformation. RBI Bulletin June 2025 67ARTICLE Financial Conditions Index for India: A High-Frequency Approach Table 2: Variable Loadings (from PCA) Indicator Variable Loadings Money Market WAMMR Spread over Repo rate 0.165 3M CP Spread over 3M T-bill Rate 0.173 Net LAF adjusted for NDTL 0.250 WAMMR Volatility 0.098 G-Sec Market Yield curve level 0.244 Yield curve slope -0.228 Yield curve curvature -0.230 Corporate bond Market Spread of 3-year AAA CB over 3-yr G-sec 0.314 Spread of 3-year AA CB over 3-yr G-sec 0.256 Spread of 5-year AAA CB over 5-yr G-sec 0.220 Spread of 5-year AA CB over 5-yr G-sec 0.219 Equity Market BSE Sensex return 0.233 BSE Mid-Cap return 0.259 BSE Small-Cap return 0.279 PE level relative to 2yr moving average 0.141 India VIX 0.107 Forex Market India US 10yr yield differential 0.175 USD-INR 1M ATM volatility 0.270 Currency return 0.267 1M forward premia 0.203 Source: Authors’ calculations. 68 RBI Bulletin June 2025Financial Conditions Index for India: A High-Frequency Approach ARTICLE Table 3: Factor Loadings (from DFM) Indicator Factor Loadings Money Market WAMMR Spread over Repo rate 0.115 3M CP Spread over 3M T-bill Rate 0.182 Net LAF adjusted for NDTL 0.202 WAMMR Volatility 0.075 G-Sec Market Yield curve level 0.182 Yield curve slope -0.179 Yield curve curvature -0.186 Corporate bond Market Spread of 3-year AAA CB over 3-yr G-sec 0.317 Spread of 3-year AA CB over 3-yr G-sec 0.283 Spread of 5-year AAA CB over 5-yr G-sec 0.239 Spread of 5-year AA CB over 5-yr G-sec 0.250 Equity Market BSE Sensex return 0.243 BSE Mid-Cap return 0.276 BSE Small-Cap return 0.294 PE level relative to 2yr moving average 0.140 India VIX 0.110 Forex Market India US 10yr yield differential 0.141 USD-INR 1M ATM volatility 0.237 Currency return 0.249 1M forward premia 0.151 Source: Authors’ calculations. Table 4: Granger Causality Test Pairwise Granger Causality Tests Sample: 2013M04 2025M04 Lags: 2 Null Hypothesis: Obs F-Statistic Prob. FCI does not Granger Cause IIP 143 3.29952 0.0398 IIP does not Granger Cause FCI 0.45890 0.6329 Source: Authors’ estimates. RBI Bulletin June 2025 69Balance Sheet Channel of Monetary Policy Transmission: ARTICLE Insights from Indian Manufacturing Firms Balance Sheet Channel of long-run (RBI, 2020). While the extant literature has empirically examined the effectiveness of monetary Monetary Policy Transmission: policy transmission in India across various channels Insights from Indian [Patra et al., (2016); Khundrakpam and Jain (2012); Mohan (2008) etc.], the studies on balance sheet Manufacturing Firms channel which operates by affecting a firm’s financial health – cashflow and net worth – influencing its Bhavesh Salunkhe, Sapna Goel, borrowing capacity and investment decisions are Amit Kumar, Preetika, Kunal Priyadarshi limited [Angelopoulou and Gibson (2009); Bernanke and Satyananda Sahoo^ and Gertler (1995); and Oliner and Rudebusch (1994) etc.] and under-researched in India. Monetary policy partly influences investment Tight monetary policy can weaken firms’ financial through the balance sheet channel – a mechanism where positions by lowering equity prices, reducing net interest rate changes affect a firm’s financial health worth, and raising borrowing costs, thereby limiting (cashflow and net worth) – which in turn impacts its access to credit and curbing investment. This borrowing capacity and investment decisions. The study mechanism— central to the balance sheet channel of investigates the existence of balance sheet channel of monetary policy transmission— has been observed monetary policy transmission in India by estimating in countries like Japan (Masuda, 2015) and the U.S. instrumental variable fixed-effects panel regression (Kashyap et al., 1992). Weaker balance sheets raise model for manufacturing firms spanning 2003-2023. the external finance premium—the additional cost It assesses whether investment sensitivity to cashflow of external funds (such as debt and equity) over changes during different monetary policy phases and internal funds—making borrowing more expensive varies between constrained (small, highly leveraged) and further constraining investment, particularly for and unconstrained (large, less leveraged) firms. The financially constrained firms. results confirm the presence of the balance sheet channel, This study seeks to fill this gap by examining particularly among small firms. whether changes in monetary policy affects the sensitivity of investment to cashflow in Introduction Indian manufacturing firms (2002-03 to 2022- Investment plays a critical role in driving 23), and whether this sensitivity differs between economic growth, and monetary policy is a key financially constrained (small, highly leveraged) and tool used by central banks to influence investment unconstrained (large, less leveraged) firms. Following activity. The empirical estimates suggest that a one Angelopoulou and Gibson (2009), the study estimates percentage point reduction in the real policy interest Tobin’s Q-model to assess the cashflow sensitivity of rate can increase the investment rate by about 9 investment under different monetary policy periods. basis points (bps) in the short-run and 109 bps in the The findings suggest that the balance sheet channel of monetary policy transmission is active amongst ^ Bhavesh Salunkhe, Sapna Goel, Amit Kumar and Satyananda Sahoo (ssahoo@rbi.org.in) are from the Department of Economic and Policy the Indian manufacturing firms, particularly in small Research (DEPR), Kunal Priyadarshi is from Financial Markets Regulation Department (FMRD) and Preetika was a research intern in DEPR. The views firms, while no conclusive differences are found expressed in this article are those of the authors and do not represent the views of the Reserve Bank of India (RBI). across leverage groups. RBI Bulletin June 2025 71ARTICLE Balance Sheet Channel of Monetary Policy Transmission: Insights from Indian Manufacturing Firms The rest of the study is organised as follows – section II highlights stylised facts about investment in India, followed by literature review in section III. Section IV discusses data sources and methodology, while section V elucidates the empirical exercise and results. Finally, section VI concludes. II. Investment Trends in India: Stylised facts Post the liberalisation reforms of 1991, fixed investment1 in India gained traction with manufacturing sector commanding an average share of 31.4 per cent in overall gross fixed capital formation (GFCF) during 1995-99. Since 2000s, however, with a shift in foreign direct investment inflows from manufacturing to services sector and emergence of new services activity, India’s overall GFCF has been reduced, while private corporates have managed to driven by services thereafter. Fixed investment rate hold ground albeit with some moderation since 2015- in India peaked at 35.8 per cent in 2007-08. It was 16. Investment by the household sector, however, 28.5 per cent in 2019-20, before regaining some has risen since 2016-17 (Chart 2). momentum in the post-pandemic period (Chart 1). At the institutional level, within the manufacturing Fazzari et al. (1988) conducted a pioneering sector, the share of public sector investment has study estimating the sensitivity of investment Chart 1: Fixed Investment across Sectors Note: All the computations are at current prices. Sources: National Statistical Office (NSO); and Authors’ calculations. 72 RBI Bulletin June 2025 )tnec rep ni( FCFG ni erahS PDG fo tnec reP 100 38 36 80 34 32 60 30 28 40 26 20 24 22 0 20 Services Agriculture, forestry & fishing Fixed Investment Rate (RHS) Manufacturing Industry (excl manufacturing) 29-1991 39-2991 49-3991 59-4991 69-5991 79-6991 89-7991 99-8991 00-9991 10-0002 20-1002 30-2002 40-3002 50-4002 60-5002 70-6002 80-7002 90-8002 01-9002 11-0102 21-1102 31-2102 41-3102 51-4102 61-5102 71-6102 81-7102 91-8102 02-9102 12-0202 22-1202 32-2202 42-3202 Chart 2: GFCF in Manufacturing Sector 1 Since, GFCF roughly comprises 90 per cent share in overall investment, the section focuses on trends relating to fixed investment only. FCFG fo tnec reP 35 30 25 20 15 10 5 0 Notes: (i) All the computations are at current prices; (ii) public sector comprises investment by departmental and non-departmental enterprises; and (iii) investment by the private corporates for the period prior to 2011-12 has been computed by subtracting the public sector investment from the registered manufacturing GFCF. Sources: NSO; and Authors’ calculations. 29-1991 39-2991 49-3991 59-4991 69-5991 79-6991 89-7991 99-8991 00-9991 10-0002 20-1002 30-2002 40-3002 50-4002 60-5002 70-6002 80-7002 90-8002 01-9002 11-0102 21-1102 31-2102 41-3102 51-4102 61-5102 71-6102 81-7102 91-8102 02-9102 12-0202 22-1202 32-2202 42-3202 Private Corporates Public Sector HouseholdsBalance Sheet Channel of Monetary Policy Transmission: ARTICLE Insights from Indian Manufacturing Firms Chart 3: Cashflow and Investment by Size of the Firms a. Small Firms b. Large Firms Notes: 1. Cashflow is defined as a ratio of profit after tax to total assets. 2. Investment is a ratio of difference of gross fixed assets (F(t)-F(t-1)) divided by average of total assets ((T(t)+T(t-1))/2). 3. Small firms comprise those with an average size of total assets less than the 50th percentile of the average size distribution over the sample period. All the remaining firms constitute the large category. 4. The sample size of small firms and large firms are 390 and 389, respectively. Sources: ProwessIQ, Centre for Monitoring Indian Economy (CMIE); and Authors’ calculations. to cashflow across different types of firms. They Recent trends (especially 2021-23), however, found that internal and external finances are not indicate a shift towards improving cashflow, perfectly substitutable, with internal funds offering possibly to manage debt better or strengthen a cost advantage. Notably, investment by financially liquidity. In contrast, significantly higher cashflow constrained firms is highly sensitive to cashflow, than investment for less leveraged firms, implies unlike unconstrained firms that can more easily a cautious and self-sufficient approach focused on access external financing. Similarly, firm-level data maintaining liquidity and reducing financial risk for Indian manufacturing firms reveal that both size (Chart 4). and leverage2 of firms significantly affect investment Different phases of monetary policy tightening, decisions. While large firms have historically based on policy rate movements, have been maintained higher investment and cashflow, small identified for the study period. The first phase firms experienced a notable rise in both during (October 2005-September 2008) witnessed a 300 bps 2021–23, indicating a potential shift in financial hike in repo rate and 400 bps in cash reserve ratio dynamics (Chart 3). (CRR). Owing to heightened supply-side pressures, Highly leveraged firms had consistently higher the second phase (March 2010-March 2012) featured investment than cashflow until 2021-23, when a 375 bps repo rate increase. In the third phase cashflow surpassed investment. These firms (September 2013-December 2014), the repo rate rose have initially focused on high investment despite by 75 bps and the fourth phase (June 2018-January moderate cashflow, especially during 2008-09. 2019) saw a 50 bps hike due to elevated crude oil prices and certain policy measures. Lastly, in the 2 The criteria of splitting the sample based on size and leverage have been discussed in detail in section IV. fifth phase (May 2022–Dec 2023), a 250 bps increase RBI Bulletin June 2025 73 tnec reP tnec reP 10 9 8 7 6 5 4 3 2 1 0 Investment Cashflow Investment Cashflow 80-3002 90-8002 41-9002 02-4102 12-0202 32-1202 10 9 8 7 6 5 4 3 2 1 0 80-3002 90-8002 41-9002 02-4102 12-0202 32-1202ARTICLE Balance Sheet Channel of Monetary Policy Transmission: Insights from Indian Manufacturing Firms Chart 4: Cashflow and Investment based on Firm’s Leverage a. Highly Leveraged Firms b. Less Leveraged Firms Notes: 1. Cashflow is defined as a ratio of profit after tax to total assets. 2. Investment is a ratio equal to difference of gross fixed assets (F(t)-F(t-1)) divided by average of total assets ((T(t)+T(t-1))/2). 3. The firms with mean leverage ratio greater than 50th percentile across all firms over sample period are considered as highly leveraged. 4. The sample size of highly leveraged firms and less leveraged firms are 389 and 390, respectively. Sources: ProwessIQ, CMIE; and Authors’ calculations. was implemented to counter inflationary risks comprising balance sheet and bank lending, (iii) exchange rate and (iv) asset prices (Mishkin, 1995). (Chart 5). 3 In recent times, however, expectations channel has III. Literature Review gained significance, given the forward-looking nature The literature on transmission mechanisms of of the monetary policy. monetary policy, in general, documents four key The credit channel, which gained recognition channels – (i) interest rate, (ii) credit aggregates following the seminal work of Bernanke and Gertler 74 RBI Bulletin June 2025 tnec reP tnec reP 12 10 8 6 4 2 0 Investment Cashflow Investment Cashflow 80-3002 90-8002 41-9002 02-4102 12-0202 32-1202 12 10 8 6 4 2 0 80-3002 90-8002 41-9002 02-4102 12-0202 32-1202 Chart 5: Changes in Monetary Policy Rates Note: Shaded area depicts the phases of monetary policy tightening based on the direction of change in the policy repo rate. Sources: RBI; and Authors’ calculations. 3 The details of each phase are discussed in Annex Table 1. tnec reP 10 9 8 7 6 5 4 3 2 30-naJ 30-peS 40-yaM 50-naJ 50-peS 60-yaM 70-naJ 70-peS 80-yaM 90-naJ 90-peS 01-yaM 11-naJ 11-peS 21-yaM 31-naJ 31-peS 41-yaM 51-naJ 51-peS 61-yaM 71-naJ 71-peS 81-yaM 91-naJ 91-peS 02-yaM 12-naJ 12-peS 22-yaM 32-naJ 32-peS Repo Reverse repo CRRBalance Sheet Channel of Monetary Policy Transmission: ARTICLE Insights from Indian Manufacturing Firms (1995), highlights that due to the existence of monetary policy transmission and its impact on information asymmetries, investment is impacted Indian manufacturing firms. by net worth of a firm. Therefore, even a minor IV. Data Description and Methodology monetary policy shock can have a notable impact The study uses firm level annual data on 779 on firm’s investment behaviour. Reinforcing these listed Indian manufacturing firms spanning 2002- findings, Angelopoulou and Gibson (2009); and 03 to 2022-23. The data have been sourced from the Oliner and Rudebusch (1996) examined the balance ProwessIQ database, maintained by the Centre for sheet channel and concluded that firms, especially Monitoring Indian Economy (CMIE). The measures the constrained ones, become more sensitive to cashflow fluctuations during periods of monetary to capture monetary policy phases are constructed policy tightening as the cost of external finance would using data from Handbook of Statistics on Indian be higher relative to internal financing. Similarly, Economy published by the RBI. using loan-level data, Aysun and Hepp (2013) also For disaggregated analysis, following Masuda supported the existence of balance sheet channel. (2015) and Balfoussia and Gibson (2018), the firms However, several studies such as Erickson and Whited are categorised by size (small vs. large) and leverage (2000), present a critique of cashflow as a variable by (high vs. less). The size of a firm is measured by reporting no statistical significance of the variable. its total assets. Average total assets of a firm are While Sahoo and Bishnoi (2023) and Rafique et al. computed over the sample period thereby, providing (2021) posit a positive significant impact of cashflow the size distribution of the firms. Small firms are on firm investment, Cleary (1991) inferred that the then defined as those with an average total assets unconstrained firms are more sensitive to cashflow below the 50th percentile of the size distribution, availability to fund their investments. Additionally, while the rest are classified as large. Being relatively a positive link has been affirmed between a firm’s young and less established, small firms typically Tobin’s Q ratio and their investment in studies by have limited collateral and are considered financially Fazzari et al. (1988), Masuda (2015) and Rafique et constrained (Angelopoulou and Gibson, 2007). al. (2021). Sahoo and Bishnoi (2023) further support Similarly, leverage, the amount of debt a firm uses this association, specifically, for manufacturing firms to finance its assets, is measured as the ratio of total in India. (long-term) debt to equity. Firms above the median The prevailing literature underscores the leverage ratio are classified as highly leveraged. Due intricate nature of monetary policy transmission to higher default risk, such firms also face financial and its impact on firm’s investment behaviour. constraints. Further, financial indicators such as Tobin’s Q ratio IV.1 Variable Description and profit after tax (PAT) offer insights into firm’s valuation and cashflow dynamics, highlighting their Dependent Variable ( ): ‘Firm level critical role in investment decisions under varying investment’ defined as annual chiatnge in gross fixed INV financial conditions. Building on this vast body of assets of the firm, scaled by the firm’s average total knowledge and dearth of such studies in Indian assets over period ‘t’ and ‘t-1’ has been used. This context, this study aims to gauge the understanding adjustment ensures that the investment metric is and effectiveness of the balance sheet channel of standardised across companies of different sizes, RBI Bulletin June 2025 75ARTICLE Balance Sheet Channel of Monetary Policy Transmission: Insights from Indian Manufacturing Firms thereby, controlling for bias due to variation in policy dummies at monthly frequency have company size within the sample. been constructed that take value ‘1’ during the months of monetary policy tightening Independent Variables and ‘0’ otherwise. They are then averaged (i) Cashflow ( ) over the year to match yearly frequency it Profit aftCear sthax (PAT) scaled by firm’s total assets of firm level data. Different tightening has been used as a proxy for a firm’s cashflow phases of monetary policy identified (Angelopoulou and Gibson, 2009; and Gupta and based on direction of change in the policy Mahakud, 2019). repo rate are October 2005-September (ii) Tobin’s Q Ratio ( ) 2008, March 2010-March 2012, September 2013-December 2014, June 2018-January it It is a ratio deQverlaotpioed to compare the market 2019, and May 2022-December 2023. value of a firm’s assets to their replacement cost. A Q > 1 implies that the market values the firm’s (b) Weighted Average Call Money Rate (WACR): assets more than the cost of replacing its assets, Over the estimation period, the Reserve suggesting an incentive to invest. On the other hand, Bank followed two broad approaches of a Q < 1 indicates that the firm’s assets are valued monetary policy, viz., multiple indicator less by the market than their replacement cost, approach (2003 to Q3 of 2016) and inflation signalling disinvestment. It thus helps to control for targeting framework thereafter, with repo firm’s opportunities and incentives to investment. rate as the main tool. Initially, policy However, the replacement cost of capital is not signals were conveyed through both repo directly observable and accordingly, as suggested in and reverse repo rates under the liquidity literature, the average total assets has been taken as adjustment facility, with the effective rate its proxy. Following Sahoo and Bishnoi (2023), the depending on liquidity conditions (Kapur Q-ratio has been specifically tailored for the Indian and Behera, 2012). Since May 2011, the context as follows: repo rate became the sole policy rate and the WACR was explicitly recognised as the operating target of monetary policy due to faster transmission of signals (RBI, 2011). where, ‘Market value of the equity’ is the product Under the current flexible inflation-targeting of ‘shares outstanding’ and ‘weighted average price framework adopted in May 2016, the WACR of share’ of the firm, while ‘Book value of debt’ is continues to be the operating target of proxied by ‘Long term borrowing’. monetary policy and this study, therefore, (iii) Monetary Policy Measures uses the WACR to represent monetary policy phases. Two monetary policy measures have been used to represent the monetary policy phases in India. (iv) Real GDP Growth (a) Narrative Measure (NM): Following Annual real GDP growth has been included with Angelopoulou and Gibson (2007), monetary one-period lag. 76 RBI Bulletin June 2025Balance Sheet Channel of Monetary Policy Transmission: ARTICLE Insights from Indian Manufacturing Firms (v) Dummy Variables value and replacement cost of assets). The Hausman specification test suggests rejection of random effects Taking cognisance of three major crises that have model in favour of fixed effects. occurred during the sample period, three dummy variables are included – global financial crisis (GFC) V. Summary Statistics and Econometric Findings dummy (2008-09), high non-performing assets (NPA) V.1 Descriptive Statistics dummy (2013-18) and Covid-19 dummy (2020-22). Small firms, being younger and less established, These dummies take value ‘1’ for crisis years and ‘0’ have lower and more volatile investment and otherwise. cashflow than large firms on average. Highly IV.2 Model Specification leveraged firms exhibit higher average investment Instrumental variable fixed-effects panel than their less leveraged counterparts. Moreover, the regression model has been used to estimate the lower average Tobin’s Q ratios of small and highly relationship among investment, firm specific leveraged firms suggest that large and less leveraged financial variables, real GDP growth and monetary firms enjoy better opportunities and incentives to policy. This relationship can be expressed in the form invest (Table 1). of following regression model, also called augmented V.2 Econometric Results specification of Q-model (Fazzari et al., 1988). As stated, NM and WACR have been used to represent monetary policy phases. While column (1) of Table 2 shows the baseline specification of Equation 1 (specified in section IV.2), columns (2) where, subscript ‘it’ indicates firm ‘i’ in period and (3) include interaction of cashflow variable ‘t’. MPM is monetary policy measure in the with NM and WACR, respectively, to test if cashflow t-1 previous period, controls for firm-specific fixed sensitivity of investment varies with monetary policy effects, and is the error term. The instrumental phases. Assuming one-year period as sufficient for it variable fixed effects model has been used due to the transmission process, lagged values of monetary ε possible endogeneity of ‘Q’ variable in the model policy measures (NM and WACR) have been used in (investment decisions of firms affect their market the interaction term. Table 1: Descriptive Statistics Firms Based on Size Based on Leverage Small Large Highly Leveraged Less Leveraged Investment Cash Tobin’s Investment Cash Tobin’s Investment Cash Tobin’s Investment Cash Tobin’s Flow Q Flow Q Q Flow Q Flow Mean 0.03 0.04 0.98 0.05 0.06 1.56 0.05 0.05 1.16 0.03 0.06 1.38 Median 0.02 0.03 0.64 0.03 0.06 0.87 0.03 0.04 0.73 0.02 0.05 0.74 Std Dev. 0.19 0.17 1.24 0.12 0.11 2.04 0.14 0.14 1.43 0.18 0.16 1.95 Average Total Assets ( million) Average Leverage Ratio 1320.88 61902.67 49.20 1.11 ₹ No. of Firms 390 389 389 390 Note: Investment, Cashflow and Tobin’s Q are ratios. Sources: ProwessIQ, CMIE; and Authors’ calculations. RBI Bulletin June 2025 77ARTICLE Balance Sheet Channel of Monetary Policy Transmission: Insights from Indian Manufacturing Firms The cashflow coefficient in normal times is firms face financing constraints, making them rely statistically significant and negative4 (Columns 2 and more on internal funds for investment. This suggests 3 in Table 2), implying less investment in the current the presence of balance sheet channel of monetary period indicated by a build-up of cashflow. The policy transmission across manufacturing firms. Alternatively, during expansionary monetary policy interaction term, however, is positive and statistically periods, the firms are less constrained by internal significant for both measures of monetary policy. It finances (cashflow) as access to external finance implies that during periods of tight monetary policy, becomes easier. This underscores the proposition Table 2: Investment, Cash flow and Monetary that monetary policy affects the investment not only Policy (All Firms) through cost of capital channel but also by increasing Independent All firms (Dependent Variable: Investment) external finance premium. Tobin’s ‘Q’ is positive Variables 1 Monetary Policy Measures and statistically significant across all specifications, 2 3 reflecting the vital role played by capital markets in (Narrative (WACR) Measure) a firm’s investment opportunities. GDP growth also Constant 0.0244*** 0.0247*** 0.0239*** has a positive and statistically significant impact on (0.0040) (0.0040) (0.0040) Tobin’s Q 0.0158*** 0.0156*** 0.0153*** firm’s investment. Covid-19 and NPA dummies are (0.0017) (0.0016) (0.0017) negative and statistically significant, as expected. Cashflow 0.0004 -0.0229** -0.1786*** (0.0094) (0.0111) (0.0324) Delving into the sub-samples, Tables 3 and 4 Cashflow*MPM(-1) 0.0786*** 0.0331*** demonstrate the estimation results for small and (0.0202) (0.0057) GDPgr(-1) 0.0017*** 0.0016*** 0.0017*** large firms, respectively.5 In normal times, the (0.0005) (0.0005) (0.0005) cashflow coefficient is negative and statistically GFC_Dummy(-1) 0.0058 0.0050 0.0031 (0.0063) (0.0063) (0.0067) significant for small firms, while for large firms, it NPA_Dummy(-1) -0.0619*** -0.0609*** -0.0635*** is positive but statistically significant only in case of (0.0032) (0.0032) (0.0032) model with WACR (Table 4). When monetary policy is Covid_Dummy(-1) -0.0301*** -0.0282*** -0.0242*** (0.0051) (0.0051) (0.0052) tight, the cashflow sensitivity of small firms becomes Observations 15580 15580 15580 positive and statistically significant (columns 2 and 3 No. of Firms 779 779 779 in Table 3), showing that their investment decisions Wald Test =1246.39 =1257.54 =1288.80 depend more on their internal funds due to financial = 0.00 = 0.00 = 0.00 constraints. Conversely, an expansionary monetary F-test fixed effects F(778,14795) F(778,14794) F(778,14794) policy would ease these constraints, reducing their =1.53 =1.54 =1.53 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 reliance on cashflow for investment. For large firms, Hausman =176.23 =181.48 =171.82 tight monetary policy reduces cashflow sensitivity. specification test = 0.00 = 0.00 = 0.00 These findings are in consonance with Angelopoulou Notes: (i) ‘***’, ‘**’, and ‘*’ indicate statistical significance at 1 per cent, and Gibson (2009); and Oliner and Rudebusch (1994) 5 per cent and 10 per cent, respectively; (ii) Figures in parentheses are standard errors; (iii) Estimation is by instrumental variable method where and indicate the presence of balance sheet channel a lag of Tobin’s Q, cashflow term, lag of GDPgr, crises dummies are used as instruments; and (iv) F-test is test of significance of fixed effects. in case of small firms. Source: Authors’ calculations. 5 For robustness check, in an alternate scenario, small firms have also 4 Although cash flow coefficient is negative and statistically significant been defined as the firms whose average size is less than the 75th in the current period, it was positive and statistically significant at lag 1, percentile of average size distribution over the sample period. The results indicating lagged impact of cash flow on investment of firms. are similar and provided in the annex tables 2(a) and 2(b). 78 RBI Bulletin June 2025Balance Sheet Channel of Monetary Policy Transmission: ARTICLE Insights from Indian Manufacturing Firms Table 3: Investment, Cash flow and Monetary Policy Table 4: Investment, Cash flow and Monetary Policy (Small Firms) (Large Firms) Independent Small firms (Dependent Variable: Investment) Independent Large firms (Dependent Variable: Investment) Variables Variables 1 Monetary Policy Measures 1 Monetary Policy Measures 2 3 2 3 (Narrative (WACR) (Narrative (WACR) Measure) Measure) Constant 0.0162** 0.0172** 0.0173** Constant 0.0313*** 0.0314*** 0.0326*** (0.0067) (0.0063) (0.0067) (0.0042) (0.0042) (0.0042) Tobin’s Q 0.0226*** 0.0216*** 0.0198*** Tobin’s Q 0.0129*** 0.0129*** 0.0131*** (0.0036) (0.0036) (0.0036) (0.0015) (0.0015) (0.0015) Cashflow 0.0032 -0.0373** -0.3794*** Cashflow 0.0005 0.0116 0.1178*** (0.0132) (0.0162) (0.0524) (0.0137) (0.0153) (0.0359) Cashflow*MPM(-1) 0.1274*** 0.0688*** Cashflow*MPM(-1) -0.0472* -0.0237*** (0.0293) (0.0091) (0.0269) (0.0068) GDPgr(-1) 0.0012 0.0011 0.0013 GDPgr(-1) 0.0021*** 0.0022*** 0.0020*** (0.0008) (0.0008) (0.0008) (0.0005) (0.0004) (0.0005) GFC_Dummy(-1) 0.0069 0.0061 0.0031 GFC_Dummy(-1) 0.0034 0.0041 0.0059 (0.0108) (0.0107) (0.0107) (0.0064) (0.0064) (0.0064) NPA_Dummy(-1) -0.0596*** -0.0579*** -0.0614*** NPA_Dummy(-1) -0.0649*** -0.0656*** -0.0636*** (0.0055) (0.0055) (0.0055) (0.0033) (0.0033) (0.0033) Covid_Dummy(-1) -0.0271*** -0.0241*** -0.0155* Covid_Dummy(-1) -0.0368*** -0.0379*** -0.0415*** (0.0090) (0.0090) (0.0092) (0.0052) (0.0052) (0.0054) Observations 7800 7800 7800 Observations 7780 7780 7780 No. of Firms 390 390 390 No. of Firms 389 389 389 Wald Test =312.25 =329.56 = 378.98 Wald Test =1605.24 =1613.38 =1615.39 = 0.00 = 0.00 = 0.00 = 0.00 = 0.00 = 0.00 F-test fixed effects F(389, 7404) F(389,7403) F(389,7403) F-test fixed effects F(388, 7385) F(388,7384) F(388,7384) =1.38 =1.38 =1.37 =1.87 =1.87 =1.88 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Hausman =151.21 =168.96 =152.79 Hausman =45.00 =45.63 =17.88 pecification test specification test = 0.00 = 0.00 = 0.00 = 0.00 = 0.00 = 0.00 Notes: (i) ‘***’, ‘**’, and ‘*’ indicate statistical significance at 1 per cent, Notes: (i) ‘***’, ‘**’, and ‘*’ indicate statistical significance at 1 per cent, 5 per cent and 10 per cent, respectively; (ii) Figures in parentheses are 5 per cent and 10 per cent, respectively; (ii) Figures in parentheses are standard errors; (iii) Estimation is by instrumental variable method where standard errors; (iii) Estimation is by instrumental variable method where a lag of Tobin’s Q, cash flow term, lag of GDPgr, crises dummies are used as a lag of Tobin’s Q, cash flow term, lag of GDPgr, crises dummies are used as instruments; and (iv) F-test is test of significance of fixed effects. instruments; and (iv) F-test is test of significance of fixed effects. Source: Authors’ calculations. Source: Authors’ calculations. Tobin’s ‘Q’ has positive and statistically investment activity due to supply chain disruptions, significant impact on investment of both small heightened global uncertainty, falling demand and large firms. Moreover, the NPA and Covid-19 and increased underutilisation of capacity. GDP dummies are negative and statistically significant growth variable is significant only in case of large as expected for both firm sizes. While the impact firms. GFC dummy has a positive but statistically of these crises on small firms is expected, insignificant impact on investment of both large firms may have experienced a decline in firm sizes. RBI Bulletin June 2025 79ARTICLE Balance Sheet Channel of Monetary Policy Transmission: Insights from Indian Manufacturing Firms The estimation results for highly leveraged in specific cases. During tight monetary policy, the and less leveraged firms are presented in Tables 5 cashflow sensitivity of investment becomes positive and 6, respectively.6 In normal times, the cashflow for both firm types, suggesting increased reliance coefficient is negative for both highly leveraged and on internal funds and presence of balance sheet less leveraged firms but is only statistically significant channel. Unlike in case of size based classification, the difference in cashflow sensitivity of investment Table 5: Investment, Cash flow and Monetary between these two firm types is inconclusive. Policy (Highly Leveraged Firms) Tobin’s Q ratio has a positive and statistically Independent Highly leveraged firms significant impact on investment of both highly Variables (Dependent Variable: Investment) leveraged and less leveraged firms. GDP growth 1 Monetary Policy Measures has a positive and statistically significant impact 2 3 (Narrative (WACR) Measure) Table 6: Investment, Cash flow and Monetary Constant 0.0292*** 0.0298*** 0.0290*** Policy (Less Leveraged Firms) (0.0049) (0.0049) (0.0049) Tobin’s Q 0.0211*** 0.0210*** 0.0209** Independent Less leveraged firms Variables (Dependent Variable: Investment) (0.0022) (0.0022) (0.0022) Cashflow -0.0169 -0.0455*** -0.1009** 1 Monetary Policy Measures (0.0121) (0.0158) (0.0399) 2 3 Cashflow*MPM(-1) 0.0695*** 0.0164** (Narrative (WACR) (0.0243) (0.0074) Measure) GDPgr(-1) 0.0023*** 0.0022*** 0.0023*** Constant 0.0192*** 0.0189*** 0.0184*** (0.0006) (0.0006) (0.0006) (0.0064) (0.0064) (0.0064) GFC_Dummy(-1) 0.0046 0.0039 0.0033 Tobin’s Q 0.0117*** 0.0113*** 0.0107*** (0.0076) (0.0076) (0.0076) (0.0024) (0.0024) (0.0024) NPA_Dummy(-1) -0.0724*** -0.0718*** -0.0730*** Cashflow 0.0127 -0.0123 -0.2511*** (0.0142) (0.0158) (0.0515) (0.0038) (0.0038) (0.0038) Cashflow*MPM(-1) 0.1238*** 0.0469*** Covid_Dummy(-1) -0.0429*** -0.0414*** -0.0405*** (0.0344) (0.0088) (0.0062) (0.0062) (0.0063) GDPgr(-1) 0.0010 0.0009 0.0012* Observations 7780 7780 7780 (0.0007) (0.0007) (0.0007) No. of Firms 389 389 389 GFC_Dummy(-1) 0.0069 0.0054 0.0033 (0.0099) (0.0099) (0.0090) Wald Test =1252.41 =1256.21 =1260.27 NPA_Dummy(-1) -0.0508*** -0.0490*** -0.0534*** (0.0051) (0.0051) (0.0051) = 0.00 = 0.00 = 0.00 Covid_Dummy(-1) -0.0168** -0.0135* -0.0068 F-test fixed effects F(388,7385) F(388, 7384) F(388, 7384) (0.0081) (0.0082) (0.0084) =1.84 =1.85 =1.83 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Observations 7800 7800 7800 Hausman =62.44 =88.52 =60.48 No. of Firms 390 390 390 specification test Wald Test =308.44 =320.43 =341.36 = 0.00 = 0.00 = 0.00 Notes: (i) ‘***’, ‘**’, and ‘*’ indicate statistical significance at 1 per cent, F-test fixed effects F(389,7404) F(389, 7403) F(389, 7403) 5 per cent and 10 per cent, respectively; (ii) Figures in parentheses are =1.22 =1.19 =1.22 standard errors; (iii) Estimation is by instrumental variable method where Prob> F=0.002 Prob> F=0.006 Prob> F=0.003 a lag of Tobin’s Q, cash flow term, lag of GDPgr, crises dummies are used as Hausman =108.66 =104.20 =110.72 instruments; and (iv) F-test is test of significance of fixed effects. specification test Source: Authors’ calculations. Notes: (i) ‘***’, ‘**’, and ‘*’ indicate statistical significance at 1 per cent, 5 per cent and 10 per cent, respectively; (ii) Figures in parentheses are 6 Highly leveraged firms have also been defined based on the mean standard errors; (iii) Estimation is by instrumental variable method where leverage ratio being greater than the 75th percentile and the rest being a lag of Tobin’s Q, cash flow term, lag of GDPgr, crises dummies are used as considered as less leveraged. The results were inconclusive and are instruments; and (iv) F-test is test of significance of fixed effects. provided in the annex tables 3(a) and 3(b). Source: Authors’ calculations. 80 RBI Bulletin June 2025Balance Sheet Channel of Monetary Policy Transmission: ARTICLE Insights from Indian Manufacturing Firms on investment only for highly leveraged firms References: while the NPA and Covid-19 dummies are negative Angelopoulou, E., and Gibson, H. D. (2009). and statistically significant for both types of firms. The Balance Sheet Channel of Monetary Policy This could be due to shrinkage in their cashflow, Transmission: Evidence from the United heightened risk of default during Covid-19 and Kingdom. Economica, 76(304), 675-703. limited access to credit during NPA crisis. Ashcraft, A. B., and Campello, M. (2007). VI. Conclusion Firm Balance Sheets and Monetary Policy Transmission. Journal of Monetary Economics, 54(6), The balance sheet channel of monetary policy 1515-1528. transmission emphasises how changes in interest rates affect a firm’s net worth, cashflow, and liquidity Aysun, U., and Hepp, R. (2013). Identifying the – factors that influence its borrowing capacity and Balance Sheet and the Lending Channels of Monetary Transmission: A Loan-Level Analysis. Journal of investment decisions. This study investigates the Banking and Finance, 37(8), 2812-2822. presence of balance sheet channel in India using firm level data on manufacturing firms over two decades Bernanke, B., and Gertler, M. (1995). Inside the (2003-2023). The analysis employs an instrumental Black Box: the Credit Channel of Monetary Policy variable fixed-effects panel regression model to Transmission. Journal of Economic Perspectives, 9(4), examine the relationship between investment, firm- 27-48. specific financial variables, real GDP growth, and Boschen, J. F., and Mills, L. O. (1991). The Effects monetary policy. The findings confirm the presence of Countercyclical Monetary Policy on Money and of the balance sheet channel in manufacturing firms. Interest Rates: An Evaluation of Evidence from FOMC Documents. Federal Reserve Bank of Philadelphia Furthermore, a detailed analysis, segmented Working Papers No. 91-20. by firm size and leverage, suggests that small firms, being more financially constrained, are more Boschen, J. F., and Mills, L. O. (1995). The Relation sensitive to internal funds under tight monetary between Narrative and Money Market Indicators of policy. 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Transmission Channel of Monetary Policy: The Cases of Germany and Spain. Bundesbank Document No. RBI (2011). Report of working group on operating 9713. procedure of monetary policy. Mishkin, F. (1995). Symposium on the Monetary RBI (2020). Report on Currency and Finance Transmission Mechanism. Journal of Economic 2020-21. Reserve Bank of India. perspectives, 9(4), 3-10. RBI (2022). Monetary Policy Report. September. Mohan, R. (2008). Monetary Policy Transmission Reserve Bank of India in India. BIS papers, 35. Sahoo, P., and Bishnoi, A. (2023). Drivers of Oliner Stephen, D., and Rudebusch, G. D. (1996). Corporate Investment in India: The Role of Firm- Is there a Broad Credit Channel for Monetary Policy? Federal Reserve Bank of San Francisco Economic Specific Factors and Macroeconomic Policy. Economic Review, 1, 3-13. Modelling, 125, 106330. 82 RBI Bulletin June 2025Balance Sheet Channel of Monetary Policy Transmission: ARTICLE Insights from Indian Manufacturing Firms Annex Table 1: Phases of Monetary Policy Tightening Sl. Period of Policy Measures Additional Measures Policy Rationale No. Tightening 1 October 2005 to Repo rate increased by 175 bps CRR increased over this period In the first sub-phase, repo rate was increased to stress September 2008 from 6.00 per cent to 7.75 per cent; from 5.00 per cent in October upon greater emphasis on price stability through 7 rate hikes of 25 bps each 2006 to 9.00 per cent in August measured but timely and even pre-emptive policy action in the first sub-phase; 2008. to anchor inflation expectations (RBI Annual Report, Repo rate increased by 125 bps 2005-06). from 7.75 per cent to 9.00 per In the second sub-phase, repo rate was increased to cent; 1 rate hike of 25 bps, 2 address the issue of volatile food and energy prices rate hikes of 50 bps each in the along with the need to managing inflation expectations. second phase. Wholesale price index (WPI) inflation had surged sharply from February 2008 (RBI Annual Report, 2008-09). 2 March 2010 to Repo rate increased by 375 bps CRR increased to 6.00 per cent Headline WPI inflation on a year-on-year basis March 2012 from 4.75 per cent to 8.50 per cent; in April 2010 from 5.00 per overshot the Reserve Bank’s baseline projection for 11 rate hikes of 25 bps each, 2 cent in April 2009. CRR stood at year-end inflation to reach 9.9 per cent (provisional) rate hikes of 50 bps each 6.00 per cent till October 2011. in February 2010. The rate of increase in the prices of Thereafter, CRR was reduced to non-food manufactured goods accelerated quite sharply. 4.75 per cent in March 2012. Furthermore, increasing capacity utilisation and rising commodity and energy prices were exerting pressure on the overall inflation. Taken together, these factors were seen to heighten the risks of supply-side pressures translating into a generalised inflationary process (RBI Annual Report, 2009-10). 3 September 2013 to Repo rate increased by 75 bps Reduced the marginal standing WPI inflation, which had eased in Q1 of 2013-14, December 2014 from 7.25 per cent to 8.00 per cent facility (MSF) rate by 75 bps has started rising again as the pass-through of fuel 3 rate hikes of 25 bps each from 10.25 per cent to 9.5 per price increases has been compounded by the sharp cent; and reduced the minimum depreciation of the rupee and rising international daily maintenance of the cash commodity prices (RBI Mid-Quarter Monetary Policy reserve ratio (CRR) from 99 Review, September 2013) per cent of the requirement to 95 per cent effective from the fortnight beginning September 21, 2013. 4 June 2018 to Repo rate increased by 50 bps The stance of the monetary Major risks to base inflation path viz., elevated price January 2019 from 6.00 per cent to 6.50 per cent policy was changed from neutral of the Indian crude basket, rise in household inflation 2 rate hikes of 25 bps each to calibrated tightening in expectations and possible second-round impact of October 2018. the staggered impact of housing rent allowance (HRA) revisions by various state governments were observed. Additionally, the announcement of hike in minimum support prices (MSPs) by the central government was expected to lead to a rise in inflation. (Monetary Policy Committee Resolution, June and August 2018) 5 May 2022 to Repo rate increased by 250 bps CRR increased to 4.5 per cent The MPC assessed that the ratcheting up of geopolitical December 2023 from 4.00 per cent to 6.50 per cent; from 4.00 per cent. tensions, the generalised hardening of global commodity 1 rate hike of 40 bps, 3 rate hikes prices, the likelihood of prolonged supply chain of 50 bps each, 1 rate hike of 35 disruptions, dislocations in trade and capital flows, bps, 1 rate hike of 25 bps divergent monetary policy responses and volatility in global financial markets posed sizeable upside risks to the inflation trajectory and downside risks to domestic growth (Monetary Policy Report, September 2022). Furthermore, the MPC posited that continued shocks to food inflation, elevated international crude oil prices and pending pass-through of input costs to selling prices were likely to sustain pressures on headline inflation (Monetary Policy Report, September 2022) Source: Authors’ illustration. RBI Bulletin June 2025 83ARTICLE Balance Sheet Channel of Monetary Policy Transmission: Insights from Indian Manufacturing Firms Annex Table 2: Investment, Cash flow and Monetary Policy a) Small Firms: b) Large Firms: Independent Small firms (Dependent Variable: Investment) Independent Large firms (Dependent Variable: Investment) Variables Variables 1 Monetary Policy Measures 1 Monetary Policy Measures 2 3 2 3 (Narrative (WACR) (Narrative (WACR) Measure) Measure) Constant 0.0192*** 0.0197*** 0.0192*** Constant 0.0394*** 0.0394*** 0.0395*** (0.0050) (0.0050) (0.0050) (0.0053) (0.0053) (0.0053) Tobin’s Q 0.0207*** 0.0202*** 0.0197*** Tobin’s Q 0.0114*** 0.0114*** 0.0114*** (0.0025) (0.0025) (0.0025) (0.0016) (0.0016) (0.0016) Cashflow 0.0070 -0.0214* -0.1967*** Cashflow -0.0716*** -0.0589** -0.0604 (0.0107) (0.0127) (0.0379) (0.0245) (0.0280) (0.0653) Cashflow*MPM(-1) 0.0969*** 0.0379*** Cashflow*MPM (-1) -0.0358 -0.0019 (0.0238) (0.0068) (0.0349) (0.0103) GDPgr(-1) 0.0017*** 0.0016*** 0.0018*** GDPgr(-1) 0.0016*** 0.0016*** 0.0016*** (0.0006) (0.0006) (0.0006) (0.0006) (0.0006) (0.0006) GFC_Dummy(-1) 0.0036 0.0027 0.0008 GFC_Dummy(-1) 0.0116 0.0120 0.0118 (0.0079) (0.0079) (0.0079) (0.0079) (0.0079) (0.0080) NPA_Dummy(-1) -0.0637*** -0.0625*** -0.0651*** NPA_Dummy(-1) -0.0608*** -0.0614*** -0.0607*** (0.0041) (0.0041) (0.0041) (0.0041) (0.0042) (0.0042) Covid_Dummy(-1) -0.0300*** -0.0279*** -0.0239*** Covid_Dummy(-1) -0.0378*** -0.0389*** -0.0383*** (0.0066) (0.0066) (0.0067) (0.0064) (0.0065) (0.0069) Observations 11680 11680 11680 Observations 3900 3900 3900 No. of Firms 584 584 584 No. of Firms 195 195 195 Wald Test =694.58 =708.12 = 731.11 Wald Test =1113.01 =1117.80 =1112.73 = 0.00 = 0.00 = 0.00 = 0.00 = 0.00 = 0.00 F-test fixed effects F(583,11090) F(583,11089) F(583,11089) F-test fixed effects F(194, 3699) F(194,3698) F(194,3698) =1.47 =1.47 =1.45 =2.05 =2.05 =2.05 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Hausman =171.73 =178.67 =164.64 Hausman =23.54 =23.53 =23.55 specification test specification test = 0.00 = 0.00 = 0.00 = 0.00 = 0.00 = 0.00 Notes: (i) ‘***’, ‘**’, and ‘*’ indicate statistical significance at 1 per cent, Notes: (i) ‘***’, ‘**’, and ‘*’ indicate statistical significance at 1 per cent, 5 per cent and 10 per cent, respectively; (ii) Figures in parentheses are 5 per cent and 10 per cent, respectively; (ii) Figures in parentheses are standard errors; (iii) Estimation is by instrumental variable method where standard errors; (iii) Estimation is by instrumental variable method where a lag of Tobin’s Q, cash flow term, lag of GDPgr, crises dummies are used as a lag of Tobin’s Q, cash flow term, lag of GDPgr, crises dummies are used as instruments; and (iv) F-test is test of significance of fixed effects. instruments; and (iv) F-test is test of significance of fixed effects. Source: Authors’ calculations. Source: Authors’ calculations. 84 RBI Bulletin June 2025Balance Sheet Channel of Monetary Policy Transmission: ARTICLE Insights from Indian Manufacturing Firms Annex Table 3: Investment, Cash flow and Monetary Policy a) Highly Leveraged Firms: b) Less Leveraged Firms: Independent Highly leveraged firms Independent Less leveraged firms Variables (Dependent Variable: Investment) Variables (Dependent Variable: Investment) 1 Monetary Policy Measures 1 Monetary Policy Measures 2 3 2 3 (Narrative (WACR) (Narrative (WACR) Measure) Measure) Constant 0.0365*** 0.0358*** 0.0364*** Constant 0.0209*** 0.0208*** 0.0202*** (0.0074) (0.0074) (0.0073) (0.0048) (0.0048) (0.0047) Tobin’s Q 0.0190*** 0.0191*** 0.0191*** Tobin’s Q 0.0145*** 0.0141*** 0.0136*** (0.0030) (0.0030) (0.0030) (0.0019) (0.0019) (0.0019) Cashflow 0.0470*** 0.0631*** 0.0572 Cashflow -0.0201* -0.0470*** -0.2828*** (0.0156) (0.0219) (0.0557) (0.0116) (0.0129) (0.0394) Cashflow*MPM(-1) -0.0324 -0.0019 Cashflow*MPM(-1) 0.1293*** 0.0479*** (0.0309) (0.0102) (0.0276) (0.0069) GDPgr(-1) 0.0024*** 0.0024*** 0.0024*** GDPgr(-1) 0.0017*** 0.0013** 0.0016*** (0.0009) (0.0009) (0.0009) (0.0006) (0.0006) (0.0006) GFC_Dummy(-1) -0.00005 0.0002 0.0001 GFC_Dummy(-1) 0.0079 0.0065 0.0042 (0.0115) (0.0115) (0.0115) (0.0074) (0.0074) (0.0074) NPA_Dummy(-1) -0.0811*** -0.0814*** -0.0810*** NPA_Dummy(-1) -0.0549*** -0.0533*** -0.0574*** (0.0058) (0.0058) (0.0058) (0.0038) (0.0038) (0.0038) Covid_Dummy(-1) -0.0539*** -0.0549*** -0.0543*** Covid_Dummy(-1) -0.0214*** -0.0185*** -0.0125** (0.0092) (0.0092) (0.0094) (0.0061) (0.0061) (0.0063) Observations 3900 3900 3900 Observations 11680 11680 11680 No. of Firms 195 195 195 No. of Firms 584 584 584 Wald Test =714.44 =718.01 =714.24 Wald Test =683.13 =702.90 =740.73 = = 0.00 = 0.00 = 0.00 0.00 = 0.00 = 0.00 F-test fixed effects F(194,3699) F(194, 3698) F(194, 3698) F-test fixed effects F(583,11090) F(583, 11089) F(583, 11089) =2.05 =2.02 =2.05 =1.33 =1.31 =1.32 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Prob> F=0.00 Hausman =31.88 =51.74 =32.54 Hausman =164.75 =154.89 =162.68 specification test specification test = 0.00 = 0.00 = 0.00 = 0.00 = 0.00 = 0.00 Notes: (i) ‘***’, ‘**’, and ‘*’ indicate statistical significance at 1 per cent, Notes: (i) ‘***’, ‘**’, and ‘*’ indicate statistical significance at 1 per cent, 5 per cent and 10 per cent, respectively; (ii) Figures in parentheses are 5 per cent and 10 per cent, respectively; (ii) Figures in parentheses are standard errors; (iii) Estimation is by instrumental variable method where standard errors; (iii) Estimation is by instrumental variable method where a lag of Tobin’s Q, cash flow term, lag of GDPgr, crises dummies are used as a lag of Tobin’s Q, cash flow term, lag of GDPgr, crises dummies are used as instruments; and (iv) F-test is test of significance of fixed effects. instruments; and (iv) F-test is test of significance of fixed effects. Source: Authors’ calculations. Source: Authors’ calculations. RBI Bulletin June 2025 85Drivers of CD Issuances: An Empirical Assessment ARTICLE Drivers of CD Issuances: CD is a negotiable, unsecured money market instrument issued by banks as a promissory note An Empirical Assessment against funds deposited for a maturity period up to one year.1 CDs being bearer documents are Anshul, Priyanka Priyadarshini readily negotiated and are attractive for both – the and Dipak R. Chaudhari* issuer banks and investors. Banks benefit from the specified maturity of deposit while investors In the recent period, banks have been relying are attracted to higher returns, short maturity and more on certificates of deposit (CDs) issuances, ready liquidity in the secondary market (Faniband, with credit growth outpacing the deposits growth. 2020). CDs act as an alternate source of short-term The CDs have been majorly issued by public sector funding to complement other traditional funding banks in the recent years while foreign banks have sources for commercial banks, giving them liquidity limited presence in the CD market. Post-covid, and solvency support. Banks can use CDs to comply mutual funds have increasingly invested in CDs with their reserve management, especially during to further reinforce their dominant share, with a concomitant decline in other investors such periods of liquidity tightness, such as the imposition as banks, financial institutions, and corporates. of incremental cash reserve ratio (CRR) in 2023 (RBI, This article, using autoregressive distributed lag 2023). Furthermore, CDs are considered as safe (ARDL) model, found that higher credit growth instruments; as a result, the returns on CDs are less along with tight system liquidity encourages CD attractive vis-à-vis corporate bonds (Puri, 2012). As issuances, while increase in market volatility CDs have fixed tenor, banks can better manage their decreases CD issuances. cash flows and plan for future banking activities. Introduction Banks find it attractive to raise funds through CDs at the beginning of interest rate upcycle, locking lower In the financial system money market is the interest rates for CDs up to a year as well as meeting fulcrum of monetary policy operations conducted by liquidity requirements. The CD issuances gained the central bank. It provides equilibrium mechanism momentum in post-covid period with the hike in for short term demand and supply of funds and enables price discovery. Money market instruments policy rates and shift in monetary policy stance at the like treasury bills and commercial papers enable time of robust credit growth (Chart 1). During Q4:2024- the government and corporates, respectively, to 25, CD issuances had reached an all-time high of ₹3.70 meet their short-term funding requirements, while lakh crore, in the backdrop of higher credit demand certificates of deposits (CDs) allow banks to access coupled with deficit liquidity2 and subdued deposits’ a cheaper source of funds than borrowing in the growth. Similarly, earlier in 2013, CD issuances had interbank market (Darpeix, 2022). increased to a 15-year high on the back of higher * Anshul and Dipak R. Chaudhari are from Financial Markets Operations Department. Priyanka Priyadarshini is from Issue Department, Bengaluru 1 CDs can also be issued by all India financial institutions (AIFIs) for 1 to RO. Authors are grateful to Shri G. Seshsayee, Vikram Rajput and Saurabh 3 years, are not considered in the article. Gupta for their comments on the earlier version of the article. The authors 2 Liquidity here is RBI’s net liquidity adjustment facility (LAF) position. If would like to thank the anonymous reviewer and the editorial team for their helpful comments and feedback. The views expressed in this article banks borrow more than lend back, it indicates liquidity deficit. are those of the authors and do not represent the views of the Reserve 3 https://www.business-standard.com/article/finance/cd-issuances-hit-15- Bank of India. year-high-106031001082_1.html RBI Bulletin June 2025 87ARTICLE Drivers of CD Issuances: An Empirical Assessment Chart 1: CDs Outstanding and as a percent of Term Deposits Source: RBI. credit growth3 while, deposit growth was lagging that supply of CDs is the response to the anticipated behind the credit growth. This raises an important strength of loan demand in the economy. During the question whether banks are substituting traditional global financial crisis (GFC), investors turned to CDs deposits with CDs in the scenario of deposit growth indicating that CDs are a safer investment option trailing credit growth. If so, what could be the reasons during crisis period (Aquilina et al., 2023). Prevailing as banks may sometimes have to pay higher interest liquidity conditions and investors’ appetite in the rates for CD issuance than traditional deposits, which market were found to be the major factors impacting may be another policy question to address. CD issuance in the European markets (Darpeix, 2022). Therefore, CD market could also provide a In terms of rates, CDs have to compete with barometer of the credit demand-supply dynamics other similar money market instruments such as of the economy. Against this backdrop, the article commercial papers (CPs), treasury bills (T-bills), examines market microstructure of CDs in India, and non-convertible debentures (NCDs). Therefore, including issuers profile and investor profile, and understanding their issuance, investor profile and assesses the potential drivers of the CD issuances the weighted average effective interest rate (WAEIR) using transaction level data. helps in gauging the market microstructure of CDs coupled with available system liquidity and funding The article is divided into six sections. Section requirements of the banking system. Further, CD II provides an overview of the CD market and cross- rates can provide insights into the future interest country experience. Section III analyses CD issuance, rate expectations by banks as well as the prevailing tenors and rates, investor profiles and credit ratings. liquidity conditions. There is a dearth of studies on Section IV discusses potential factors impacting the dynamics of CD market both globally as well as in CD issuance. Section V empirically examines the Indian context. An initial study by Cohan (1973) determinants of CD issuance volume using the on the determinants of CD market in the US shows autoregressive distributed lag (ARDL) approach and 88 RBI Bulletin June 2025 erorc hkal ₹ tnec reP 5.0 10 4.5 9 4.0 8 3.5 7 3.0 6 2.5 5 2.0 4 1.5 3 1.0 2 0.5 1 0.0 0 70-10-5002 72-50-5002 41-01-5002 30-30-6002 12-70-6002 80-21-6002 72-40-7002 41-90-7002 10-20-8002 02-60-8002 70-11-8002 72-30-9002 41-80-9002 10-10-0102 12-50-0102 80-01-0102 52-20-1102 51-70-1102 20-21-1102 02-40-2102 70-90-2102 52-10-3102 41-60-3102 10-11-3102 12-30-4102 80-80-4102 62-21-4102 51-50-5102 20-01-5102 91-20-6102 80-70-6102 52-11-6102 41-40-7102 10-90-7102 91-10-8102 80-60-8102 62-01-8102 51-30-9102 20-80-9102 02-21-9102 80-50-0202 52-90-0202 21-20-1202 20-70-1202 91-11-1202 80-40-2202 62-80-2202 31-10-3202 20-60-3202 02-01-3202 80-30-4202 62-70-4202 31-21-4202 CDs outstanding CDs as a percentage of Term Deposits (RHS)Drivers of CD Issuances: An Empirical Assessment ARTICLE market volatility (VIX), liquidity conditions, returns transmission in China; however, it also resulted in on equity, and banks credit to deposit ratio uses maturity mismatch, increasing leverage and decline as explanatory variables. Section VI concludes the in credit ratings of banks, thereby increasing financial article with overall findings. stability concerns. II. CD Market: Some Preliminaries The cross-country experience shows that banks or deposit taking institutions are the major II.1 Cross-Country Experience issuers of CDs while mutual funds, pension funds The development of CDs began in the US by New and insurance companies including cash rich non- York banks in mid-1960s as a result of rising credit financial corporations are the investors in CDs (FSB, demand and dampened deposit growth during the 2024). Generally, issuance of CD is concomitant with economic growth cycle (McKinney, 1967). In 1978, the increase in policy rates, as banks scout for money the US Federal Reserve introduced ‘money market market instruments during the policy tightening certificate of deposit’ to prevent rising interest rates phase. Although CD markets function well in normal from adversely affecting the flow of savings into times, they are susceptible to illiquidity in times of financial institutions (Winningham, 1979). This stress. Generally, CDs are held till maturity given was closely associated with the US interest rate the short-term nature of these instruments, which liberalisation process (Liu, 2018). In the US, CDs are results in very limited secondary market activity in considered as special type of deposit account with normal times. Further, the primary issuance market, a bank or financial institution with tenor up to five where most activity takes place, is intermediated by years and can be bought through federally insured a small number of core dealers that typically act as banks where the funds are insured up to USD a single point of market entry. The limited number 250,000.4 During the global financial crisis (GFC), of intermediaries means that they may not be able many American investors turned to CDs as it is a safer to respond to spikes in liquidity demand in times of investment in volatile market conditions.5 Globally, stress (FSB, 2024). CDs are rarely traded in the secondary markets and investors tend to hold them till maturity (Aquilina et Unlike other money market instruments, there is al., 2023). no definitive source of data that compiles and reports In the Euro area, banks account for around 70 global CD issuances. Countries have varying reporting per cent of outstanding CD issuance, with the French requirements and methodologies for tracking CD banks being most active. CDs are mainly issued in market, which makes it difficult to get a concise idea domestic currency; however, it can be issued in other about the CD market. A Report based on survey data, currencies in the US and UK market. In contrast to estimates global CD market size USD 1 trillion in 2023 the advanced countries, in China the CD market is and it is projected to reach USD 1.5 trillion in 2032.6 nascent and grew after the Chinese central bank Another report projected to reach CD market to USD liberalised interest rates in 2015. Liu (2018) found 2.3 trillion by 2033 from USD 1.5 trillion in 2024.7 that growth in the CD improved monetary policy Whatsoever the estimates are, it still reflects smaller 4 https://www.investor.gov/introduction-investing/investing-basics/ 6 https://dataintelo.com/report/global-certificate-of-deposit-market investment-products/certificates-deposit-cds 7 https://www.verifiedmarketreports.com/product/certificate-of-deposit- 5 https://www.sec.gov/reportspubs/investor-publications/investorpubscertific market RBI Bulletin June 2025 89ARTICLE Drivers of CD Issuances: An Empirical Assessment share in the outstanding USD 128 trillion global debt up the excess liquidity emanating from withdrawal market as on August 2020, estimated by international of ₹2000 denominated currency, CD issuances capital market association (ICMA). Lack of public data increased. Further, quarter-end effects of advance tax across CD markets presents a challenge when it comes payments and goods and services tax (GST) outflows, to monitoring these markets, and thus may discourage coupled with lesser government spending leading to broader investor participation (FSB, 2024). liquidity tightening, result in higher CD issuance by banks. Along with these factors, slowdown in CASA II.2 Indian Experience deposit growth for banks as bank depositors shift to In India, although CDs are mentioned in the alternate assets, has resulted in increased reliance Reserve Bank of India Act 1934, due to the lack of an on CDs by banks.8 active secondary market, administered interest rates It is found that banking liquidity and CD and possible danger of fictious transactions, CDs issuance were negatively correlated (-0.62) during were not issued until 1989. The Vaghul Committee the study period. Therefore, CD issuances spike in on money market reforms recommended issuances March as Banks use CDs as a way to manage liquidity of CDs in 1987 (RBI, 1987). Major milestones in the needs arising as a result of tight liquidity conditions development of CD market in India is given in Annex during the year-end. Since April 2022, CD issuance table A2. Since their inception, CDs are issued by banks for up to 1 year, while the non-bank financial has been increasing and reached ₹1.17 lakh crore in March 2025. Outstanding CD issuances increased institutions can issue CDs for a duration of 1 to 3 years. Details about the CD product, eligible issuers to all time high of ₹11.75 lakh crore during 2024-25 (Chart 2a and b). and investors along with regulatory requirement are given in Annex Table A1. III. CD Issuers and Investors Typically, CD issuances go up when there is a Among the CD issuers, public sector banks (PSBs) boom in credit demand with lower growth in bank and private sector banks (PVBs) are the dominant deposits. During Covid, the CD market had become players, while CD issuance by foreign banks (FBs) dormant due to limited requirement for funds by and small finance banks (SFBs) is muted and banks and surplus liquidity conditions. Recently, intermittent. The share of PVBs has declined from 85 there has been an increase in CD issuances and the per cent in January 2022 to 30 per cent in December CD rates i.e., WAEIR. CD issuance, which was muted 2024, concomitantly the share of PSBs has increased during the Covid period (April 2020-November 2021), from 6 per cent to 69 per cent during the period. jumped to ₹ 68,973 crore in the fortnight ending This contrasts with the general belief that issuance March 22, 2024, from a low of ₹386 crore on May of CDs is dominated by PVBs to complement their 8, 2020 (Chart 2a). As Covid-related uncertainties current and savings account (CASA) deposits waned, hike in policy rates and shift in monetary (Chart 3). policy stance at the time of robust credit growth Though CDs can be issued for a period up to led to the rise in outstanding CDs. On the back of Reserve Bank’s introduction of 10 per cent 8 https://economictimes.indiatimes.com/industry/banking/finance/banking/ more-savers-ditch-bank-deposits-to-flirt-with-equity/articleshow/107923540. incremental CRR (I-CRR) from May 19, 2023, to mop cms 90 RBI Bulletin June 2025Drivers of CD Issuances: An Empirical Assessment ARTICLE Chart 2: Trends in CD Issuance a. Trends in CD Issuance and Outstanding b. CD Issuance Seasonality Sources: F-Trac and authors’ calculations. 365 days, the average tenor depends on the liquidity 2021, which coincides around the start and peak of needs of banks and expectations of the future interest rate easing cycle; and thereafter, the average interest rates. During interest rate hike cycle, banks tenor has decreased to 128 days in May 2022 when benefit by locking longer tenor CDs, while in easing Reserve Bank raised policy rate. In September 2024 cycle banks usually have no benefit in issuing longer the average tenor of CD issuances was lower at 146 tenor CDs unless there is high credit demand. The days indicating that banks were raising CDs for average tenor of CDs witnessed increasing trend short-term funding and expecting decline in interest from 95 days in June 2019 to 296 days in October rates (Chart 4a). RBI Bulletin June 2025 91 erorc hkal ₹ Amount Issued Outstanding (RHS) erorc hkal ₹ 1.20 6 1.00 5 0.80 4 0.60 3 0.40 2 0.20 1 0.00 0 8102-naJ 8102-rpA 8102-luJ 8102-tcO 9102-naJ 9102-rpA 9102-luJ 9102-tcO 0202-naJ 0202-rpA 0202-luJ 0202-tcO 1202-naJ 1202-rpA 1202-luJ 1202-tcO 2202-naJ 2202-rpA 2202-luJ 2202-tcO 3202-naJ 3202-rpA 3202-luJ 3202-tcO 4202-naJ 4202-rpA 4202-luJ 4202-tcO 5202-naJ 5202-rpA erorc ₹ 200000 180000 160000 140000 120000 100000 80000 60000 40000 20000 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2019 2020 2021 2022 2023 2024 2025 Chart 3: Share of CD Issuers Sources: F-Trac and Authors’ calculations. tnec reP 100 90 80 70 60 50 40 30 20 10 0 91-nuJ 91-peS 91-ceD 02-raM 02-nuJ 02-peS 02-ceD 12-raM 12-nuJ 12-peS 12-ceD 22-raM 22-nuJ 22-peS 22-ceD 32-raM 32-nuJ 32-peS 32-ceD 42-raM 42-nuJ 42-peS 42-ceD 52-raM Foreign Banks PVBs PSBs SFBsARTICLE Drivers of CD Issuances: An Empirical Assessment Chart 4: Maturity Profile of CD Issuance a. Average Tenor of CD Issuances b. Tenor Wise Share in Issuance Sources: F-Trac and Authors’ calculations. Amongst the various tenors, the share of CDs 155 days, indicating use of CDs mostly as instruments issued up to 91 days and between 180-365 days for their short-term funding needs (Charts 5). dominate the CD issuance, thus making CDs either The CD WAEIR increased steeply after February an instrument of short-term liquidity management 2022 alongside increase in policy rate, signalling or an instrument to lock short-term rates for longer deficit liquidity conditions. A comparison of WAEIR period (up to 1 year), which may be beneficial for of different categories of issuing banks shows that banks during the interest rate upcycle. This is on an average, PSBs had lower WAEIR than others. further corroborated by the fact that the share of CDs However, this spread in the WAEIR among the banks between 180-365 days has declined since April 2023, when RBI paused interest rate hikes. Since then, the share of CDs issued up to 91 days dominate the CDs issuance, indicating the use of CDs as instrument to meet short-term liquidity needs (Chart 4b). As CDs are unsecured debt instruments, the average tenor of the CD issuance and WAEIR provide insights into short-term funding dynamics among the four broad categories of commercial banks. The average tenor for PVBs is higher at 222 days, vis-à- vis both PSBs as well as SFBs at 155 and 215 days, respectively. Longer tenor of CDs issuance by PVBs imply that they raise funds to not just meet the short-term funding requirements but also for locking in lower interest rates. PSBs have an average tenor of 92 RBI Bulletin June 2025 syaD tnec reP 350 300 250 200 150 100 50 0 91-nuJ 91-peS 91-ceD 02-raM 02-nuJ 02-peS 02-ceD 12-raM 12-nuJ 12-peS 12-ceD 22-raM 22-nuJ 22-peS 22-ceD 32-raM 32-nuJ 32-peS 32-ceD 42-raM 42-nuJ 42-peS 42-ceD 52-raM 100 90 80 70 60 50 40 30 20 10 0 91-nuJ 91-guA 91-tcO 91-ceD 02-beF 02-rpA 02-nuJ 02-guA 02-tcO 02-ceD 12-beF 12-rpA 12-nuJ 12-guA 12-tcO 12-ceD 22-beF 22-rpA 22-nuJ 22-guA 22-tcO 22-ceD 32-beF 32-rpA 32-nuJ 32-guA 32-tcO 32-ceD 42-beF 42-rpA 42-nuJ 42-guA 42-tcO 42-ceD 52-beF Upto 91-days 92 - 180 days 181 - 365 days Chart 5: Issuer-wise Tenor Foreign Banks PVBs PSBs SFBs Sources: F-Trac and Authors’ calculations. syaD 91-nuJ 91-guA 91-tcO 91-ceD 02-beF 02-rpA 02-nuJ 02-guA 02-tcO 02-ceD 12-beF 12-rpA 12-nuJ 12-guA 12-tcO 12-ceD 22-beF 22-rpA 22-nuJ 22-guA 22-tcO 22-ceD 32-beF 32-rpA 32-nuJ 32-guA 32-tcO 32-ceD 42-beF 42-rpA 42-nuJ 42-guA 42-tcO 42-ceD 52-beF 400 350 300 250 200 150 100 50 0Drivers of CD Issuances: An Empirical Assessment ARTICLE narrowed since July 2022. For SFBs, the WAEIR is usually higher than others, reflecting higher risk premia (Chart 6). III.1 Who are the CD Investors? Globally, it has been found that money market mutual funds are the major investors in the CD market (Aquilina et al., 2023). In the Indian context also, mutual funds remain the dominant investors, with an average share of 85 per cent since November 2021. Among other investors, PVBs and PSBs have an average share of 11 and 6 per cent, respectively, while corporates have a marginal share (Chart 7). As debt mutual funds are mandated to invest in shorter duration instruments they are always III.2 Credit Rating Across CD Issuance on the lookout for investment opportunities in the CD market. Thus, an increase in assets under The credit risk of the underlying assets held management (AUM) of debt MFs further might by the issuing banks is reflected in its credit rating. have boosted the MFs’ share in the total investment If a bank is less creditworthy, it has to pay higher in CDs during the post-covid period. The AUM of rate for CD issuance. This is in line with global debt MFs registered a compounded annual growth experience (Johnson et al. 2008). However, CD rate of 12.2 per cent from March 2022 to September market is considered to be less efficient and as CD 2022 (Gupta et al., 2022) [Chart 8]. rates are negotiated bilaterally, market stakeholders Chart 6: Issuer-wise WAEIR Note: The breaks in between are due to no CD issuance in the issuer category for that time period. Sources: F-Trac and Authors’ calculations. RBI Bulletin June 2025 93 tnec reP 9.00 8.00 7.00 6.00 5.00 4.00 3.00 2.00 1.00 0.00 91-nuJ 91-peS 91-ceD 02-raM 02-nuJ 02-peS 02-ceD 12-raM 12-nuJ 12-peS 12-ceD 22-raM 22-nuJ 22-peS 22-ceD 32-raM 32-nuJ 32-peS 32-ceD 42-raM 42-nuJ 42-peS 42-ceD 52-raM Chart 7: Share of CD Investors Sources: F-Trac and Authors’ calculations. Foreign Banks PSBs PVBs SFBs tnec reP 100 90 80 70 60 50 40 30 20 10 0 91-nuJ 91-guA 91-tcO 91-ceD 02-beF 02-rpA 02-nuJ 02-guA 02-tcO 02-ceD 12-beF 12-rpA 12-nuJ 12-guA 12-tcO 12-ceD 22-beF 22-rpA 22-nuJ 22-guA 22-tcO 22-ceD 32-beF 32-rpA 32-nuJ 32-guA 32-tcO 32-ceD 42-beF 42-rpA 42-nuJ 42-guA 42-tcO 42-ceD 52-beF Mutual Funds PVBs Financial Institutions Corporates PSBs Chart 8: AUM of Debt Mutual Funds Sources: FIMMDA and Authors’ calculations. erorc ₹ 1,80,000 1,60,000 1,53,800 1,40,000 1,20,000 1,00,000 80,000 60,000 40,000 20,000 0 91-rpA 91-luJ 91-tcO 02-naJ 02-rpA 02-luJ 02-tcO 12-naJ 12-rpA 12-luJ 12-tcO 22-naJ 22-rpA 22-luJ 22-tcO 32-naJ 32-rpA 32-luJ 32-tcO 42-naJARTICLE Drivers of CD Issuances: An Empirical Assessment and bank specific characteristics can influence CD repo rate till the first hike on May 4, 2022; thereafter, rates. Almost all the CD issuances are A1+ rated remained above the repo rate, which points to while among the rating agencies, CRISIL dominates tight liquidity conditions in accordance with RBI’s with 55 per cent share (Chart 9). withdrawal of accommodation stance. Consequent to the rate hike, liquidity conditions tightened IV. CD Issuance in India: Trends and Correlates whereby liquidity absorption declined from average Allen (1971) observed that CD issuance is of ₹6.5 lakh crore in January 2022 to ₹4,547 crore in sensitive to interest rates of other money market February 2023, further to an injection of ₹1.17 lakh instruments, thus CDs’ outstanding volume is crore in December 2023 (Chart 10). dependent on the ability of CDs to compete with other money market instruments and banks’ funding Macroeconomic shocks can affect banks’ risk requirements. A positive correlation between CD premia on CDs i.e., spread between the WAEIR of issuance and WAEIR with the weighted average call CDs and the risk free rate (Kishan and Opiela, 2015) rate (WACR) is found in the Indian CD market. The as it can be seen that during the US regional banking WAEIR of CD issuance follows the path of policy rate crisis in March 2023, The CD WAEIR spiked. In India, cycle. For instance, it increased consistently between the spread between WAEIR of CDs and repo rate has the fortnight ending May 6, 2022 to December 31, decreased since the pause in policy rate hikes in April 2023, from 4.2 per cent to 7.5 per cent, in line with 2023. The narrowing of spread between CD issuances the increase in policy repo rate. of various tenors implies that the compensation for The 3-month CDs traded marginally above the term premia is declining in the CD market, following repo rate before the onset of COVID pandemic, a pattern similar to the G-sec market. The spread of however, it was below the repo rate during the 3-month CDs over 3-month T-Bill has moved in sync surplus liquidity phase and mostly traded around the with the liquidity conditions, remaining broadly Chart 9: CD Issuance - Credit Ratings Chart 10: Liquidity and Key Rates 13% 12% 51% 23% CRISIL A1+ ICRA A1+ IND A1+ CARE A1+ Note: CRISIL (Credit Rating Information Services of India Limited), ICRA (Investment Information and Credit Rating Agency of India Limited), CARE (Credit Analysis and Research Limited) and IND (India Ratings) are rating agencies, while A1+ is a rating indicates very high degree of safety for timely repayment. Sources: F-Trac, RBI and Authors’ calculations. Note: liquidity is Repo + MSF – Sources: F-Trac and Authors’ calculations. SDF - Reverse Repo. 94 RBI Bulletin June 2025 tnec reP erorc hkal ₹ 8.5 11.0 7.5 9.5 6.5 8.0 6.5 5.5 5.0 4.5 3.5 3.5 2.0 2.5 0.5 1.5 -1.0 0.5 -2.5 -0.5 -4.0 91-nuJ 91-peS 91-ceD 02-raM 02-nuJ 02-peS 02-ceD 12-raM 12-nuJ 12-peS 12-ceD 22-raM 22-nuJ 22-peS 22-ceD 32-raM 32-nuJ 32-peS 32-ceD 42-raM Liquidity (+ Surplus) RHS WACR Repo rate WAEIRDrivers of CD Issuances: An Empirical Assessment ARTICLE range bound during the period. The spread was less than 40 basis points (bps) in December 2021 and increased thereafter to 100 bps around March 2023. The range between the minimum and maximum rate of CD issuance on fortnightly basis reflects the heterogeneity among the issuers as well as future interest rate expectations and liquidity needs of market participants (Chart 11). CDs can also act as a substitute to traditional deposits, especially during stressed liquidity conditions (Cohan, 1973). CDs and shorter tenor deposits are strong substitutes for one another and banks tend to prefer CDs over deposits as the latter are more sensitive to rates than the former (Humphrey 1979). A positive relationship between incremental of moderate increase in deposits rates during the credit deposit (ICD) ratio and CD issuances during the period. The weighted average term deposit rate fortnight may exist as higher credit offtake compared (WATDR) of PSBs, PVBs and Foreign banks on to deposits could lead to higher issuance of CDs to outstanding deposits increased by 188 bps, 177 bps meet the liquidity requirement of banks (Chart 12). and 295 bps, respectively, during April 2022 to May 2024 (RBI, 2024) [Chart 13]. Further, robust CD issuances during Q4:2023- 24 may be due to sustained increase in credit During highly uncertain market conditions, it is growth along with trailed deposit growth because expected that CD issuance could be less due to muted Chart 11: WAEIR and Range Sources: F-Trac, RBI and Authors’ calculations. RBI Bulletin June 2025 95 tnec reP tnec reP 9 3.0 8 2.5 7 2.0 6 1.5 5 1.0 4 0.5 3 0.0 2 1 -0.5 0 -1.0 8102-raM 8102-nuJ 8102-peS 8102-ceD 9102-raM 9102-nuJ 9102-peS 9102-ceD 0202-raM 0202-nuJ 0202-peS 0202-ceD 1202-raM 1202-nuJ 1202-peS 1202-ceD 2202-raM 2202-nuJ 2202-peS 2202-ceD 3202-raM 3202-nuJ 3202-peS 3202-ceD 4202-raM 4202-nuJ 4202-peS 4202-ceD 5202-raM Chart 13: Weighted Average Term Deposit Rate Spread (3M T-Bill) RHS WAEIR Range Source: RBI. tnec reP 8 7 6 5 4 3 2 1 0 02-guA 02-tcO 02-ceD 12-beF 12-rpA 12-nuJ 12-guA 12-tcO 12-ceD 22-beF 22-rpA 22-nuJ 22-guA 22-tcO 22-ceD 32-beF 32-rpA 32-nuJ 32-guA 32-tcO 32-ceD 42-beF 42-rpA Chart 12: CD Issuances and Incremental Credit Deposit Ratio Sources: RBI, Authors’ calculations, and Bloomberg. PSBs PVBs Foreign Banks tnec reP erorc hkal ₹ 400 0.8 300 0.7 200 0.6 100 0.5 0 0.4 -100 0.3 -200 0.2 -300 -400 0.1 -500 0.0 Incremental Credit Deposit Ratio CD issuances (RHS) 81-luJ 81-tcO 91-naJ 91-rpA 91-luJ 91-tcO 02-naJ 02-rpA 02-luJ 02-tcO 12-naJ 12-rpA 12-luJ 12-tcO 22-naJ 22-rpA 22-luJ 22-tcO 32-naJ 32-rpA 32-luJ 32-tcO 42-naJ 42-rpAARTICLE Drivers of CD Issuances: An Empirical Assessment credit demand by industry. This limits the need volatility index (VIX) which measures the uncertainty for banks to issue CDs. Further, during heightened in the markets, Sensx_return as a proxy of equity volatility period, some investors may shift towards returns, CD_RATE_CH as a measure of variation safer assets, such as T-bills. The India volatility index in CD rate (WAEIR), ICD_ratio for how much new (VIX), being an indicator of uncertainty in the market, deposits are being utilised for lending, LAF_CH as a is a market fear gauge, and has negative correlation measure of variation in liquidity over a fortnight and with CD issuance (Chart 14). OIS_CH as a measure of variation in OIS rates. The variable description and descriptive statistics are V. Empirical Analysis presented in Annex Tables A3 and A5, respectively. CD issuances tend to be influenced by a number CD rate change (CD_RATE_CH) indicates of factors as discussed above (section IV). In order fortnightly variation in the rates (WAIER) at which to further understand the contribution of various CDs are issued. The relationship of WAIER with CD factors towards growth/decline in CD issuances issuances depends on the RBI policy cycle, credit over time, a regression model is estimated using growth and availability of other short term deposit fortnightly data (July 2018-November 2023). instruments among others. When CD issuance act To understand the factors driving CD issuance, as a substitute to the deposits (short term up to 1 the following equation is estimated: year) especially when credit demand is soaring, and deposit growth is lagging behind an increase in CD rates (WAIER) should lead to a decline in CD In the estimated model, dependent variable CD t issuances and vice versa. Incremental Credit Deposit depicts fortnightly CD issuances which is represented ratio (ICD_ratio) indicates the fortnightly change in by the natural logarithm of seasonally adjusted CD credit deposit ratio; therefore, a positive relationship issuances during a fortnight. is the error correction may exist as higher credit offtake relative to deposits term. The independent variable X includes market ψ t could lead to higher issuance of CDs to meet the increasing reserve requirements. Chart 14: CD Issuance and VIX Movements The liquidity adjustment facility change (LAF_ CH) indicates the variation in banking liquidity during the fortnight vis-à-vis previous fortnight. While a positive value implies increase in surplus liquidity, a negative value indicates decline in system liquidity during the fortnight. A period of liquidity shortage encourages banks to explore alternative avenues to raise the funds. Thus, CD issuances tend to increase with the decline in liquidity and decrease with the increase in surplus liquidity. It is therefore expected that CD issuances, in the long run, are negatively related to system liquidity measure, LAF_CH variable in the model. A dummy for liquidity tightness Sources: RBI and Bloomberg. has also been taken, where 1 indicates period 96 RBI Bulletin June 2025 erorc ₹ tnec reP 90000 80 80000 70 70000 60 60000 50 50000 40 40000 30 30000 20 20000 10000 10 0 0 CD Issuance (Volume) VIX (RHS) 81-luJ 81-tcO 91-naJ 91-rpA 91-luJ 91-tcO 02-naJ 02-rpA 02-luJ 02-tcO 12-naJ 12-rpA 12-luJ 12-tcO 22-naJ 22-rpA 22-luJ 22-tcO 32-naJ 32-rpA 32-luJ 32-tcO 42-naJ 42-rpA 42-luJDrivers of CD Issuances: An Empirical Assessment ARTICLE when RBI pivoted monetary policy stance towards (ECT) associated with the ARDL model reflects the withdrawal of accommodation post pandemic, speed of adjustment to long-run path following a otherwise zero. short run deviation. If the F-statistics (Wald test) establishes that there is a single long run relationship Interest rate expectations impact money market and the sample data size is small (n≤ 30) or finite, instruments’ behaviour. For the CD issuance, the ARDL error correction representation becomes increase in market expectation of interest rates could relatively more efficient. However, limitation of lead to increase in CD issuance and vice versa. The the ARDL approach is that when there are multiple variable overnight indexed swap (OIS_CH), in our long-run relationships, the model cannot be model, indicates the variation in OIS rates over a applied. fortnight. While a positive value indicates increase in As per the estimation results in the short run, OIS rate, a negative value implies a decline in the rate CD issuances are negatively impacted by increase in over the fortnight. The increase in OIS rates reflects surplus liquidity. On the other hand, withdrawal of expectations of higher interest rates and lower credit accommodation (DUMMY) impacted CD issuances growth, could lead to decline in CD issuances. positively, which is indicative of the fact that In time series econometrics, divergence from CD issuances increased after the Reserve Bank mean over time implies non-stationarity and it shifted its monetary policy stance to withdrawal is considered as a violation of assumption of the of accommodation. Among the variables that have classical linear regression estimation as it may lead long run impact over CD issuances include market to misleading or spurious regression. The Augmented volatility measure (VIX), incremental CD ratio, LAF Dicky Fuller (ADF) tests for stationarity of selected variation over the fortnight and fortnightly variation variables depict a mix of I(0) and I(1). In order to in OIS rates (Table 1). measure the predictive power of the independent variables, a Granger causality test (Granger, 1969) Table 1: ARDL Model Estimation Results is applied (Annex Table A4). The results reconfirm Variable Coefficient p-value that liquidity and higher credit growth relative to Long-Run Error Correction Term -0.499*** 0.000 deposits growth can predict the future volume of CD constant 9.446*** 0.000 issuances (Annex Table A6). Further as the F-statistic VIX -0.042* 0.081 establishes a single long run relationship, the ARDL Sensx_return 0.0004 0.994 CD_RATE_CH -0.009 0.536 technique is appropriate for estimation (Annex ICD_ratio 0.005*** 0.005 Table A7). LAF_CH -0.001** 0.040 OIS_CH -0.144*** 0.006 The cointegration technique is a powerful way Short-Run of detecting the presence of steady state equilibrium D(LAF_CH) -0.0014*** 0.000 DUMMY 0.442** 0.002 between non-stationary variables. As per Pesaran et Adj-R2 0.52 al. (2001), the autoregressive distributed lag (ARDL) D-W statistics 2.06 cointegration technique can be used in determining LM-p-value 0.28 the long run relationship between series with ARCH-p-value 0.26 different order of integration like, I(0) and I(1) but Note: ***, **, * denote significance level of 1 per cent, 5 per cent, and 10 per cent, respectively. not I(2). The coefficient of error correction term Source: Authors’ estimate. RBI Bulletin June 2025 97ARTICLE Drivers of CD Issuances: An Empirical Assessment The estimation results confirm that liquidity References situation, interest rate expectation, and volatility (VIX) Allen, J. B. (1971). Factors Determining the Volume determine CD issuance in the long run. A positive of Certificates of Deposits Outstanding: A Case Study ICD coefficient indicates increase in credit with lower of the Drain off in 1969. American Economist, 15(2), deposits mobilisation prompts CD issuances. In the 32–37. short run also, liquidity is found to be the major driver of CD issuances. The findings reconfirm that CD Aquilina, M., Schrimpf, A., and Todorov, K. (2023). issuances are mainly driven by liquidity management CP and CDs Markets: A Primer. BIS Quarterly Review, September 2023, 63–76. and short-term funding requirements. Cohan, B. S. (1973). The Determinants of Supply VI. Conclusion and Demand for Certificates of Deposit. Journal of CD is a money market instrument issued by Money, Credit and Banking, 5(1), 100–112. banks to meet their short-term funding requirement. Darpeix, P.-E. (2022). The Market for Short-Term Debt However, in the recent period it was in focus due Securities in Europe: What We Know and What We to higher issuances accompanied by robust credit Do Not Know. SSRN Electronic Journal, 21. growth and a lagging deposit growth. It has been observed that during the covid induced liquidity Faniband, M. (2020). The behaviour of trading surplus phase private banks were front runner in volume: Evidence from money market instruments. issuing the CDs; however, after February 2022 PSBs Indian Journal of Finance. dominates the share in CD issuance. Foreign banks FSB. (2024). FSB examines vulnerabilities in short- and relatively new SFBs have limited presence in term funding markets. https://www.fsb.org/2024/05/ the CD market. CD rates are relatively higher for fsb-examines-vulnerabilities-in-short-term-funding- SFBs while PSBs were able to raise CDs at relatively markets. lower rates. Mutual funds continued to remain the Granger, C. W. J. (1969). Investigating Causal Relations major investor in CDs as higher retail participation by Econometric Models and Cross-spectral Methods. in equity market led to higher asset allocation by Econometrica. 37 (3): 424–438. mutual funds. Gupta, M., Kumar S., Seet, S., & Borad A. (2022). The empirical results depict a positive impact of Market Returns and Flows to Debt Mutual Funds. RBI withdrawal of accommodation and incremental credit Bulletin, October. deposit ratio over the volume of CD issuances during Humphrey, D. B. (1979). Large Bank Intra-Deposit the study period. This indicates banks’ inclination Maturity Composition. Journal of Banking & Finance, towards increased usage of CDs, amidst tightened 3(1), 43–66. liquidity conditions coupled with credit growth Johnson, R. M., Lange, D. R., & Newman, J. A. outpacing deposits growth. Although, CD market is (2008). The market for retail certificates of deposit: largely a bilaterally negotiated market, CD issuances Explaining interest rates. Financial Services Review. is found to be sensitive to current and expected rate of interest. Furthermore, during uncertainty banks Kishan, R. P., & Opiela, T. P. (2015). Macroeconomic tend to reduce CD issuances. Shocks and Discipline in the Market for Large 98 RBI Bulletin June 2025Drivers of CD Issuances: An Empirical Assessment ARTICLE Certificates of Deposit. Banks and Bank Systems, (10, Journal of Marketing, Financial Services & Iss.4),8-14. Management Research, 1(9), 3622. www. indianresearchjournals.com Liu, K. (2018). Why Does the Negotiable Certificate of Deposit Matter for Chinese Banking? Economic RBI. (1987). Report of the Working Group on the Affairs. Money Market. https://rbidocs.rbi.org.in/rdocs// McKinney, G. W. (1967). New Sources of Bank Funds: PublicationReport/Pdfs/CR637_19872E959BF4B5454 Certificates of Deposit and Debt Securities. Law and 9D981C7FF70F0F5E7D8.PDF Contemporary Problems, 32(1), 71. RBI. (2023). Reserve Bank of India Bulletin. September Pesaran, M. H., Y. Shin, and R. P. Smith (1999), RBI. (2024). Monetary policy report, April. “Pooled Mean Group Estimation of Dynamic Heterogeneous Panels”, Journal of the American Winningham, S. (1979). The Effect of Money Statistical Association, Vol. 94, No. 446, pp. 621-634. Market Certificates of Deposit on the Monetary Puri, N. (2012). Role of Money Market in Context Aggregates and Their Components. Economic Review, to Growth of Indian Economy. IRJC International 20–31. RBI Bulletin June 2025 99ARTICLE Drivers of CD Issuances: An Empirical Assessment Annex Table A1: Certificates of Deposit: Current Specification Product Negotiable, unsecured money market instrument issued as a promissory note against funds deposited. A CD shall be issued in dematerialised form through any of the depositories approved by and registered with SEBI. Issuance Form A CD can be issued at a discount to face value. CDs can be issued in fixed or floating rate basis. Denomination Minimum of ₹5 lakh and multiples of ₹5 lakh thereafter. CDs can be treaded over the counter (OTC), electronic trading platform (ETP) or recognised stock exchanges approved by RBI. Settlement will be T+0 or T+1. Secondary market CDs shall be settled on delivery versus payment (DvP) basis through clearing corporation of any recognised stock exchange or any other platform approved by RBI. Minimum: 7 Days and Maximum: 1 Year from the date of issuance. Maturity Settlement on a T+1 basis. Loan against CDs Loan against CDs not allowed, unless specified by RBI. CDs buyback allowed after 7 days of the issuance. The buyback should be offered to all investors and investors shall have Buyback of CDs option to accept or reject the buyback offer. Regulators RBI and FIMMDA (Market Self-Regulatory Organisation - SRO). Scheduled commercial banks, Regional Rural Banks, Small Finance Banks and all India financial institutions (AIFIs). For AIFIs Eligible Issuers tenor should not be less than 1 year and not exceeding 3 years. CD details shall be reported by the issuer to trade repository, i.e., Financial Market Trade Reporting and Confirmation Reporting Platform (F-TRAC) of the CCIL. Secondary market transactions shall be reported on the F-TRAC platform by each counterparty to the transaction. Reserve Requirement Banks are required to maintain cash reserve ratio (CRR) and statutory liquidity ratio (SLR), on the issue price of the CDs. Eligible Investors All persons’ resident in India. Sources: RBI and FIMMDA. 100 RBI Bulletin June 2025Drivers of CD Issuances: An Empirical Assessment ARTICLE Table A2: Development of Certificates of Deposit Market in India Year Major Development 1934 RBI Act 1934 mentions “certificate of Deposit” as a money market instrument 1985 First comprehensive recommendations on development of money market made by Chakrvarty Committee 1987 RBI constituted a working group on the money market (Chairman: Shri N. Vaghul), recommended the feasibility of introducing CD. CDs introduced in India, can be issued by scheduled commercial banks (excluding RRBs and local area banks) Banks can account the issue price under the head of “CD issued” and show them under deposits. CD amount should be included under 1989 the section 42 returns. Minimum CD issuance size was ₹1 crore. Reduced minimum issuance size to ₹1 lakh from ₹1 crore. 2002 To impart transparency and encourage secondary market transactions, CDs to be issued only in dematerialised form. 2005 The minimum maturity period of CDs reduced from 15 days to 7 days. 2020 Small Finance Banks allowed to issue CDs Regional Rural Banks allowed to issue CDs. 2021 Banks allowed to buy-back CDs. CDs shall be issued in minimum denomination of ₹5 lakh and in multiples of ₹5 lakh thereafter. Sources: RBI and FIMMDA. Table A3: Description of Variables Variable Description Source CD Natural logarithm of seasonally adjusted sum of Certificate of Deposit CCIL issuances during a fortnight. VIX Market volatility index. National Stock Exchange (NSE) Sensex_retrn Fortnightly return in stock market. Bombay Stock Exchange CD_RATE_CH Fortnightly change in the Weighted Average Effective Interest Rate CCIL, authors calculation (WAEIR) for CD market. LAF_CH Fortnightly change in liquidity available in the system. RBI OIS_CH Fortnightly change in OIS rates (1 year tenor). Bloomberg ICD_ratio Incremental Credit Deposit ratio during the fortnight. RBI Dummy Dummy for increase in liquidity tightness (1 indicates period when RBI shifted its focus towards withdrawal of accommodation post pandem- RBI; authors calculation ic, otherwise 0) Source: Authors’ estimate. RBI Bulletin June 2025 101ARTICLE Drivers of CD Issuances: An Empirical Assessment Table A4: Pairwise Granger Causality Tests Null Hypothesis: Obs F-Statistic Prob. Remarks ICD does not Granger Cause CD_VOL 139 6.55 0.00 Causality CD_VOL does not Granger Cause ICD 0.13 0.88 No causality IIP does not Granger Cause CD_VOL 139 2.11 0.13 No causality CD_VOL does not Granger Cause IIP 0.27 0.77 No causality LAF_S does not Granger Cause CD_VOL 139 4.91 0.01 Causality CD_VOL does not Granger Cause LAF_S 2.08 0.13 No causality LG_SNSX does not Granger Cause CD_VOL 139 1.71 0.18 No causality CD_VOL does not Granger Cause LG_SNSX 0.98 0.38 No causality MCLR does not Granger Cause CD_VOL 139 9.91 0.00 Causality CD_VOL does not Granger Cause MCLR 6.92 0.00 Causality OIS does not Granger Cause CD_VOL 139 1.62 0.20 No causality CD_VOL does not Granger Cause OIS 0.34 0.71 No causality VIX does not Granger Cause CD_VOL 139 1.62 0.20 No causality CD_VOL does not Granger Cause VIX 0.34 0.71 No causality WACR does not Granger Cause CD_VOL 139 8.78 0.00 Causality CD_VOL does not Granger Cause WACR 3.27 0.04 Causality WAEIR does not Granger Cause CD_VOL 139 7.95 0.00 Causality CD_VOL does not Granger Cause WAEIR 2.19 0.12 No causality BSI does not Granger Cause CD_VOL 139 2.62 0.08 Causality CD_VOL does not Granger Cause BSI 1.94 0.15 No causality IIP does not Granger Cause ICD 137 1.06 0.35 No causality ICD does not Granger Cause IIP 0.37 0.69 No causality Sources: Authors’ estimate. Table A5: Descriptive Statistics Ln CD Volume (sea- Incremental credit LAF_CH Snsx_retrn OIS_CH VIX CDR_ CH sonally adjusted) deposit ratio Mean 9.261 49.09 -6.38 0.38 0.04 18.27 -0.44 Max 11.842 357.47 3045 11.78 25.81 70.38 26.65 min 4.751 -428.89 -2184 -12.57 -11.16 10.13 -100 Std Deviation 1.278 88.69 968.91 3.48 3.44 7.84 11.06 Skewness -0.99 -0.85 0.23 -0.37 2.96 3.37 -5.09 Kurtosis 4.37 9.40 3.06 5.39 25.29 19.24 49.04 Jarque-Bera 33.81 257.96 1.26 36.71 3104.81 1817.39 12876.05 Probability 0.00 0.00 0.53 0.00 0.00 0.00 0.00 Observations 140 141 140 140 140 141 139 Source: Authors’ estimate. 102 RBI Bulletin June 2025Drivers of CD Issuances: An Empirical Assessment ARTICLE Table A6: ADF Unit Root Test Results Variable t-statistic Probability D(Ln_cdvol_sa) -10.366*** 0.00 D(Incremental CD ratio) -18.673*** 0.00 LAF_CH -21.340*** 0.00 Snsx_retrn -5.966*** 0.00 OIS_CH -5.93*** 0.00 VIX -4.463*** 0.00 CDR_CH -10.463** 0.00 Note: *** denote significant level of 1 per cent, while** denote significance at 5 per cent confidence level. Source: Authors’ estimate. Table A7: Bounds Test Results F-Bounds Test Null Hypothesis: No levels relationship Test Statistic value Signif. I(0) I(1) F-statistic 4.88 10% 1.99 2.94 k 6 5% 2.27 3.28 1% 2.88 3.99 Source: Authors’ estimate. Chart A1: Stability Tests a. CUSUM of Squares Test b. CUSUM Test Source: Authors’ estimate. RBI Bulletin June 2025 103Predicting CPI inflation in India: Combining Forecasts from a ARTICLE ‘Suite’ of Statistical and Machine Learning Models Predicting CPI inflation in a ‘Suite of Models’ approach, integrating diverse frameworks to improve the predictive accuracy. India: Combining Forecasts Traditionally, models that are dependent on macro from a ‘Suite’ of Statistical and and/or micro economic theories detailing the complex macroeconomic relationships have often been used in Machine Learning Models most central banks for informing the policy decision- making. More recently, with the advancement in by Renjith Mohan, Saquib Hasan, computational capacity, large-scale statistical and Sayoni Roy, Suvendu Sarkar, and Joice John^ Machine Learning (ML) models are also becoming popular. While traditional models attempt to predict This article attempts to develop a methodology for the macroeconomic outcomes from the interactions of forecasting the headline Consumer Price Index (CPI) economic agents, ML and Deep Learning (DL) models inflation as well as CPI excluding food and fuel inflation are more data-dependent and focus more on the state for India using various statistical, machine learning, and of the economy. In practice, both can function in deep learning models, which are then combined using a complementarity to provide valuable information to performance-weighted forecasts combination approach. the policy makers. Traditional statistical models are This framework can also be used to generate density useful for their stability1 and interpretability, whereas forecasts and can provide estimates of standard deviation ML models may offer advancements in forecast as well as the asymmetry, around the weighted average accuracy. However, its inability to provide a coherent inflation forecasts. The results indicate a clear advantage in using all model classes together. It is also seen that a interpretation remains a concern. performance-weighted combination of statistical, ML In this context, this article attempts to a develop and DL models leverages the strengths of each approach, a ‘suite’ of statistical and ML models for forecasting resulting in more accurate and reliable inflation forecasts CPI headline and core inflation2 in India. It attempts in the Indian context. to synthesise two earlier works done in the Indian Introduction context viz. Bhoi and Singh (2022) which focused on ML models for inflation forecasting, and John et Inflation forecasts are a key set of information for the conduct of monetary policy in Inflation Targeting al. (2020) which explored the forecast combination (IT) central banks as forward-looking policies would approach using different time series and statistical have to take into account conditional predictions of models for forecasting CPI inflation. While Bhoi various key macroeconomic variables given the lags in and Singh (2022) found relative gains in using ML- transmission and other nominal rigidities. It is also based techniques over traditional ones in forecasting important to assess and communicate risks around inflation in India, John et al. (2020) established the those predictions, which helps in building credibility relative advantage of using forecast combination and improving transparency. Acknowledging that no approaches for inflation forecasting in India. single model can capture all economic complexities, central banks around the globe generally adopt 1 Stability here implies the robustness of model forecasts against variations in hyperparameter tuning. Unlike traditional statistical models, ^ The authors are from the Department of Statistics and Information which rely on well-defined parametric structures, ML and DL models often Management (DSIM), Reserve Bank of India (RBI). The views expressed in exhibit sensitivity to hyperparameter choices, leading to forecast volatility this article are those of the authors and do not represent the views of the across different tuning configurations. Reserve Bank of India. 2 CPI excluding food and fuel. This notion is used in the rest of the article RBI Bulletin June 2025 105ARTICLE Predicting CPI inflation in India: Combining Forecasts from a ‘Suite’ of Statistical and Machine Learning Models Building on these results, this article employs a economic forecasts. Their findings underscored the combination approach for forecasting CPI headline point that complexity in forecasting models does and core inflations in India, generated from a large not necessarily result in better accuracy, especially in number (say 216) of statistical, ML, and DL models3, uncertain environments. They found that forecasts and evaluates its pseudo-out of sample4 forecast from even simple combination approaches proved performance. Availability of large number of individual more accurate than sophisticated models in many forecasts enable this framework to sum up those cases. into density forecasts and hence can also be used to The “M” competitions initiated by Spyros estimate the standard deviation and skewness. The Makridakis in 1982 have had a colossal impact on article is structured as follows: Section 2 reviews the the forecasting sphere. Instead of focusing on the relevant literature; the data and methodologies are mathematical properties of the models (which was the outlined in Section 3; Section 4 discusses the empirical traditional way of looking at the forecasting models), results; and concluding remarks are put together in they paid sole attention to out of sample forecast Section 5. accuracy. They found that complex forecasting 2. Literature Review models do not necessarily always offer more precise projections than simpler ones. Following the legacy, With the increase in computational power over the “M4” competition, launched in 2017, tested a the years, as shown in Bates and Granger (1969), range of methods, including traditional statistical the world has shifted from using a ‘single best models like Auto-Regressive Integrated Moving model’ approach to ‘forecast combination’ approach, Average (ARIMA) and Exponential Smoothing (ETS) thereby, overcoming the uncertainties arising from alongside various ML and DL models. A key takeaway usage of different datasets, assumptions and various from the competition was that simple combination specifications of the models thus, by increasing the methods, such as Comb5—a straightforward average reliability of the results. of several ETS variants—outperformed more Stock and Watson (2004) employed the benefits advanced techniques across various data frequencies. of combination techniques to macroeconomic This reinforced the idea that simpler methods forecasting, particularly for output growth across often outperform more sophisticated models. The seven countries. They found that simple methods such competition also revealed the limitations of pure as averaging multiple forecasts, often outperformed ML models, which at times underperformed to more complex and adaptive techniques, and aided traditional statistical methods. This highlighted the to mitigate the instability often seen in individual need for a hybrid approach that combines ML/DL algorithms and traditional statistical methods in a 3 Statistical models are structured mathematical framework-based model built on probability theory and assumptions about data generating process. forecast combination framework to improve overall ML models are data-driven algorithms that identify patterns and optimise predictions without strict parametric assumptions. DL models are subset forecasting accuracy. of ML models where multi-layered neural networks are employed to extract hierarchical representations from large datasets for complex tasks. In the Indian context, John et al. (2020) explored 4 In a pseudo out-of-sample forecasting exercise (usually conducted ex- inflation forecast combination approach in the Indian post the availability of the actual data for verifying the forecastablity of the framework), the forecasts are generated at some time t in the past, using only the data available till that time for the parametrisation of the model 5 Comb model is the simple arithmetic average of single exponential as well as for generating the forecast of exogenous variables. smoothing, Holt and damped exponential smoothing. 106 RBI Bulletin June 2025Predicting CPI inflation in India: Combining Forecasts from a ARTICLE ‘Suite’ of Statistical and Machine Learning Models context, using 26 different time series and statistical and DL models, which are then aggregated using models, but not including ML and DL approaches. weights that are being derived based on the out of Their study emphasised the value of traditional sample forecast performance of these models. The econometric methods while acknowledging the detailed steps for estimating the inflation forecasts growing importance of ML and DL models. John et al. using performance-weighted combinations are as (2020) further pointed to the need for an integrated under: approach that combines the forecasts from individual i. Inflation series are seasonally adjusted using models to enhance the forecasting accuracy. Bhoi the X-13 ARIMA8 technique. and Singh (2022) focused on refining econometric models for inflation forecasting in India, stressing ii. Exogenous variables like INR-USD, Indian the enhanced performance of ML/DL models for basket of crude oil price, real GDP and output forecasting CPI inflation in the Indian context. gap are used for the estimations in some models. The series which are available only 3. Data and Methodology on quarterly frequency (GDP and output gap) 3.1 Data are converted to monthly frequency using The time-series CPI data released by the National the temporal disaggregation method9. Statistical Office (NSO) for the period January 2012 to iii. Seasonally adjusted annualised rates (SAAR) July 2024 has been used as the primary (dependent) of CPI (headline and core, separately) are variable of interest. Apart from headline inflation, then calculated. core inflation (derived from CPI by excluding food iv. Two different window sizes are used for and fuel) is also separately modelled for generating the estimation – 36 months (3 years) and forecasts using the same methodology. The other 96 months (8 years). These windows are explanatory variables used as the determinants of rolled over for the entire sample period. headline and core inflations in various models are – This produced multiple sub-samples of (i) crude oil price (Indian basket), (ii) Rupee-United data. A shorter window size of 3 years and a States Dollar (INR-USD) exchange rate, (iii) real gross longer window size of 8 years are used to domestic product (GDP) and output gap6 and (iv) minimise the bias emanating from a fixed policy repo rate7. sample size. 3.2 Methodology v. Each model in Table 1 is estimated separately A large number of h-period ahead inflation in each sub-sample using SAAR (headline and forecasts are generated using various statistical, ML, core, separately) as the dependent variable (or as one of the dependent variables). 6 Output gap is defined as (actual GDP level minus potential GDP level)*100/(potential GDP level). Potential GDP is estimated by using Hodrick-Prescott (HP) filter. 8 X-13 ARIMA uses Seasonal ARIMA (SARIMA) models to determine the 7 Crude oil prices (Indian Basket) are obtained from the Petroleum seasonal pattern in the economic series. The order of the SARIMA models Planning & Analysis Cell (PPAC) under the Ministry of Petroleum & Natural is determined based on the in-sample goodness of fit of different models Gas, Government of India (GoI). Real Gross Domestic Product data is and the best model is selected using suitable information criteria. The sourced from the Ministry of Statistics and Programme Implementation selected model, therefore, represents the underlying data-generating (MoSPI), GoI. The INR-USD exchange rate and the repo rate are sourced process through average parameter estimates. from the Database of Indian Economy (DBIE) maintained by the Reserve 9 Temporal disaggregation has been carried out using Denton-Cholette Bank of India (RBI). method (Denton, 1971). RBI Bulletin June 2025 107ARTICLE Predicting CPI inflation in India: Combining Forecasts from a ‘Suite’ of Statistical and Machine Learning Models Table 1: Suite of Models Class of Models Type of Models Specifications Sample Window Total number of (Number) Sizes (Number) models Statistical Models RW, AR, MA, ARMA, ARX, MAX, ARMAX, ARCH, MACH, 46 2 92 ARMACH, VAR, VARX, BVAR, BVARX Machine Learning Models SVM, EL, RF, GPR, NARNET-LM, NARNET-SCG, NARNET-BR, 44 2 88 NARNETX-LM, NARNETX-SCG, NARNETX-BR Deep Learning Models LSTM-SGDM, LSTM-ADAM 18 2 36 TOTAL 26 108 - 216 Note: RW: Random Walk; AR: Autoregressive, MA: Moving average, X: with exogenous variables, CH: Conditional heteroskedastic, VAR: Vector autoregression, BVAR: Bayesian VAR, SVM: Support Vector Machine, EL: Ensemble Learning, RF: Random Forest, GPR: Gaussian Process Regression, NARNET: Non-linear auto regressive neural network, LM: Levenberg–Marquardt, SCG: Scaled conjugate gradient; BR: Bayesian Regularization, LSTM: Long-short term memory, SGDM: Stochastic gradient descent with momentum, ADAM: Adaptive Moment Estimation. Refer to Annex Table 1 for details. Source: Authors’ estimates x. These weights are used to calculate the vi. The year-on-year inflation ( ) for each weighted average of inflation forecasts from model in each sub-sample are then forecasted the individual models. up to 12 months ahead horizon. vii. Pseudo-out-of-sample errors are then calculated. The pseudo-out-of-sample error xi. Furthermore, 216 different inflation point is defined as the difference between the forecasts for each horizon are bifurcated in actual value ( ) and the forecasted value two groups – (a) above the weighted average ( ). forecast, (b) below the weighted average viii. The 12-month ahead root mean squared forecast. Then, the RMSE-weighted standard forecast error (RMSE) for the model is deviation is calculated for both groups (σ 1 estimated using the following formulae. A and σ , where σ is the standard deviation window size of 12 months has been used to of the2 forecasts a1bove the weighted average calculate the RMSEs. These are estimated for forecast and σ is the standard deviation of each subsample. the forecasts 2below the weighted average forecast). xii. Assuming a split-normal distribution asymmetric confidence intervals of desired ix. The weights for the forecast combination are significant levels can be calculated around estimated as follows: each h-period ahead forecasts. xiii. Finally, the asymmetry of the forecast can be determined using the formulae: where, N is the total number of models. 108 RBI Bulletin June 2025Predicting CPI inflation in India: Combining Forecasts from a ARTICLE ‘Suite’ of Statistical and Machine Learning Models 3.3 Toolbox / Software the simple average forecasts for the entire sample period is carried out in the following sub-sections. The entire methodology described above has been programmed and a toolbox has been developed 4.2 A Comparison of RMSEs: Individual Models in MATLAB. Versus Performance-weighted: 4. Empirical Findings The average RMSE across the 12-month horizon of the performance-weighted forecasts for the headline 4.1 Estimated Inflation Forecast, Standard Deviation and core inflation are found to be approximately 70 and Asymmetry: An Illustration per cent lower than the benchmark random walk (RW) The 12-month ahead performance-weighted forecast. It is also found to be better than the forecasts inflation forecasts, standard deviation and generated by more than 75 per cent of models in all asymmetry, which are estimated using the suit of horizons. Certain models produce better forecasts models generated using the data till December 2023 is in some horizons and for some windows. The best presented in Chart 1. performers are not the same throughout all the horizons as well as for all the windows. However, a The realised monthly inflation numbers for 2024 judicious combination of forecasts (like performance- forecasted using the data till December 2023 fell well weighting) helps to reduce biases arising out of such within the range of forecasts and was broadly aligned divergences (Charts 2 & 3). Unlike what witnessed with performance-weighted forecasts. As expected, for core inflation forecasts, the plateauing nature of the standard deviations were higher for longer the RMSEs for headline inflation forecasts as horizon horizons. The asymmetricity was pointing towards increases may be due to the influence of the effect of an upward bias in the forecast. The comparison of the transitory shocks. the forecast accuracy of the performance-weighted forecasts vis-à-vis that of the individual models and 4.3 Forecast Accuracy10: Performance-weighted Chart 1: CPI Headline Inflation Forecasts: An Illustration a. CPI Headline Inflation b. Standard Deviation in the Forecasts Note: The upside arrow indicates an upside bias (> 1). Source: Authors’ estimates RBI Bulletin June 2025 109 tnec reP Range Actual Performance-weighted Forecasts Asymmetry 0.2 0.4 0.5 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 0011 .... 5702 0505 0.25 0.00 22-naJ 22-beF 22-raM 22-rpA 22-yaM 22-nuJ 22-luJ 22-guA 22-peS 22-tcO 22-voN 22-ceD 32-naJ 32-beF 32-raM 32-rpA 32-yaM 32-nuJ 32-luJ 32-guA 32-peS 32-tcO 32-voN 32-ceD 42-naJ 42-beF 42-raM 42-rpA 42-yaM 42-nuJ 42-luJ 42-guA 42-peS 42-tcO 42-voN 42-ceD 12 1.6 1.5 10 1.4 1.4 1.4 1.4 1.5 1.4 1.3 8 1.2 1.2 1.2 6 4 2 -ARTICLE Predicting CPI inflation in India: Combining Forecasts from a ‘Suite’ of Statistical and Machine Learning Models Chart 2. Pseudo-out of sample RMSE for Headline Inflation Note: Red markers are RMSEs of performance-weighted forecast. Source: Authors’ estimates. Versus Simple Average standard normal values. Table 2 presents the results for four forecast horizons, applied separately to two The Diebold-Mariano (DM)11 test has been used different rolling window sizes for both headline and for a formal statistical comparison of the performance- core inflation. The DM test was performed separately weighted combination method from that of a for each model type — Statistical, ML, DL, and a simple average forecast for each class of models combination of all models — for headline and core (Statistical, ML and DL) as well as for the entire basket inflation, as well as for each rolling window size. This of all 216 forecasts, separately, over different forecast resulted in sixteen instances (forecast horizon (4) x horizons. model types (4)) for each combination of window size In the DM test, the null hypothesis is that the and inflation type. simple average is as accurate as the performance- Overall, the performance-weighted forecasts weighted forecast combinations, while the alternative for both headline and core inflations were found hypotheses are: (i) the simple average is less accurate to be at par or better than simple average forecasts than the performance-weighted combination, and for all model classes and across horizons, attaching (ii) the simple average is more accurate than the a minimum guarantee of forecast accuracy for the performance-weighted combination. To minimise performance-weighted forecasts. The comparison the ‘size bias’ in small samples, the bias correction between the two aggregation methods for headline suggested by Harvey, Leybourne, and Newbold (1998) inflation using a rolling window of three years was applied, using Student’s t critical values instead of (column (1) in Table 2) revealed that the performance- 10 Root Mean Squared Error (RMSE) is mostly used as the metric of the weighted method significantly outperformed the accuracy of forecasting models. Lower RMSEs indicates better accuracy of simple average method in 12 out of 16 instances. the forecast. This notion is interchangeably used in this article. 11 DM Test compares forecast accuracy between two models and test However, with a rolling window of eight years for whether the difference in forecast errors between two models is statistically significant. headline inflation, the performance-weighted method 110 RBI Bulletin June 2025 sESMR Chart 3. Pseudo-out of sample RMSE for Core Inflation 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 1 2 3 4 5 6 7 8 9 10 11 12 Horizons sESMR 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 1 2 3 4 5 6 7 8 9 10 11 12 Horizons Note: Red markers are RMSEs of performance-weighted forecast. Source: Authors’ estimates.Predicting CPI inflation in India: Combining Forecasts from a ARTICLE ‘Suite’ of Statistical and Machine Learning Models only outperformed the simple average in two cases outperform the performance-weighted in any cases. (out of 16) (column (2) in Table 2). On the other For core inflation, the performance-weighted method hand, simple average forecasts did not significantly surpassed the simple average in six and four cases Table 2: Comparison of RMSEs - Simple Average Versus Performance-weighted: Diebold-Mariano (DM) Test Class of Models Forecast Horizon Headline Inflation Core Inflation Alternative (1 or 2) Window size=3 Window size=8 Window size=3 Window size=8 years years years years (1) (2) (3) (4) p-values 1 0.08* 0.07* 0.31 0.47 3 months 2 0.92 0.93 0.69 0.53 1 0.14 0.20 0.37 0.28 6 months 2 0.86 0.80 0.63 0.72 Statistical Models 1 0.14 0.17 0.32 0.22 9 months 2 0.86 0.83 0.68 0.78 1 0.15 0.21 0.21 0.22 12 months 2 0.85 0.79 0.79 0.78 1 0.08* 0.21 0.03** 0.06* 3 months 2 0.92 0.79 0.97 0.94 1 0.01*** 0.29 0.04** 0.02** 6 months 2 0.99 0.71 0.96 0.98 Machine Learning Models 1 0.05** 0.22 0.03** 0.02** 9 months 2 0.96 0.78 0.97 0.98 1 0.04** 0.29 0.00*** 0.00*** 12 months 2 0.96 0.71 1.00 1.00 1 0.07* 0.17 0.01*** 0.27 3 months 2 0.93 0.83 0.99 0.73 1 0.06* 0.19 0.10 0.18 6 months 2 0.94 0.81 0.90 0.82 Deep Learning Models 1 0.01*** 0.21 0.03** 0.02 9 months 2 0.99 0.79 0.97 0.98 1 0.00*** 0.02** 0.05 0.14 12 months 2 1.00 0.98 0.95 0.86 1 0.05** 0.39 0.17 0.14 3 months 2 0.95 0.61 0.83 0.86 1 0.08* 0.17 0.40 0.35 6 months 2 0.92 0.83 0.60 0.65 All Models 1 0.10* 0.20 0.29 0.35 9 months 2 0.90 0.80 0.71 0.65 1 0.14 0.20 0.16 0.24 12 months 2 0.86 0.80 0.84 0.76 *: Significant at 10% level; **: Significant at 5% level; ***: Significant at 1% level. Note: Null Hypothesis (H): Forecast Accuracy of Simple Average of Forecasts is equal to Forecast Accuracy of Performance-weighted Forecast Average 0 Alternative 1: Forecast Accuracy of Simple Average of Forecasts < Forecast Accuracy for Performance-weighted Forecast Average Alternative 2: Forecast Accuracy of Simple Average of Forecasts > Forecast Accuracy for Performance-weighted Forecast Average DM statistics presented in this table are adjusted for autocorrelation following Harvey, Leybourne, and Newbold (1998). Source: Authors’ estimates. RBI Bulletin June 2025 111ARTICLE Predicting CPI inflation in India: Combining Forecasts from a ‘Suite’ of Statistical and Machine Learning Models (out of 16) for window sizes of three and eight years, accurate inflation forecasts than that of simple respectively (columns (3) and (4) in Table 2). Notably, average forecast in the Indian context. the simple average never significantly outperformed 4.4 Forecast accuracy of performance-weighted the performance-weighted method. To reiterate forecasts among various classes of models the results, RMSEs for the simple average and After confirming the efficacy of the performance- performance-weighted forecasts are compared using the paired Wilcoxon signed-rank test12 (Table 3). weighted forecast over the simple average forecast, now we turn towards the comparison of the forecast Table 3 compares the RMSEs of simple average performance of the weighted average forecasts across forecasts versus performance-weighted forecast different classes of models viz. Statistical, ML, DL, averages of headline and core inflations, under and the super-class of all models. First, using the different model classes and rolling window sizes. The DM test, the forecast accuracy of the individual null hypothesis is that the RMSE of the simple average model classes (statistical, ML and DL) – aggregated forecast is as accurate as that of the performance using performance weights – is compared with the weighted one, with the alternatives being that the all-models combined forecasts, which aggregates simple average is either more or less accurate. Results show that the RMSE of the performance-weighted the forecasts from all 216 individual models using forecast average is significantly lower than that of performance-weighted weights. The DM test is the simple average on a consistent basis, reinforcing applied across different forecast horizons, rolling the DM test findings in Table 2 that performance- window sizes, and for inflation categories (headline weighted combinations yield more or similarly and core). Table 3: Comparison of RMSEs of Forecast Combinations (1 month to 12 months horizon) - Simple Average Versus Performance-weighted: Paired Wilcoxon Signed-Rank Test Class of Models Alternative Headline Inflation Core Inflation (1 or 2) Window size=3 years Window size=8 years Window size=3 years Window size=8 years (1) (2) (3) (4) p-values 1 0.99 1.00 1.00 1.00 Statistical Models 2 0.00*** 0.00*** 0.00*** 0.00*** 1 1.00 0.76 1.00 0.96 Machine Learning Models 2 0.00*** 0.00*** 0.00*** 0.046*** 1 1.00 1.00 0.99 1.00 Deep Learning Models 2 0.00*** 0.00*** 0.00*** 0.00*** 1 1.00 1.00 1.00 1.00 All Models together 2 0.00*** 0.00*** 0.00*** 0.00*** *: Significant at 10% level; **: Significant at 5% level; ***: Significant at 1% level. Note: Null Hypothesis (H): RMSEs of Simple Average of Forecasts are equal to RMSEs of Performance-weighted Forecast Average 0 Alternative 1: RMSEs of Simple Average of Forecasts < RMSEs of Performance-weighted Forecast Average Alternative 2: RMSEs of Simple Average of Forecasts > RMSEs of Performance-weighted Forecast Average Source: Authors’ estimates. 12 This non-parametric test is useful for comparing two matched samples, providing a robust alternative to the paired t-test when the focus is on comparative performances. The test assesses whether there is a greater-than-50 per cent probability that RMSEs of the performance-weighted average forecasts of 1-month to 12-month ahead horizon from a particular class of model is greater than that from the other classes, separately. 112 RBI Bulletin June 2025Predicting CPI inflation in India: Combining Forecasts from a ARTICLE ‘Suite’ of Statistical and Machine Learning Models The results show that for the 3-year rolling (2) and (4) in Table 4). More importantly, weighted window, the all-combined forecasts significantly forecasts from neither of the model classes (statistical, outperform the performance-weighted forecasts from ML or DL) in both horizons or for either headline or different class of models in four out of 12 instances, core inflations, significantly outperformed the all- for both core and headline inflation (columns (1) and models combined forecasts (Table 4). When each (3) in Table 4), while for others all-combined forecasts model class is analysed separately vis-à-vis the all- are at par across different class of models. However, models combined, performance-weighted forecast for an 8-year rolling window, the all-combined significantly outperformed the weighted forecast forecasts perform better in only one case (columns from the class of DL models in most instances (six out Table 4: Comparison of RMSEs among Classes of Models: Diebold-Mariano (DM) Test Class of Models against Forecast Horizon Alternative Headline Inflation Core Inflation All Models Together (1 or 2) Window size=3 Window size=8 Window size=3 Window size=8 years years years years (1) (2) (3) (4) p-values RBI Bulletin June 2025 113 sledoM fo ssalC 1 0.15 0.14 0.09* 0.48 3 months 2 0.85 0.86 0.91 0.52 1 0.13 0.16 0.36 0.29 6 months 2 0.87 0.84 0.64 0.71 Statistical Models 1 0.15 0.19 0.19 0.22 9 months 2 0.85 0.81 0.81 0.78 1 0.15 0.21 0.16 0.22 12 months 2 0.85 0.79 0.84 0.78 1 0.03** 0.13 0.19 0.01*** 3 months 2 0.97 0.87 0.81 0.99 1 0.18 0.16 0.39 0.21 6 months 2 0.82 0.84 0.61 0.79 Machine Learning Models 1 0.15 0.19 0.30 0.38 9 months 2 0.85 0.81 0.70 0.62 1 0.15 0.21 0.16 0.25 12 months 2 0.85 0.79 0.84 0.75 1 0.06* 0.14 0.00*** 0.13 3 months 2 0.94 0.86 1.00 0.87 1 0.08* 0.03** 0.00*** 0.26 6 months 2 0.92 0.97 1.00 0.74 Deep Learning Models 1 0.09* 0.33 0.07* 0.45 9 months 2 0.91 0.67 0.93 0.56 1 0.47 0.25 0.18 0.27 12 months 2 0.53 0.75 0.82 0.73 *: Significant at 10% level; **: Significant at 5% level; ***: Significant at 1% level. Note: Null Hypothesis (H): Forecast Accuracy of performance-weighted forecast average of a particular class of models is equal to Forecast Accuracy of 0 Performance-weighted Forecast Average of all models Alternative 1: Forecast Accuracy of performance-weighted forecast average of a particular class of models < Forecast Accuracy of Performance-weighted Forecast Average of all models Alternative 2: Forecast Accuracy of performance-weighted forecast average of a particular class of models > Forecast Accuracy of Performance-weighted Forecast Average of all models DM statistics presented in this table are adjusted for autocorrelation following Harvey, Leybourne, and Newbold (1998). Source: Authors’ estimates.ARTICLE Predicting CPI inflation in India: Combining Forecasts from a ‘Suite’ of Statistical and Machine Learning Models Table 5: Comparison of RMSEs of Performance-weighted Forecast Combinations (1 month to 12 months horizon) among Classes of Model: Paired Wilcoxon Signed-Rank Test All Models together vis à vis Alternative (1 or 2) Headline Inflation Core Inflation Window size=3 Window size=8 Window size=3 Window size=8 years years years years (1) (2) (3) (4) p-values of eight) but performs mostly similarly to that from reliable inflation forecasts in the Indian context. statistical and ML models. Additionally, forecast combination approach provides a confidence band that allows policymakers to assess The paired Wilcoxon signed-rank test supports these findings, showing that the all-models combined risks and make more informed decisions. forecasts outperformed the weighted forecasts from This approach is particularly valuable in the statistical models in most cases. Further, the accuracy Indian context given the complexities of its inflation of the all-models combined forecasts is found to be at dynamics, which is often influenced by global par with the forecast combination derived separately uncertainties and food price volatility. However, from ML and DL models. it is crucial to acknowledge that there are time- 5. Concluding Remarks variations, asymmetries and nonlinearities that The findings strongly support the effectiveness influence the inflationary developments emanating of forecast combination of statistical, ML and DL from overlapping shocks. Even then the combination methods in improving inflation forecasting accuracy of forecasts generated from statistical, ML and DL in the Indian context. The results indicate a clear models ensures robustness, as it minimises the model advantage in using all model classes together, with a misspecifications biases, making it a much more guarantee that the forecast accuracy never deteriorate reliable benchmark. while combining forecasts from all classes of models References: and getting better in most cases. It further reiterates that a performance-weighted combination of Bates, J. M., & Granger, C. W. (1969). The combination statistical, ML and DL models leverages the strengths of forecasts. Journal of the Operational Research of each approach, resulting in more accurate and Society, 20(4), 451-468. 114 RBI Bulletin June 2025 sledoM fo ssalC 1 0.00*** 0.00*** 0.88 0.00*** Statistical Models 2 1.00 0.99 0.13 1.00 1 0.78 0.99 0.15 0.00*** Machine Learning Models 2 0.26 0.00*** 0.87 1.00 1 0.37 0.00*** 0.42 1.00 Deep Learning Models 2 0.66 1.00 0.60 0.00*** *: Significant at 10% level; **: Significant at 5% level; ***: Significant at 1% level. Note: Null Hypothesis (H0): RMSEs of Performance-weighted Forecast Average of All models are equal to RMSEs of Performance-weighted Forecast Average of particular class of models Alternative 1: RMSEs of Performance-weighted Forecast Average of All models < RMSEs of Performance-weighted Forecast Average of particular class of models Alternative 2: RMSEs of Performance-weighted Forecast Average of All models > RMSEs of Performance-weighted Forecast Average of particular class of models Source: Authors’ estimates.Predicting CPI inflation in India: Combining Forecasts from a ARTICLE ‘Suite’ of Statistical and Machine Learning Models Denton, F. T. (1971). Adjustment of monthly or Singh, N., & Bhoi, B. (2022). Inflation Forecasting in quarterly series to annual totals: an approach based India: Are Machine Learning Techniques Useful?. on quadratic minimization. Journal of the American Reserve Bank of India Occasional Papers, 43(2). Statistical Association, 66(333), 99-102. Stock, J. H., & Watson, M. W. (2004). Combination John, J., Singh, S., & Kapur, M. (2020). Inflation Forecast forecasts of output growth in a seven-country data set. Combinations: The Indian Experience. Reserve Bank Journal of Forecasting, 23(6), 405–430. https://doi.org/ of India Working Paper Series No. 11. https://doi.org/10.1002/for.928 Makridakis, S., Spiliotis, E., & Assimakopoulos, V. Harvey, D. I., Leybourne, S. J., & Newbold, P. (1998). (2020). The M4 Competition: 100,000 time series and 61 forecasting methods. International Journal of Tests for forecast encompassing. Journal of Business Forecasting, 36(1), 54-74. & Economic Statistics, 16(2), 254-259. RBI Bulletin June 2025 115ARTICLE Predicting CPI inflation in India: Combining Forecasts from a ‘Suite’ of Statistical and Machine Learning Models Annex Table 1. List of Models Sr. Class of Algorithm/ Lag Hidden Type of Models No. Models Optimizer Length layers 1 Random Walk Models - - - 2 Autoregressive (AR) Models - 1 - 3 - 3 Moving average (MA) Models - 1 - AR: 1 - 3 4 ARMA Models - - MA: 1 AR: 1 - 3 5 AR conditional heteroscedastic (ARCH) Models - - GARCH: 1 MA: 1 6 MACH Models - - GARCH: 1 Statistical AR: 1 - 3 7 Models ARMACH Models - MA: 1 - GARCH: 1 8 Vector Auto Regressive (VAR) models - 1 - 3 - 9 Bayesian VAR models - 1 - 3 - 10 AR Models with Exogenous Variables - 1 - 3 - 11 MA Models with Exogenous Variables - 1 - 12 ARMA Models with Exogenous Variables - 1 - 3 - 13 VAR models with Exogenous Variables - 1 - 3 - 14 Bayesian VAR models with Exogenous Variables - 1 - 3 - 15 Support Vector Machine (SVM) for regression - 1 - 3 - 16 Ensemble learning technique for regression - 1 - 3 - 17 Binary decision tree for regression (Random Forest) - 1 - 3 - 18 Machine Gaussian process regression (GPR) model for regression - 1 - 3 - Learning Levenberg-Marquardt optimizer 19- Models Nonlinear autoregressive neural network (NARNET) Bayesian Regularization optimizer 1 - 3 5 & 10 21 models Scaled Conjugate Gradient optimizer Levenberg-Marquardt optimizer 22- Nonlinear autoregressive neural network models with Bayesian Regularization optimizer 1 - 3 5 & 10 24 Exogenous Variables (NARNETX) Scaled Conjugate Gradient optimizer Stochastic gradient descent with momentum Deep 25- (SGDM) optimizer 25, 50 & Learning Long Short-Term Memory (LSTM) Networks 1 - 3 26 Adaptive Moment Estimation (ADAM) 75 Models optimizer Source: Authors’ estimates. 116 RBI Bulletin June 2025CURRENT STATISTICS Select Economic Indicators Reserve Bank of India Money and Banking Prices and Production Government Accounts and Treasury Bills Financial Markets External Sector Payment and Settlement Systems Occasional SeriesCURRENT STATISTICS Contents No. Title Page 1 Select Economic Indicators 119 Reserve Bank of India 2 RBI – Liabilities and Assets 120 3 Liquidity Operations by RBI 121 4 Sale/ Purchase of U.S. Dollar by the RBI 122 4A Maturity Breakdown (by Residual Maturity) of Outstanding Forwards of RBI (US$ Million) 123 5 RBI's Standing Facilities 123 Money and Banking 6 Money Stock Measures 124 7 Sources of Money Stock (M) 125 3 8 Monetary Survey 126 9 Liquidity Aggregates 127 10 Reserve Bank of India Survey 128 11 Reserve Money – Components and Sources 128 12 Commercial Bank Survey 129 13 Scheduled Commercial Banks' Investments 129 14 Business in India – All Scheduled Banks and All Scheduled Commercial Banks 130 15 Deployment of Gross Bank Credit by Major Sectors 131 16 Industry-wise Deployment of Gross Bank Credit 132 17 State Co-operative Banks Maintaining Accounts with the Reserve Bank of India 133 Prices and Production 18 Consumer Price Index (Base: 2012=100) 134 19 Other Consumer Price Indices 134 20 Monthly Average Price of Gold and Silver in Mumbai 134 21 Wholesale Price Index 135 22 Index of Industrial Production (Base: 2011-12=100) 139 Government Accounts and Treasury Bills 23 Union Government Accounts at a Glance 139 24 Treasury Bills – Ownership Pattern 140 25 Auctions of Treasury Bills 140 Financial Markets 26 Daily Call Money Rates 141 27 Certificates of Deposit 142 28 Commercial Paper 142 29 Average Daily Turnover in Select Financial Markets 142 30 New Capital Issues by Non-Government Public Limited Companies 143 RBI Bulletin June 2025 117CURRENT STATISTICS No. Title Page External Sector 31 Foreign Trade 144 32 Foreign Exchange Reserves 144 33 Non-Resident Deposits 144 34 Foreign Investment Inflows 145 35 Outward Remittances under the Liberalised Remittance Scheme (LRS) for Resident Individuals 145 36 Indices of Nominal Effective Exchange Rate (NEER) and Real Effective Exchange Rate (REER) of the Indian Rupee 146 37 External Commercial Borrowings (ECBs) – Registrations 147 38 India’s Overall Balance of Payments (US $ Million) 148 39 India's Overall Balance of Payments (` Crore) 149 40 Standard Presentation of BoP in India as per BPM6 (US $ Million) 150 41 Standard Presentation of BoP in India as per BPM6 (` Crore) 151 42 India’s International Investment Position 152 Payment and Settlement Systems 43 Payment System Indicators 153 Occasional Series 44 Small Savings 155 45 Ownership Pattern of Central and State Governments Securities 156 46 Combined Receipts and Disbursements of the Central and State Governments 157 47 Financial Accommodation Availed by State Governments under various Facilities 158 48 Investments by State Governments 159 49 Market Borrowings of State Governments 160 50 (a) Flow of Financial Assets and Liabilities of Households - Instrument-wise 161 50 (b) Stocks of Financial Assets and Liabilities of Households- Select Indicators 164 Notes: .. = Not available. – = Nil/Negligible. P = Preliminary/Provisional. PR = Partially Revised. 118 RBI Bulletin June 2025CURRENT STATISTICS No. 1: Select Economic Indicators 2023-24 2024-25 Item 2024-25 Q3 Q4 Q3 Q4 1 2 3 4 5 1 Real Sector (% Change) 1.1 GVA at Basic Prices 6.4 8.0 7.3 6.5 6.8 1.1.1 Agriculture 4.6 1.5 0.9 6.6 5.4 1.1.2 Industry 4.5 12.6 9.9 3.5 4.7 1.1.3 Services 7.5 8.5 8.0 7.5 7.9 1.1a Final Consumption Expenditure 6.5 5.3 6.3 8.3 4.7 1.1b Gross Fixed Capital Formation 7. 1 9. 3 6 . 0 5 . 2 9 . 4 2024 2025 2024-25 Mar. Apr. Mar. Apr. 1 2 3 4 5 1.2 Index of Industrial Production 4.0 5.5 5.2 3.9 2.7 2 Money and Banking (% Change) 2.1 Scheduled Commercial Banks 2.1.1 Deposits 10.6 12.9 12.0 10.6 10.1 (10.3) (13.5) (12.6) (10.3) (9.8) 2.1.2 Credit # 12.1 16.3 15.5 12.1 11.1 (11.0) (20.2) (19.2) (11.0) (10.1) 2.1.2.1 Non-food Credit # 12.0 16.3 15.5 12.0 11.0 (11.0 ) (20.2 ) (19.2 ) (11.0 ) (10. 0 ) 2.1.3 Investment in Govt. Securities 10.6 11.1 10.7 10.6 9.8 (9.7) (12.8) (12.3) (9.7) (9.0) 2.2 Money Stock Measures 2.2.1 Reserve Money (M0) 4.3 5.6 5.8 4.3 3.7 2.2.2 Broad Money (M3) 9. 6 11. 1 10 . 9 9 . 6 9 . 6 (9.4) (11.6) (11.4) (9.4) (9.4) 3 Ratios (%) 3.1 Cash Reserve Ratio 4.00 4.50 4.50 4.00 4.00 3.2 Statutory Liquidity Ratio 18.00 18.00 18.00 18.00 18.00 3.3 Cash-Deposit Ratio 4.3 5.0 5.4 4.3 4.5 (4.3) (5.0) (5.3) (4.3) (4.5) 3.4 Credit-Deposit Ratio 79.1 78.1 77.4 79.1 78.1 (80.8) (80.3) (79.5) (80.8) (79.7) 3.5 Incremental Credit-Deposit Ratio # 89.2 95.8 37.4 89.2 -8.4 (86.1) (113.4) (34.4) (86.1) (-11.2) 3.6 Investment-Deposit Ratio 29.5 29.5 29.2 29.5 29.1 (29.7) (29.8) (29.5) (29.7) (29.3) 3.7 Incremental Investment-Deposit Ratio 29.5 25.8 8.1 29.5 -5.3 (28.1) (28.4) (6.9) (28.1) (-5.8) 4 Interest Rates (%) 4.1 Policy Repo Rate 6.2 5 6.5 0 6.5 0 6.2 5 6.0 0 4.2 Fixed Reverse Repo Rate 3.35 3.35 3.35 3.35 3.35 4.3 Standing Deposit Facility (SDF) Rate * 6.00 6.25 6.25 6.00 5.75 4.4 Marginal Standing Facility (MSF) Rate 6.50 6.75 6.75 6.50 6.25 4.5 Bank Rate 6.50 6.75 6.75 6.50 6.25 4.6 Base Rate 9.10/10.40 9.10/10.25 9.10/10.25 9.10/10.40 9.10/10.40 4.7 MCLR (Overnight) 8.15/8.45 8.00/8.60 8.00/8.60 8.15/8.45 8.15/8.45 4.8 Term Deposit Rate >1 Year 6.00/7.25 6.50/7.25 6.00/7.25 6.00/7.25 6.00/7.15 4.9 Savings Deposit Rate 2.70/3.00 2.70/3.00 2.70/3.00 2.70/3.00 2.70/2.75 4.10 Call Money Rate (Weighted Average) 6.35 6.85 6.65 6.35 5.86 4.11 91-Day Treasury Bill (Primary) Yield 6.52 7.01 6.92 6.52 5.90 4.12 182-Day Treasury Bill (Primary) Yield 6.52 7.14 7.04 6.52 5.93 4.13 364-Day Treasury Bill (Primary) Yield 6.47 7.08 7.07 6.47 5.91 4.14 10-Year G-Sec Par Yield (FBIL) 6.62 7.07 7.16 6.62 6.40 5 Reference Rate and Forward Premia 5.1 INR-US$ Spot Rate (Rs. Per Foreign Currency) 85.58 83.37 83.34 85.58 85.58 5.2 INR-Euro Spot Rate (Rs. Per Foreign Currency) 92.32 90.22 89.43 92.32 97.12 5.3 Forward Premia of US$ 1-month (%) 3.12 1.00 1.16 3.12 2.57 3-month (%) 2.56 1.11 1.26 2.56 2.34 6-month (%) 2.2 8 1.3 1 1.3 7 2.2 8 2.1 5 6 Inflation (%) 6.1 All India Consumer Price Index 4.6 4.9 4.8 3.3 3.2 6.2 Consumer Price Index for Industrial Workers 3.39 4.2 3.9 19.7 9.0 6.3 Wholesale Price Index 2.3 0.3 1.2 2.2 0.9 6.3.1 Primary Articles 5.2 4.6 5.2 1.3 -1.4 6.3.2 Fuel and Power -1.3 -2.7 -0.9 0.0 -2.2 6.3.3 Manufactured Products 1. 7 -0. 8 -0 . 1 3 . 2 2 . 6 7 Foreign Trade (% Change) 7.1 Imports 6.2 -6.4 11.1 11.4 19.1 7.2 Exports 0.1 -0.6 2.0 0.7 9.0 Note : Financial Benchmark India Pvt. Ltd. (FBIL) has commenced publication of the G-Sec benchmarks with effect from March 31, 2018 as per RBI circularFMRD.DIRD. 7/14.03.025/2017-18 dated March 31, 2018. FBIL has started dissemination of reference rates w.e.f. July 10, 2018. #: Bank credit growth and related ratios for all fortnights from December 3, 2021 to November 18, 2022 are adjusted for past reporting errors by select scheduled commercial banks (SCBs). Figures in parentheses include the impact of merger of a non-bank with a bank. *: As per Press Release No. 2022-2023/41 dated April 08, 2022. RBI Bulletin June 2025 119CURRENT STATISTICS Reserve Bank of India No. 2: RBI - Liabilities and Assets * (₹ Crore) Item As on the Last Friday/ Friday 2024-25 2024 2025 May May 02 May 09 May 16 May 23 May 30 1 2 3 4 5 6 7 1 Issue Department 1.1 Liabilities 1.1.1 Notes in Circulation 3683836 3537514 3774260 3804149 3805608 3805396 3798507 1.1.2 Notes held in Banking Department 11 14 11 17 16 16 13 1.1/1.2 Total Liabilities (Total Notes Issued) or Assets 3683847 3537528 3774272 3804166 3805624 3805412 3798520 1.2 Assets 1.2.1 Gold 235379 174725 244792 260985 245932 252131 255367 1.2.2 Foreign Securities 3448129 3362365 3529249 3542838 3559415 3553110 3542856 1.2.3 Rupee Coin 340 437 231 343 278 171 297 1.2.4 Government of India Rupee Securities - - - - - - - 2 Banking Department 2.1 Liabilities 2.1.1 Deposits 1709285 1733922 1500535 1556544 1603369 1861354 1824626 2.1.1.1 Central Government 100 101 100 100 100 100 101 2.1.1.2 Market Stabilisation Scheme - - - - - - 2.1.1.3 State Governments 42 42 42 42 42 42 42 2.1.1.4 Scheduled Commercial Banks 943060 951109 933070 925199 928136 935087 956086 2.1.1.5 Scheduled State Co-operative Banks 7776 8555 8423 8277 8276 8169 8301 2.1.1.6 Non-Scheduled State Co-operative Banks 5963 5224 5252 5299 5114 5200 5002 2.1.1.7 Other Banks 46963 49246 47516 47751 47161 47374 47182 2.1.1.8 Others 593085 589411 400591 472917 506200 757766 704649 2.1.1.9 Financial Institution Outside India 112296 130234 105541 96958 108338 107616 103263 2.1.2 Other Liabilities 2150508 1612560 2269533 2337286 2312623 2076485 2112709 2.1/2.2 Total Liabilities or Assets 3859793 3346482 3770068 3893830 3915992 3937839 3937335 2.2 Assets 2.2.1 Notes and Coins 11 14 11 17 17 16 13 2.2.2 Balances Held Abroad 1413591 1456002 1414408 1453056 1447619 1473711 1489277 2.2.3 Loans and Advances 2.2.3.1 Central Government - - - - - - - 2.2.3.2 State Governments 26284 10723 38480 51342 36404 24410 27482 2.2.3.3 Scheduled Commercial Banks 251984 71305 23458 25291 23081 23717 6516 2.2.3.4 Scheduled State Co-op.Banks - - - - - - - 2.2.3.5 Industrial Dev. Bank of India - - - - - - - 2.2.3.6 NABARD - - - - - - - 2.2.3.7 EXIM Bank - - - - - - - 2.2.3.8 Others 36426 9311 18700 17267 17019 15797 12340 2.2.3.9 Financial Institution Outside India 111768 129564 105709 97151 108184 107187 103071 2.2.4 Bills Purchased and Discounted 2.2.4.1 Internal - - - - - - - 2.2.4.2 Government Treasury Bills - - - - - - - 2.2.5 Investments 1560630 1365532 1704903 1755757 1817035 1814629 1813740 2.2.6 Other Assets 459101 304031 464398 493949 466633 478373 484895 2.2.6.1 Gold 429510 296897 446686 476236 448768 460079 465984 * Data are provisional. 120 RBI Bulletin June 2025CURRENT STATISTICS No. 3: Liquidity Operations by RBI (₹ Crore) Date Standing OMO (Outright) Net Injection (+)/ Liquidity Absorption (-) Liquidity Adjustment Facility Facilities (1+3+5+7+9-2-4-6 -8) Sale Purchase Variable Variable Reverse Rate Repo Rate MSF SDF Repo Reverse Repo Repo 1 2 3 4 5 6 7 8 9 10 Apr. 1, 2025 - - - - 2804 357282 - - - -354478 Apr. 2, 2025 - - 9170 - 176 393917 -664 - - -385235 Apr. 3, 2025 - - 6012 - 1494 413054 -2052 - - -407600 Apr. 4, 2025 - - 12419 - 2167 259087 600 - 20000 -223901 Apr. 5, 2025 - - - - 3959 208842 - - - -204883 Apr. 6, 2025 - - - - 3834 181582 - - - -177748 Apr. 7, 2025 - - 16505 - 542 165387 - - - -148340 Apr. 8, 2025 - - 23515 - 385 163624 -207 - - -139931 Apr. 9, 2025 - - 19295 - 757 209696 946 - 20000 -168698 Apr. 10, 2025 - - - - 43 155389 - - - -155346 Apr. 11, 2025 - - 14317 - 39 191464 - - - -177108 Apr. 12, 2025 - - - - 19 137537 - - - -137518 Apr. 13, 2025 - - - - 20 134809 - - - -134789 Apr. 14, 2025 - - - - 8324 139007 - - - -130683 Apr. 15, 2025 - - 9564 - 32 177126 - - - -167530 Apr. 16, 2025 - - 10346 - 102 188292 194 - - -177650 Apr. 17, 2025 - - 32245 - 2018 256201 - - - -221938 Apr. 18, 2025 - - - - 3 211023 - - - -211020 Apr. 19, 2025 - - - - 5036 134001 - - - -128965 Apr. 20, 2025 - - - - 4798 105973 - - - -101175 Apr. 21, 2025 - - 6332 - 879 87351 175 - 40000 -39965 Apr. 22, 2025 - - 17892 - 413 91222 768 - - -72149 Apr. 23, 2025 - - 18872 - 304 133629 1089 - 20000 -93364 Apr. 24, 2025 - - 9634 - 323 146584 - - - -136627 Apr. 25, 2025 - - 6947 - 298 145006 - - - -137761 Apr. 26, 2025 - - - - 189 133722 - - - -133533 Apr. 27, 2025 - - - - 223 125923 - - - -125700 Apr. 28, 2025 - - 4998 - 3190 132959 -1330 - - -126101 Apr. 29, 2025 - - 5901 - 716 121701 8 - - -115076 Apr. 30, 2025 - - 14952 - 8471 187714 770 - 20000 -143521 RBI Bulletin June 2025 121CURRENT STATISTICS No. 4: Sale/ Purchase of U.S. Dollar by the RBI i) Operations in onshore / offshore OTC segment Item 2024 2025 2024-25 Apr. Mar. Apr. 1 2 3 4 1 Net Purchase/ Sale of Foreign Currency (US $ Million) (1.1-1.2) -34511 -3647 14355 -1660 1.1 Purchase (+) 364200 8006 41515 10110 1.2 Sale (–) 398711 11653 27160 11770 2 ₹ equivalent at contract rate (₹ Crores) -291233 -30488 124586 -14635 3 Cumulative (over end-March) (US $ Million) -34511 -3647 -34511 -1660 (₹ Crore) -291233 -30488 -291233 -14635 4 Outstanding Net Forward Sales (-)/ Purchase (+) at the end of month (US -84345 -16257 -84345 -72575 $ Million) ii) Operations in currency futures segment Item 2024 2025 2024-25 Apr. Mar. Apr. 1 2 3 4 1 Net Purchase/ Sale of Foreign Currency (US $ Million) (1.1-1.2) 0 0 0 0 1.1 Purchase (+) 31415 1519 1202 0 1.2 Sale (–) 31415 1519 1202 0 2 Outstanding Net Currency Futures Sales (-)/ Purchase (+) at the end of 0 -2424 0 0 month (US $ Million) 122 RBI Bulletin June 2025CURRENT STATISTICS No. 4 A : Maturity Breakdown (by Residual Maturity) of Outstanding Forwards of RBI (US $ Million) Item As on April 30 , 2025 Long (+) Short (-) Net (1-2) 1 2 3 1. Upto 1 month 0 7360 -7360 2. More than 1 month and upto 3 months 0 7365 -7365 3. More than 3 months and upto 1 year 0 37750 -37750 4. More than 1 year 0 20100 -20100 Total (1+2+3+4) 0 72575 -72575 No. 5: RBI’s Standing Facilities (₹ Crore) Item As on the Last Reporting Friday 2024-25 2024 2025 May 31 Dec. 27 Jan. 24 Feb. 21 Mar. 21 Apr. 18 May 30 1 2 3 4 5 6 7 8 1 MSF 9961 14601 31127 3232 500 9961 2003 1540 2 Export Credit Refinance for Scheduled Banks 2.1 Limit - - - - - - - - 2.2 Outstanding - - - - - - - - 3 Liquidity Facility for PDs 3.1 Limit 9900 9900 9900 9900 9900 9900 14900 14900 3.2 Outstanding 9517 9311 8459 9556 9096 9517 7999 8595 4 Others 4.1 Limit 76000 76000 76000 76000 76000 76000 76000 76000 4.2 Outstanding - - - - - - - - 5 Total Outstanding (1+2.2+3.2+4.2) 19478 23912 39586 12788 9596 19478 10002 10135 RBI Bulletin June 2025 123CURRENT STATISTICS Money and Banking No. 6: Money Stock Measures (₹ Crore) Item Outstanding as on March 31/last reporting Fridays of the month/ reporting Fridays 2024-25 2024 2025 Apr. 19 Mar. 21 Apr. 04 Apr. 18 1 2 3 4 5 1 Currency with the Public (1.1 + 1.2 + 1.3 – 1.4) 3630751 3454255 3620845 3650071 3693751 1.1 Notes in Circulation 3686799 3532885 3677221 3702330 3749799 1.2 Circulation of Rupee Coin 35889 32689 35563 35889 35889 1.3 Circulation of Small Coins 743 743 743 743 743 1.4 Cash on Hand with Banks 93696 112314 93696 89913 93722 2 Deposit Money of the Public 2953329 2693081 2950448 3029352 2886362 2.1 Demand Deposits with Banks 2840023 2606729 2840023 2926145 2782612 2.2 'Other' Deposits with Reserve Bank 113307 86352 110426 103207 103750 3 M1 (1 + 2) 6584081 6147336 6571293 6679423 6580113 4 Post Office Saving Bank Deposits 201999 195445 201999 201999 201999 5 M2 (3 + 4) 6786080 6342781 6773292 6881422 6782112 6 Time Deposits with Banks 20643062 19006639 20643062 21104486 20992039 (20702508) (19112622) (20702508) (21164353) (21050572) 7 M3 (3 + 6) 27227143 25153975 27214355 27783909 27572152 (27286589) (25259958) (27273801) (27843776) (27630685) 8 Total Post Office Deposits 1395485 1324920 1395485 1395485 1395485 9 M4 (7 + 8) 28622628 26478895 28609840 29179394 28967637 (28682074) (26584878) (28669286) (29239261) (29026170) Figures in parentheses include the impact of merger of a non-bank with a bank. 124 RBI Bulletin June 2025CURRENT STATISTICS No. 7 : Sources of Money Stock (M) 3 (₹ Crore) Sources Outstanding as on March 31/last reporting Fridays of the month/reporting Fridays 2024-25 2024 2025 Apr. 19 Mar. 21 Apr. 04 Apr. 18 1 2 3 4 5 1 Net Bank Credit to Government 8463065 7589043 8135829 8501313 8576102 1 Net Bank Credit to Government (Including Merger) (8510825) (7676346) (8183590) (8549079) (8623867) 1.1 RBI’s net credit to Government (1.1.1–1.1.2) 1508105 1221629 1180870 1577390 1626509 1.1.1 Claims on Government 1591591 1372757 1528323 1626086 1654545 1.1.1.1 Central Government 1558903 1355261 1509131 1587786 1617753 1.1.1.2 State Governments 32688 17496 19192 38299 36792 1.1.2 Government deposits with RBI 83485 151128 347453 48695 28036 1.1.2.1 Central Government 83443 151086 347411 48653 27993 1.1.2.2 State Governments 42 42 42 42 42 1.2 Other Banks’ Credit to Government 6954959 6367414 6954959 6923923 6949593 1.2 Other Banks Credit to Government (Including Merger) (7002720) (6454717) (7002720) (6971689) (6997358) 2 Bank Credit to Commercial Sector 18646762 16729391 18644339 18794027 18583507 2 Bank Credit to Commercial Sector (Including Merger) (19068129) (17250209) (19065706) (19210628) (18995997) 2.1 RBI’s credit to commercial sector 38246 10804 35823 21538 19280 2.2 Other banks’ credit to commercial sector 18608516 16718586 18608516 18772489 18564228 2.2 Other banks credit to commercial sector (Including Merger) (19029883) (17239405) (19029883) (19189091) (18976717) 2.2.1 Bank credit by commercial banks 17822605 15970978 17822605 17984731 17775378 2.2.1 Bank credit by commercial banks (Including Merger) (18243972) (16491796) (18243972) (18401333) (18187868) 2.2.2 Bank credit by co-operative banks 766659 729036 766659 768373 769470 2.2.3 Investments by commercial and co-operative banks in other securities 19252 18573 19252 19385 19379 2.2.3 Investments by commercial and co-operative banks in other securities (Including Merger) (19252) (18573) (19252) (19385) (19379) 3 Net Foreign Exchange Assets of Banking Sector (3.1 + 3.2) 6027804 5520761 5977361 6079051 6169394 3.1 RBIs net foreign exchange assets (3.1.1 - 3.1.2) 5550947 5194340 5500504 5602194 5692537 3.1.1 Gross foreign assets 5550956 5194342 5500509 5602201 5692537 3.1.2 Foreign liabilities 9 2 5 7 1 3.2 Other banks’ net foreign exchange assets 476857 326421 476857 476857 476857 4 Government’s Currency Liabilities to the Public 36632 33432 36306 36632 36632 5 Banking Sector’s Net Non-monetary Liabilities 5947120 4718651 5579480 5627113 5793482 5 Banking Sectors Net Non-monetary Liabilities (Including Merger) (6356801) (5220790) (5989161) (6031614) (6195205) 5.1 Net non-monetary liabilities of RBI 2147427 1752989 2159098 2205404 2308158 5.2 Net non-monetary liabilities of other banks (residual) 3799694 2965662 3420382 3421709 3485324 5.2 Net non-monetary liabilities of other banks (residual) (Including Merger) (4209375) (3467801) (3830063) (3826210) (3887047) M₃(1+2+3+4–5) 27227143 25153975 27214355 27783909 27572152 M3 (1+2+3+4-5) (Including Merger) (27286589) (25259958) (27273801) (27843776) (27630685) Figures in parentheses include the impact of merger of a non-bank with bank. RBI Bulletin June 2025 125CURRENT STATISTICS No. 8: Monetary Survey (₹ Crore) Item Outstanding as on March 31/last reporting Fridays of the month/reporting Fridays 2024-25 2024 2025 Apr. 19 Mar. 21 Apr. 04 Apr. 18 1 2 3 4 5 Monetary Aggregates NM₁ (1.1+1.2.1+1.3) 6584081 6147336 6571293 6679423 6580113 NM₂ (NM₁ + 1.2.2.1) 15741937 14598412 15729149 16047804 15896809 NM2 (NM1 + 1.2.2.1) (Including Merger) (15768688) (14646104) (15755900) (16074744) (15923149) NM₃ (NM₂ +1.2.2.2 + 1.4 = 2.1 + 2.2 + 2.3 – 2.4 – 2.5) 27850121 25702843 27837333 28418643 28152487 NM3 (NM2 + 1.2.2.2 + 1.4 = 2.1 + 2.2 + 2.3 - 2.4 - 2.5) (Including Merger) (27909568) (25808825) (27896780) (28478509) (28211019) 1 Components 1.1 Currency with the Public 3630751 3454255 3620845 3650071 3693751 1.2 Aggregate Deposits of Residents 23190815 21386899 23190815 23744768 23486381 1.2 Aggregate Deposits of Residents (Including Merger) (23250261) (21492881) (23250261) (23804635) (23544913) 1.2.1 Demand Deposits 2840023 2606729 2840023 2926145 2782612 1.2.2 Time Deposits of Residents 20350792 18780169 20350792 20818624 20703768 1.2.2 Time Deposits of Residents (Including Merger) (20410239) (18886151) (20410239) (20878490) (20762301) 1.2.2.1 Short-term Time Deposits 9157856 8451076 9157856 9368381 9316696 1.2.2.1 Short-term Time Deposits (Including Merger) (9184607) (8498768) (9184607) (9395321) (9343035) 1.2.2.1.1 Certificates of Deposits (CDs) 527375 370047 527375 523653 521063 1.2.2.2 Long-term Time Deposits 11192936 10329093 11192936 11450243 11387073 1.2.2.2 Long-term Time Deposits (Including Merger) (11225631) (10387383) (11225631) (11483170) (11419265) 1.3 'Other' Deposits with RBI 113307 86352 110426 103207 103750 1.4 Call/Term Funding from Financial Institutions 915248 775338 915248 920596 868605 2 Sources 2.1 Domestic Credit 28333316 25413620 28003657 28570901 28425537 2.1 Domestic Credit (Including Merger) (28802443) (26021742) (28472785) (29035269) (28885792) 2.1.1 Net Bank Credit to the Government 8463065 7589043 8135829 8501313 8576102 2.1.1 Net Bank Credit to the Government (Including Merger) (8510825) (7676346) (8183590) (8549079) (8623867) 2.1.1.1 Net RBI credit to the Government 1508105 1221629 1180870 1577390 1626509 2.1.1.2 Credit to the Government by the Banking System 6954959 6367414 6954959 6923923 6949593 2.1.1.2 Credit to the Government by the Banking System (Including Merger) (7002720) (6454717) (7002720) (6971689) (6997358) 2.1.2 Bank Credit to the Commercial Sector 19870251 17824577 19867828 20069588 19849435 2.1.2 Bank Credit to the Commercial Sector (Including Merger) (20291618) (18345395) (20289195) (20486190) (20261925) 2.1.2.1 RBI Credit to the Commercial Sector 38246 10804 35823 21538 19280 2.1.2.2 Credit to the Commercial Sector by the Banking System 19832006 17813773 19832006 20048051 19830156 2.1.2.2 Credit to the Commercial Sector by the Banking System (Including Merger) (20253372) (18334591) (20253372) (20464652) (20242645) 2.1.2.2.1 Other Investments ( Non-SLR Securities) 1208294 1079540 1208294 1259278 1249654 2.2 Government's Currency Liabilities to the Public 36632 33432 36306 36632 36632 2.3 Net Foreign Exchange Assets of the Banking Sector 5605462 5106924 5555018 5682160 5727331 2.3.1 Net Foreign Exchange Assets of the RBI 5550947 5194340 5500504 5602194 5692537 2.3.2 Net Foreign Currency Assets of the Banking System 54514 -87416 54514 79966 34794 2.4 Capital Account 4481192 4058263 4550842 4559109 4715903 2.5 Other items (net) 2053777 1295009 1616487 1716442 1722833 Figures in parentheses include the impact of merger of a non-bank with a bank. 126 RBI Bulletin June 2025CURRENT STATISTICS No. 9: Liquidity Aggregates (₹ Crore) Aggregates 2024-25 2024 2025 Apr. Feb. Mar. Apr. 1 2 3 4 5 1 NM₃ 27837333 25702843 27461802 27837333 28152487 (27896780) (25808825) (27523665) (27896780) (28211019) 2 Postal Deposits 739921 702549 739921 739921 739921 3 L₁ ( 1 + 2) 28577254 26405392 28201723 28577254 28892408 (28636701) (26511374) (28263586) (28636701) (28950940) 4 Liabilities of Financial Institutions 95148 78167 80416 95148 102284 4.1 Term Money Borrowings 10 1858 16 10 4 4.2 Certificates of Deposit 80810 63595 66365 80810 87705 4.3 Term Deposits 14328 12713 14035 14328 14575 5 L₂ (3 + 4) 28672403 26483559 28282140 28672403 28994692 (28731849) (26589541) (28344002) (28731849) (29053224) 6 Public Deposits with Non-Banking Financial Companies 121178 .. .. 121178 .. 7 L₃ (5 + 6) 28793581 .. .. 28793581 .. Notes : 1 . Figures in the columns might not add up to the total due to rounding off of numbers. 2. Figures in parentheses include the impact of merger of a non-bank with a bank. RBI Bulletin June 2025 127CURRENT STATISTICS No. 10: Reserve Bank of India Survey (₹ Crore) Item Outstanding as on March 31/last reporting Fridays of the month/reporting Fridays 2024-25 2024 2025 Apr. 19 Mar. 21 Apr. 04 Apr. 18 1 2 3 4 5 1 Components 1.1 Currency in Circulation 3724448 3566568 3714541 3739984 3787473 1.2 Bankers’ Deposits with the RBI 991488 1007174 941950 990201 969883 1.2.1 Scheduled Commercial Banks 926001 944236 882415 930337 909269 1.3 ‘Other’ Deposits with the RBI 113307 86352 110426 103207 103750 Reserve Money (1.1 + 1.2 + 1.3 = 2.1 + 2.2 + 2.3 – 2.4 – 2.5) 4829243 4660094 4766917 4833392 4861106 2 Sources 2.1 RBI’s Domestic Credit 1389090 1185311 1389205 1399970 1440096 2.1.1 Net RBI credit to the Government 1508105 1221629 1180870 1577390 1626509 2.1.1.1 Net RBI credit to the Central Government (2.1.1.1.1 + 2.1.1.1.2 + 2.1.1.1.3 + 2.1.1.1.4 – 2.1.1.1.5) 1475460 1204176 1161720 1539133 1589760 2.1.1.1.1 Loans and Advances to the Central Government - - - - - 2.1.1.1.2 Investments in Treasury Bills - - - - - 2.1.1.1.3 Investments in dated Government Securities 1558574 1354918 1508724 1587489 1617568 2.1.1.1.3.1 Central Government Securities 1558574 1354918 1508724 1587489 1617568 2.1.1.1.4 Rupee Coins 329 343 407 297 185 2.1.1.1.5 Deposits of the Central Government 83443 151086 347411 48653 27993 2.1.1.2 Net RBI credit to State Governments 32646 17454 19150 38257 36749 2.1.2 RBI’s Claims on Banks -157261 -47122 172512 -198958 -205693 2.1.2.1 Loans and Advances to Scheduled Commercial Banks -157261 -47122 172512 -198958 -205693 2.1.3 RBI’s Credit to Commercial Sector 38246 10804 35823 21538 19280 2.1.3.1 Loans and Advances to Primary Dealers 9182 8770 9517 7066 7999 2.1.3.2 Loans and Advances to NABARD - - - - - 2.2 Government’s Currency Liabilities to the Public 36632 33432 36306 36632 36632 2.3 Net Foreign Exchange Assets of the RBI 5550947 5194340 5500504 5602194 5692537 2.3.1 Gold 668162 474181 664219 676510 721972 2.3.2 Foreign Currency Assets 4882794 4720161 4836289 4925691 4970566 2.4 Capital Account 1875114 1697208 1944763 1927539 2035757 2.5 Other Items (net) 272313 55781 214335 277865 272401 No. 11: Reserve Money - Components and Sources (₹ Crore) Item Outstanding as on March 31/last Fridays of the month/Fridays 2024-25 2024 2025 Apr. 26 Mar. 28 Apr. 04 Apr. 11 Apr. 18 Apr. 25 1 2 3 4 5 6 7 Reserve Money (1.1 + 1.2 + 1.3 = 2.1 + 2.2 + 2.3 + 2.4 + 2.5 – 2.6) 4829243 4734241 4836336 4833392 4875039 4861106 4909934 1 Components 1.1 Currency in Circulation 3724448 3566523 3720468 3739984 3780610 3787473 3797541 1.2 Bankers' Deposits with RBI 991488 1081463 1003762 990201 991277 969883 1008614 1.3 ‘Other’ Deposits with RBI 113307 86255 112106 103207 103153 103750 103780 2 Sources 2.1 Net Reserve Bank Credit to Government 1508105 1115036 1388403 1577390 1614985 1626509 1581741 2.2 Reserve Bank Credit to Banks -157261 149292 -27049 -198958 -185651 -205693 -121917 2.3 Reserve Bank Credit to Commercial Sector 38246 11266 38467 21538 18411 19280 21982 2.4 Net Foreign Exchange Assets of RBI 5550947 5166731 5526072 5602194 5669221 5692537 5714171 2.5 Government's Currency Liabilities to the Public 36632 33632 36632 36632 36632 36632 36922 2.6 Net Non- Monetary Liabilities of RBI 2147427 1741717 2126189 2205404 2278560 2308158 2322965 128 RBI Bulletin June 2025CURRENT STATISTICS No. 12: Commercial Bank Survey (₹ Crore) Item Outstanding as on last reporting Fridays of the month/ reporting Fridays of the month 2024-25 2024 2025 Apr. 19 Mar. 21 Apr. 04 Apr. 18 1 2 3 4 5 1 Components 1.1 Aggregate Deposits of Residents 22228885 20420942 22228885 22769964 22514062 (22288331) (20526924) (22288331) (22829831) (22572594) 1.1.1 Demand Deposits 2698049 2461947 2698049 2781234 2638562 1.1.2 Time Deposits of Residents 19530836 17958995 19530836 19988730 19875499 (19590283) (18064977) (19590283) (20048596) (19934032) 1.1.2.1 Short-term Time Deposits 8788876 8081548 8788876 8994928 8943975 1.1.2.1.1 Certificates of Deposits (CDs) 527375 370047 527375 523653 521063 1.1.2.2 Long-term Time Deposits 10741960 9877447 10741960 10993801 10931525 1.2 Call/Term Funding from Financial Institutions 915248 775338 915248 920596 868605 2 Sources 2.1 Domestic Credit 25687563 23118372 25687563 25868218 25678284 (26156690) (23726494) (26156690) (26332586) (26138539) 2.1.1 Credit to the Government 6649537 6059797 6649537 6615848 6645062 (6697298) (6147101) (6697298) (6663613) (6692827) 2.1.2 Credit to the Commercial Sector 19038025 17058575 19038025 19252371 19033223 (19459392) (17579393) (19459392) (19668972) (19445712) 2.1.2.1 Bank Credit 17822605 15970978 17822605 17984731 17775378 (18243972) (16491796) (18243972) (18401333) (18187868) 2.1.2.1.1 Non-food Credit 17786074 15952888 17786074 17955374 17743253 (18207441) (16473706) (18207441) (18371976) (18155742) 2.1.2.2 Net Credit to Primary Dealers 15458 15910 15458 16547 16537 2.1.2.3 Investments in Other Approved Securities 630 1110 630 777 616 2.1.2.4 Other Investments (in non-SLR Securities) 1199332 1070577 1199332 1250315 1240692 2.2 Net Foreign Currency Assets of Commercial Banks (2.2.1-2.2.2-2.2.3) 54514 -87416 54514 79966 34794 2.2.1 Foreign Currency Assets 529621 288100 529621 541180 501919 2.2.2 Non-resident Foreign Currency Repatriable Fixed Deposits 292270 226470 292270 285863 288271 2.2.3 Overseas Foreign Currency Borrowings 182837 149045 182837 175352 178853 2.3 Net Bank Reserves (2.3.1+2.3.2-2.3.3) 1165137 1091678 791777 1206720 1196674 2.3.1 Balances with the RBI 926001 944236 882415 930337 909269 2.3.2 Cash in Hand 81874 100321 81874 77425 81713 2.3.3 Loans and Advances from the RBI -157261 -47122 172512 -198958 -205693 2.4 Capital Account 2581908 2336884 2581908 2607399 2655975 2.5 Other items (net) (2.1+2.2+2.3-2.4-1.1-1.2) 1181172 589471 807812 856945 871111 2.5.1 Other Demand and Time Liabilities (net of 2.2.3) 878795 748203 878795 846530 836232 2.5.2 Net Inter-Bank Liabilities (other than to PDs) 118268 196397 118268 122227 120132 Figures in parentheses include the impact of merger of a non-bank with a bank. No. 13: Scheduled Commercial Banks’ Investments (₹ Crore) Item As on 2024 2025 March 21, 2025 Apr. 19 Mar. 21 Apr. 04 Apr. 18 1 2 3 4 5 1 SLR Securities 6697928 6148210 6697928 6664391 6693443 (6650167) (6060907) (6650167) (6616625) (6645677) 2 Other Government Securities (Non-SLR) 165500 165537 165500 163820 164973 3 Commercial Paper 63163 47918 63163 61210 68491 4 Shares issued by 4.1 PSUs 13874 12835 13874 15170 15355 4.2 Private Corporate Sector 95984 88509 95984 102895 102574 4.3 Others 7664 7378 7664 7896 8182 5 Bonds/Debentures issued by 5.1 PSUs 130308 115109 130308 129762 127728 5.2 Private Corporate Sector 248138 249472 248138 254454 253869 5.3 Others 150000 125034 150000 153185 156987 6 Instruments issued by 6.1 Mutual funds 119867 85830 119867 155449 144485 6.2 Financial institutions 204865 175705 204865 206473 198048 Notes: Data against column Nos. (1), (2) & (3) are final and for column Nos. (4) & (5) data are Provisional. 1. Data since July 14, 2023 include the impact of the merger of a non-bank with a bank. 2. Figures in parentheses exclude the impact of the merger. RBI Bulletin June 2025 129CURRENT STATISTICS No. 14: Business in India - All Scheduled Banks and All Scheduled Commercial Banks (₹ Crore) Item As on the Last Reporting Friday (in case of March)/ Last Friday All Scheduled Banks All Scheduled Commercial Banks 2024 2025 2024 2025 2024-25 2024-25 Apr. Mar. Apr. Apr. Mar. Apr. 1 2 3 4 5 6 7 8 Number of Reporting Banks 208 209 208 208 135 136 135 135 1 Liabilities to the Banking System 458011 541798 458011 485692 451305 537356 451305 480018 1.1 Demand and Time Deposits from Banks 315675 296469 315675 354621 309414 292303 309414 349245 1.2 Borrowings from Banks 112027 170567 112027 107502 111976 170542 111976 107500 1.3 Other Demand and Time Liabilities 30310 74763 30310 23569 29916 74511 29916 23272 2 Liabilities to Others 25053097 22917159 25053097 25236728 24557481 22440579 24557481 24727930 2.1 Aggregate Deposits 23055487 21264492 23055487 23332769 22580601 20804308 22580601 22840577 (22996040) (21160334) (22996040) (23274855) (22521155) (20700150) (22521155) (22782663) 2.1.1 Demand 2748263 2530730 2748263 2680697 2698049 2480773 2698049 2630004 2.1.2 Time 20307224 18733762 20307224 20652072 19882552 18323535 19882552 20210573 2.2 Borrowings 920568 789091 920568 888614 915248 784526 915248 884265 2.3 Other Demand and Time Liabilities 1077042 863576 1077042 1015345 1061632 851745 1061632 1003088 3 Borrowings from Reserve Bank 311466 209301 311466 23088 311466 209301 311466 23088 3.1 Against Usance Bills /Promissory Notes - - - - - - - - 3.2 Others 311466 209301 311466 23088 311466 209301 311466 23088 4 Cash in Hand and Balances with Reserve Bank 985044 1131231 985044 1051971 964289 1108501 964289 1030327 4.1 Cash in Hand 84399 93173 84399 85275 81874 90784 81874 82976 4.2 Balances with Reserve Bank 900645 1038058 900645 966696 882415 1017716 882415 947351 5 Assets with the Banking System 432645 435794 432645 463223 348496 363001 348496 372327 5.1 Balances with Other Banks 273720 244270 273720 302288 215801 193978 215801 237512 5.1.1 In Current Account 13239 12215 13239 12946 10619 9388 10619 10653 5.1.2 In Other Accounts 260481 232055 260481 289342 205182 184590 205182 226859 5.2 Money at Call and Short Notice 44772 30878 44772 38697 25838 13390 25838 19488 5.3 Advances to Banks 43856 48078 43856 41915 39504 45925 39504 38818 5.4 Other Assets 70296 112568 70296 80323 67353 109708 67353 76510 6 Investment 6850574 6281775 6850574 6837270 6697928 6129440 6697928 6682751 (6802814) (6194450) (6802814) (6790686) (6650167) (6042115) (6650167) (6636167) 6.1 Government Securities 6842024 6274221 6842024 6828474 6697298 6128369 6697298 6682185 6.2 Other Approved Securities 8550 7553 8550 8796 630 1070 630 566 7 Bank Credit 18708286 16981402 18708286 18680190 18243972 16545337 18243972 18214777 (18286919) (16462061) (18286919) (18266000) (17822605) (16025997) (17822605) (17800587) 7a Food Credit 87145 81990 87145 98699 36531 28213 36531 46725 7.1 Loans, Cash-credits and Overdrafts 18370704 16662862 18370704 18337163 17909851 16230106 17909851 17875224 7.2 Inland Bills-Purchased 76523 65609 76523 80991 74963 64286 74963 79561 7.3 Inland Bills-Discounted 222320 212417 222320 224117 221059 211116 221059 222677 7.4 Foreign Bills-Purchased 15357 19194 15357 14893 15122 18965 15122 14661 7.5 Foreign Bills-Discounted 23382 21320 23382 23026 22977 20865 22977 22655 Notes: 1. Data in column Nos. (4) & (8) are Provisional. 2. Data since July 2023 include the impact of the merger of a non-bank with a bank. 3. Figures in parentheses exclude the impact of the merger. 130 RBI Bulletin June 2025CURRENT STATISTICS No. 15: Deployment of Gross Bank Credit by Major Sectors (₹ Crore) Outstanding as on Growth(%) Mar. 21, Financial Sector 2025 2024 2025 year so far Y-o-Y Apr. 19 Mar. 21 Apr. 18 2025-26 2025 1 2 3 4 % % I. Bank Credit (II + III) 18243936 16491796 18243936 18186759 -0.3 10.3 (17822569) (15970978) (17822569) (17774269) (-0.3) (11.3) II. Food Credit 36531 18090 36531 32126 -12.1 77.6 III. Non-food Credit 18207404 16473706 18207404 18154634 -0.3 10.2 (17786038) (15952888) (17786038) (17742144) (-0.2) (11.2) 1. Agriculture & Allied Activities 2287071 2115986 2287071 2309631 1.0 9.2 2. Industry (Micro and Small, Medium and Large) 3937149 3655455 3937149 3895471 -1.1 6.6 (3925090) (3639138) (3925090) (3883660) (-1.1) (6.7) 2.1 Micro and Small 791721 731994 791721 798669 0.9 9.1 2.2 Medium 360475 309427 360475 365378 1.4 18.1 2.3 Large 2784953 2614034 2784953 2731423 -1.9 4.5 3. Services 5161462 4605915 5161462 5088547 -1.4 10.5 (5094021) (4509188) (5094021) (5012374) (-1.6) (11.2) 3.1 Transport Operators 258409 234760 258409 260093 0.7 10.8 3.2 Computer Software 32915 24774 32915 33451 1.6 35.0 3.3 Tourism, Hotels & Restaurants 83091 77054 83091 84692 1.9 9.9 3.4 Shipping 7305 6884 7305 7778 6.5 13.0 3.5 Aviation 46026 44998 46026 46540 1.1 3.4 3.6 Professional Services 195956 173429 195956 194449 -0.8 12.1 3.7 Trade 1186787 1020885 1186787 1163877 -1.9 14.0 3.7.1. Wholesale Trade¹ 648619 537086 648619 621874 -4.1 15.8 3.7.2 Retail Trade 538168 483799 538168 542003 0.7 12.0 3.8 Commercial Real Estate 532757 468803 532757 549472 3.1 17.2 (488689) (402521) (488689) (503090) (2.9) (25.0) 3.9 Non-Banking Financial Companies (NBFCs)² of which, 1636098 1564519 1636098 1610587 -1.6 2.9 3.9.1 Housing Finance Companies (HFCs) 323146 330115 323146 314881 -2.6 -4.6 3.9.2 Public Financial Institutions (PFIs) 228678 232074 228678 220806 -3.4 -4.9 3.10 Other Services³ 1182118 989810 1182118 1137607 -3.8 14.9 (1166422) (969994) (1166422) (1116037) (-4.3) (15.1) 4. Personal Loans 5952299 5346354 5952299 5980893 0.5 11.9 (5610478) (4938617) (5610478) (5656449) (0.8) (14.5) 4.1 Consumer Durables 23402 23577 23402 23279 -0.5 -1.3 4.2 Housing 3010477 2741455 3010477 3008941 -0.1 9.8 (2689068) (2358299) (2689068) (2704137) (0.6) (14.7) 4.3 Advances against Fixed Deposits 141101 121868 141101 143518 1.7 17.8 4.4 Advances to Individuals against share & bonds 10080 8472 10080 10488 4.0 23.8 4.5 Credit Card Outstanding 284366 259641 284366 287172 1.0 10.6 4.6 Education 137456 119125 137456 137454 0.0 15.4 4.7 Vehicle Loans 622794 578504 622794 629691 1.1 8.8 4.8 Loan against gold jewellery⁴ 208735 101552 208735 223034 6.9 119.6 4.9 Other Personal Loans 1513889 1392161 1513889 1517316 0.2 9.0 (1493525) (1367743) (1493525) (1497721) (0.3) (9.5) 5. Priority Sector (Memo) (i) Agriculture & Allied Activities⁵ 2287804 2060244 2287804 2233685 -2.4 8.4 (ii) Micro & Small Enterprises⁶ 2240503 1964032 2240503 2313293 3.2 17.8 (iii) Medium Enterprises⁷ 601451 498958 601451 604299 0.5 21.1 (iv) Housing 746651 753576 746651 744228 -0.3 -1.2 (665107) (659843) (665107) (663951) (-0.2) (0.6) (v) Education Loans 62825 61027 62825 62637 -0.3 2.6 (vi) Renewable Energy 10325 5712 10325 11979 16.0 109.7 (vii) Social Infrastructure 1316 2619 1316 1147 -12.9 -56.2 (viii) Export Credit 12361 12539 12361 13086 5.9 4.4 (ix) Others 47900 75152 47900 48689 1.6 -35.2 (x) Weaker Sections including net PSLC- SF/MF 1820904 1605821 1820904 1789687 -1.7 11.5 Notes: (1) Data are provisional. Bank credit, Food credit and Non-food credit data are based on Section-42 return, which covers all scheduled commercial banks (SCBs), while sectoral non-food credit data are based on sector-wise and industry-wise bank credit (SIBC) return, which covers select banks accounting for about 95 per cent of total non-food credit extended by all SCBs, pertaining to the last reporting Friday of the month. (2) Data since July 28, 2023 include the impact of the merger of a non-bank with a bank. (3) Figures in parentheses exclude the impact of the merger. 1 Wholesale trade includes food procurement credit outside the food credit consortium. 2 NBFCs include HFCs, PFIs, Microfinance Institutions (MFIs), NBFCs engaged in gold loan and others. 3 “Other Services” include Mutual Fund (MFs), Banking and Finance other than NBFCs and MFs, and other services which are not indicated elsewhere under services. 4 Since May 2024, a bank has changed the classification of a category of agricultural loan into “Loans against gold jewellery” under retail segment. 5 “Agriculture and Allied Activities” under the priority sector also include priority sector lending certificates (PSLCs). 6 “Micro and Small Enterprises” under the priority sector include credit to micro and small enterprises in industry and services sectors and also include PSLCs. 7 “Medium Enterprises” under the priority sector include credit to medium enterprises in industry and services sectors. RBI Bulletin June 2025 131CURRENT STATISTICS No. 16: Industry-wise Deployment of Gross Bank Credit (₹ Crore) Outstanding as on Growth(%) Financial 2024 2025 Y-o-Y Mar. 21, year so far Industry 2025 Apr. 19 Mar. 21 Apr. 18 2025-26 2025 1 2 3 4 % % 2 Industries (2.1 to 2.19) 3937149 3655455 3937149 3895471 -1.1 6.6 (3925089) (3639138) (3925089) (3883660) (-1.1) (6.7) 2.1 Mining & Quarrying (incl. Coal) 56756 55315 56756 53970 -4.9 -2.4 2.2 Food Processing 219527 210714 219527 224436 2.2 6.5 2.2.1 Sugar 28522 27896 28522 28381 -0.5 1.7 2.2.2 Edible Oils & Vanaspati 20927 20149 20927 21239 1.5 5.4 2.2.3 Tea 5084 5721 5084 4981 -2.0 -12.9 2.2.4 Others 164994 156948 164994 169834 2.9 8.2 2.3 Beverage & Tobacco 35513 31592 35513 34580 -2.6 9.5 2.4 Textiles 277267 253819 277267 275379 -0.7 8.5 2.4.1 Cotton Textiles 107227 97390 107227 103692 -3.3 6.5 2.4.2 Jute Textiles 4288 4266 4288 4333 1.1 1.6 2.4.3 Man-Made Textiles 49091 44282 49091 49321 0.5 11.4 2.4.4 Other Textiles 116661 107882 116661 118032 1.2 9.4 2.5 Leather & Leather Products 12980 12488 12980 13157 1.4 5.4 2.6 Wood & Wood Products 27826 23840 27826 27842 0.1 16.8 2.7 Paper & Paper Products 52848 46270 52848 52465 -0.7 13.4 2.8 Petroleum, Coal Products & Nuclear Fuels 154178 133967 154178 135500 -12.1 1.1 2.9 Chemicals & Chemical Products 267814 251949 267814 267186 -0.2 6.0 2.9.1 Fertiliser 32011 36872 32011 31850 -0.5 -13.6 2.9.2 Drugs & Pharmaceuticals 88738 81941 88738 86357 -2.7 5.4 2.9.3 Petro Chemicals 26892 25666 26892 29823 10.9 16.2 2.9.4 Others 120172 107470 120172 119157 -0.8 10.9 2.10 Rubber, Plastic & their Products 103464 88937 103464 103555 0.1 16.4 2.11 Glass & Glassware 13443 12199 13443 13668 1.7 12.0 2.12 Cement & Cement Products 59752 58089 59752 58452 -2.2 0.6 2.13 Basic Metal & Metal Product 433502 381616 433502 436006 0.6 14.3 2.13.1 Iron & Steel 300156 269936 300156 299924 -0.1 11.1 2.13.2 Other Metal & Metal Product 133345 111680 133345 136083 2.1 21.9 2.14 All Engineering 240135 197017 240135 240016 0.0 21.8 2.14.1 Electronics 52862 44296 52862 52978 0.2 19.6 2.14.2 Others 187272 152722 187272 187038 -0.1 22.5 2.15 Vehicles, Vehicle Parts & Transport Equipment 119057 111469 119057 119583 0.4 7.3 2.16 Gems & Jewellery 85734 83491 85734 90892 6.0 8.9 2.17 Construction 150701 131369 150701 150407 -0.2 14.5 2.18 Infrastructure 1322831 1322295 1322831 1311402 -0.9 -0.8 2.18.1 Power 682953 647359 682953 687776 0.7 6.2 2.18.2 Telecommunications 118940 137366 118940 108302 -8.9 -21.2 2.18.3 Roads 311219 331069 311219 313483 0.7 -5.3 2.18.4 Airports 9156 7443 9156 9293 1.5 24.9 2.18.5 Ports 5916 6342 5916 5467 -7.6 -13.8 2.18.6 Railways 13595 13138 13595 12121 -10.8 -7.7 2.18.7 Other Infrastructure 181052 179580 181052 174959 -3.4 -2.6 2.19 Other Industries 303822 249019 303822 286975 -5.5 15.2 Notes: (1) Data since July 28, 2023 include the impact of the merger of a non-bank with a bank. (2) Figures in parentheses exclude the impact of the merger. 132 RBI Bulletin June 2025CURRENT STATISTICS No. 17: State Co-operative Banks Maintaining Accounts with the Reserve Bank of India (₹ Crore) Last Reporting Friday (in case of March)/Last Friday/ Item Reporting Friday 2024 2025 2023-24 Mar. 29 Jan. 31 Feb. 07 Feb. 21 Feb. 28 Mar. 07 Mar. 21 Mar. 28 1 2 3 4 5 6 7 8 9 Number of Reporting Banks 33 33 34 34 34 34 34 34 34 1 Aggregate Deposits (2.1.1.2+2.2.1.2) 138788.9 138788.9 137422.7 141128.7 141197.5 141021.9 141431.2 142953.8 146871.0 2 Demand and Time Liabilities 2.1 Demand Liabilities 3022 6.7 30226.7 25128.9 25006.3 25232.3 25377.7 26 240.2 2903 3.2 29215 .6 2.1.1 Deposits 2.1.1.1 Inter-Bank 9101.3 9101.3 6389.8 6957.9 6678.7 6336.1 7072.2 8543.2 9022.9 2.1.1.2 Others 15000.4 15000.4 12576.7 12842.5 12977.2 13305.9 13485.0 13597.0 14063.9 2.1.2 Borrowings from Banks 130.0 130.0 789.3 355.0 615.0 537.7 445.0 827.0 700.0 2.1.3 Other Demand Liabilities 5995.0 5995.0 5373.1 4851.0 4961.4 5197.9 5238.0 6066.1 5428.9 2.2 Time Liabilities 198141.8 198141.8 178875.8 181832.3 181707.7 181395.7 182829.0 188026.7 201100.7 2.2.1 Deposits 2.2.1.1 Inter-Bank 72308.4 72308.4 52326.4 51828.6 51761.4 52005.7 53235.4 57013.2 66874.3 2.2.1.2 Others 123788.5 123788.5 124846.0 128286.2 128220.3 127715.9 127946.1 129356.8 132807.1 2.2.2 Borrowings from Banks 673.6 673.6 650.8 650.8 650.3 650.3 650.3 650.3 643.9 2.2.3 Other Time Liabilities 1371.3 1371.3 1052.6 1066.8 1075.8 1023.8 997.2 1006.3 775.4 3 Borrowing from Reserve Bank 0.0 699.8 699.7 699.5 4 Borrowings from a notified bank / Government 95914.5 95914.5 111993.8 113739.2 113412.6 115298.7 116039.2 117531.6 126928.5 4.1 Demand 27317.7 27317.7 44397.3 45530.1 46377.3 46815.1 47552.2 47476.4 53459.8 4.2 Time 68596.8 68596.8 67596.4 68209.1 67035.3 68483.6 68486.9 70055.2 73468.7 5 Cash in Hand and Balances with Reserve Bank 16263.7 16263.7 11244.6 11086.3 11271.6 10776.7 12029.4 12049.8 13390.9 5.1 Cash in Hand 960.0 960.0 777.4 744.8 833.1 854.2 1226.3 961.5 1052.1 5.2 Balance with Reserve Bank 15303.7 15303.7 10467.2 10341.5 10438.5 9922.5 10803.1 11088.4 12338.8 6 Balances with Other Banks in Current Account 2088.1 2088.1 1204.8 1428.6 1100.0 1281.1 1095.8 1355.2 1656.3 7 Investments in Government Securities 77700.5 77700.5 75052.7 75044.6 76597.1 76364.1 75604.6 75941.0 77220.1 8 Money at Call and Short Notice 34355.3 34355.3 12239.3 15510.2 14526.0 16049.2 19365.0 18381.0 26531.1 9 Bank Credit (10.1+11) 135141.9 135141.9 170245.1 171448.7 170308.0 171858.1 171435.7 171861.3 174828.8 10 Advances 10.1 Loans, Cash-Credits and Overdrafts 134936.8 134936.8 170045.3 171246.9 170138.6 171681.7 171259.2 171672.1 174590.4 10.2 Due from Banks 14218 5.2 142185.2 112047.0 112520.9 114341.3 1 16430.1 117 656.1 11850 7.5 124607 .6 11 Bills Purchased and Discounted 205.1 205.1 199.8 201.7 169.4 176.5 176.5 189.2 238.4 RBI Bulletin June 2025 133CURRENT STATISTICS Prices and Production No. 18: Consumer Price Index (Base: 2012=100) Group/Sub group 2024-25 Rural Urban Combined Rural Urban Combined May 24 Apr. 25 May 25 (P) May 24 Apr. 25 May 25 (P) May.24 Apr.25 May.25 (P) 1 2 3 4 5 6 7 8 9 10 11 12 1 Food and beverages 198.6 205.3 201.1 190.6 193.4 193.2 197.6 200.6 201.0 193.2 196.0 196.1 1.1 Cereals and products 195.0 193.7 194.6 188.7 199.0 197.8 189.0 198.6 197.8 188.8 198.9 197.8 1.2 Meat and fish 222.3 231.9 225.7 226.5 222.6 225.6 236.3 231.4 235.2 229.9 225.7 229.0 1.3 Egg 192.8 197.5 194.6 184.9 181.0 185.1 189.1 186.6 191.8 186.5 183.2 187.7 1.4 Milk and products 186.3 187.0 186.6 184.1 188.4 189.3 184.3 189.3 191.1 184.2 188.7 190.0 1.5 Oils and fats 175.4 165.5 171.8 160.5 190.6 191.6 155.2 178.2 179.2 158.6 186.0 187.0 1.6 Fruits 188.3 194.2 191.0 180.4 209.6 204.5 187.4 213.2 210.0 183.7 211.3 207.1 1.7 Vegetables 222.1 269.6 238.2 190.7 164.7 164.0 233.2 200.5 202.2 205.1 176.8 177.0 1.8 Pulses and products 208.0 213.5 209.8 203.7 190.3 187.1 209.7 195.3 192.2 205.7 192.0 188.8 1.9 Sugar and confectionery 130.4 132.6 131.2 128.9 133.8 134.4 131.3 135.8 136.2 129.7 134.5 135.0 1.10 Spices 228.5 223.9 227.0 229.2 222.2 221.6 223.6 220.1 219.6 227.3 221.5 220.9 1.11 Non-alcoholic beverages 185.2 173.9 180.5 182.4 189.6 190.2 170.8 179.0 179.5 177.6 185.2 185.7 1.12 Prepared meals, snacks, sweets 199.4 209.7 204.2 196.6 203.6 204.0 205.5 215.4 215.9 200.7 209.1 209.5 2 Pan, tobacco and intoxicants 207.3 212.6 208.7 205.5 209.6 210.4 211.5 214.3 216.7 207.1 210.9 212.1 3 Clothing and footwear 197.9 186.7 193.5 195.7 200.3 200.7 184.7 189.6 189.9 191.3 196.1 196.4 3.1 Clothing 198.8 188.8 194.9 196.5 201.2 201.7 186.7 191.8 192.2 192.6 197.5 198.0 3.2 Footwear 192.7 174.7 185.2 191.1 194.5 194.8 173.0 177.1 177.4 183.6 187.3 187.6 4 Housing -- 181.5 181.5 -- -- -- 180.1 185.4 185.8 180.1 185.4 185.8 5 Fuel and light 181.2 169.7 176.9 180.3 183.3 184.8 169.3 173.3 174.9 176.1 179.5 181.0 6 Miscellaneous 189.3 180.7 185.1 185.9 194.8 195.6 177.3 185.6 186.0 181.7 190.3 190.9 6.1 Household goods and services 185.7 177.1 181.6 183.9 187.6 187.7 174.8 179.8 178.2 179.6 183.9 183.2 6.2 Health 198.4 193.2 196.4 195.7 203.1 203.9 190.0 197.8 198.6 193.5 201.1 201.9 6.3 Transport and communication 175.5 164.8 169.9 171.8 178.3 178.7 161.5 167.1 167.4 166.4 172.4 172.8 6.4 Recreation and amusement 180.1 175.5 177.5 178.5 181.6 181.8 173.3 178.1 178.4 175.6 179.6 179.9 6.5 Education 190.8 186.2 188.1 186.9 194.1 194.2 182.4 189.5 190.2 184.3 191.4 191.9 6.6 Personal care and effects 204.3 206.2 205.1 198.6 222.2 225.4 200.6 224.8 227.5 199.4 223.3 226.3 General Index (All Groups) 194.9 190.0 192.6 189.4 194.0 194.3 185.7 190.9 191.4 187.7 192.6 193.0 Source: National Statistical Office, Ministry of Statistics and Programme Implementation, Government of India. P: Provisional No. 19: Other Consumer Price Indices Item Base Year Linking 2024-25 2024 2025 Factor Apr. Mar. Apr. 1 2 3 4 5 6 1 Consumer Price Index for Industrial Workers 2016 2.88 142.6 139.4 143.0 143.5 2 Consumer Price Index for Agricultural Labourers 1986-87 5.89 1299 1263 1306 1307 3 Consumer Price Index for Rural Labourers 1986-87 - 1311 1275 1319 1320 Source: Labour Bureau, Ministry of Labour and Employment, Government of India. No. 20: Monthly Average Price of Gold and Silver in Mumbai Item 2024-25 2024 2025 Apr. Mar. Apr. 1 2 3 4 1 Standard Gold (₹ per 10 grams) 75842 71353 86890 93091 2 Silver (₹ per kilogram) 89131 80778 97868 95309 Source: India Bullion & Jewellers Association Ltd., Mumbai for Gold and Silver prices in Mumbai. 134 RBI Bulletin June 2025CURRENT STATISTICS No. 21: Wholesale Price Index (Base: 2011-12 = 100) Commodities Weight 2024-25 2024 2025 May Mar. Apr. (P) May (P) 1 2 3 4 5 6 1 ALL COMMODITIES 100.000 154.9 153.5 154.8 154.2 154.1 1.1 PRIMARY ARTICLES 22.618 192.5 188.1 185.5 184.4 184.3 1.1.1 FOOD ARTICLES 15.256 205.3 199.3 194.8 195.1 196.2 1.1.1.1 Food Grains (Cereals+Pulses) 3.462 210.1 204.1 210.0 206.5 204.0 1.1.1.2 Fruits & Vegetables 3.475 241.4 220.8 197.4 200.3 202.7 1.1.1.3 Milk 4.440 185.8 184.0 187.2 186.4 188.9 1.1.1.4 Eggs, Meat & Fish 2.402 173.4 178.4 170.4 172.1 176.6 1.1.1.5 Condiments & Spices 0.529 232.7 236.9 200.8 204.7 200.8 1.1.1.6 Other Food Articles 0.948 213.6 207.7 224.0 227.9 224.9 1.1.2 NON-FOOD ARTICLES 4.119 161.7 156.5 162.6 159.9 158.9 1.1.2.1 Fibres 0.839 161.4 159.9 162.1 162.4 164.9 1.1.2.2 Oil Seeds 1.115 181.5 179.2 179.3 182.9 184.2 1.1.2.3 Other non-food Articles 1.960 138.7 131.4 141.7 139.5 137.8 1.1.2.4 Floriculture 0.204 277.4 260.7 274.6 219.2 198.5 1.1.3 MINERALS 0.833 229.0 227.1 245.5 245.7 228.1 1.1.3.1 Metallic Minerals 0.648 219.2 219.3 238.5 238.5 218.8 1.1.3.2 Other Minerals 0.185 263.4 254.5 270.1 270.7 260.5 1.1.4 CRUDE PETROLEUM & NATURAL GAS 2.410 151.3 156.9 145.1 137.4 137.4 1.2 FUEL & POWER 13.152 150.0 150.1 152.1 148.1 146.7 1.2.1 COAL 2.138 135.6 135.8 135.6 135.9 137.0 1.2.1.1 Coking Coal 0.647 143.4 143.4 143.4 143.5 146.4 1.2.1.2 Non-Coking Coal 1.401 125.8 125.8 125.8 126.2 126.6 1.2.1.3 Lignite 0.090 232.4 236.0 231.2 231.2 231.2 1.2.2 MINERAL OILS 7.950 156.2 159.5 156.9 150.6 147.5 1.2.3 ELECTRICITY 3.064 144.1 135.7 151.3 150.4 151.6 1.3 MANUFACTURED PRODUCTS 64.231 142.6 142.0 144.6 144.9 144.9 1.3.1 MANUFACTURE OF FOOD PRODUCTS 9.122 172.0 164.5 180.1 179.6 178.4 1.3.1.1 Processing and Preserving of meat 0.134 155.7 155.8 159.9 157.0 157.3 1.3.1.2 Processing and Preserving of fish, Crustaceans, Molluscs and products thereof 0.204 144.9 143.2 144.4 145.6 146.9 1.3.1.3 Processing and Preserving of fruit and Vegetables 0.138 132.6 131.8 134.0 137.2 136.0 1.3.1.4 Vegetable and Animal oils and Fats 2.643 168.5 147.6 191.4 190.2 186.7 1.3.1.5 Dairy products 1.165 180.8 179.4 183.5 183.9 183.5 1.3.1.6 Grain mill products 2.010 186.9 182.8 188.6 187.3 186.4 1.3.1.7 Starches and Starch products 0.110 167.0 162.9 160.7 159.8 157.6 1.3.1.8 Bakery products 0.215 170.5 165.7 176.0 176.3 175.9 1.3.1.9 Sugar, Molasses & honey 1.163 139.1 139.6 143.4 143.7 143.9 1.3.1.10 Cocoa, Chocolate and Sugar confectionery 0.175 160.6 149.9 174.5 174.5 176.4 1.3.1.11 Macaroni, Noodles, Couscous and Similar farinaceous products 0.026 156.7 147.0 171.5 162.4 158.7 1.3.1.12 Tea & Coffee products 0.371 190.7 193.9 191.7 189.4 190.2 1.3.1.13 Processed condiments & salt 0.163 192.6 192.3 189.9 189.7 189.5 1.3.1.14 Processed ready to eat food 0.024 152.7 149.1 155.4 156.4 156.5 1.3.1.15 Health supplements 0.225 185.1 179.2 186.5 188.8 187.2 1.3.1.16 Prepared animal feeds 0.356 204.1 204.8 195.3 197.1 198.8 1.3.2 MANUFACTURE OF BEVERAGES 0.909 134.1 133.2 134.8 135.4 135.6 1.3.2.1 Wines & spirits 0.408 136.0 134.0 137.6 138.3 138.8 1.3.2.2 Malt liquors and Malt 0.225 138.7 138.3 139.6 139.8 139.6 1.3.2.3 Soft drinks; Production of mineral waters and Other bottled waters 0.275 127.5 127.8 126.7 127.6 127.6 1.3.3 MANUFACTURE OF TOBACCO PRODUCTS 0.514 177.8 174.3 181.9 181.0 182.4 1.3.3.1 Tobacco products 0.514 177.8 174.3 181.9 181.0 182.4 RBI Bulletin June 2025 135CURRENT STATISTICS No. 21: Wholesale Price Index (Contd.) (Base: 2011-12 = 100) Commodities Weight 2024-25 2024 2025 May Mar. Apr.(P) May(P) 1 2 3 4 5 6 1.3.4 MANUFACTURE OF TEXTILES 4.881 136.3 135.7 136.5 136.4 136.6 1.3.4.1 Preparation and Spinning of textile fibres 2.582 121.4 122.0 121.0 120.9 120.5 1.3.4.2 Weaving & Finishing of textiles 1.509 158.3 156.5 159.1 158.9 160.3 1.3.4.3 Knitted and Crocheted fabrics 0.193 124.0 123.2 124.0 124.4 124.8 1.3.4.4 Made-up textile articles, Except apparel 0.299 160.4 159.2 161.9 161.3 161.5 1.3.4.5 Cordage, Rope, Twine and Netting 0.098 142.7 138.9 149.7 148.2 150.7 1.3.4.6 Other textiles 0.201 134.9 132.1 135.2 135.6 133.1 1.3.5 MANUFACTURE OF WEARING APPAREL 0.814 153.4 152.0 154.5 154.1 155.0 1.3.5.1 Manufacture of Wearing Apparel (woven), Except fur Apparel 0.593 150.9 150.1 152.4 152.1 153.2 1.3.5.2 Knitted and Crocheted apparel 0.221 160.1 157.2 160.1 159.6 159.7 1.3.6 MANUFACTURE OF LEATHER AND RELATED PRODUCTS 0.535 125.3 124.0 125.4 126.6 127.0 1.3.6.1 Tanning and Dressing of leather; Dressing and Dyeing of fur 0.142 106.1 104.2 104.0 106.6 110.9 1.3.6.2 Luggage, HandbAgs, Saddlery and Harness 0.075 142.5 141.0 142.9 142.6 141.0 1.3.6.3 Footwear 0.318 129.7 128.8 130.9 131.7 130.9 1.3.7 MANUFACTURE OF WOOD AND PRODUCTS OF WOOD AND CORK 0.772 149.2 149.5 150.0 150.3 150.2 1.3.7.1 Saw milling and Planing of wood 0.124 141.1 139.5 143.2 143.2 143.0 1.3.7.2 Veneer sheets; Manufacture of plywood, Laminboard, Particle board and Other panels and Boards 0.493 148.6 149.5 149.4 149.6 149.4 1.3.7.3 Builder's carpentry and Joinery 0.036 215.3 215.3 215.1 216.7 215.4 1.3.7.4 Wooden containers 0.119 140.6 140.3 140.0 140.3 141.3 1.3.8 MANUFACTURE OF PAPER AND PAPER PRODUCTS 1.113 139.2 138.1 141.0 140.8 140.4 1.3.8.1 Pulp, Paper and Paperboard 0.493 144.6 144.3 145.6 145.5 144.4 1.3.8.2 Corrugated paper and Paperboard and Containers of paper and Paperboard 0.314 147.3 144.4 150.9 151.3 151.2 1.3.8.3 Other articles of paper and Paperboard 0.306 122.4 121.6 123.5 122.2 122.8 1.3.9 PRINTING AND REPRODUCTION OF RECORDED MEDIA 0.676 187.3 185.6 190.6 189.8 189.8 1.3.9.1 Printing 0.676 187.3 185.6 190.6 189.8 189.8 1.3.10 MANUFACTURE OF CHEMICALS AND CHEMICAL PRODUCTS 6.465 136.5 135.8 136.9 137.4 137.2 1.3.10.1 Basic chemicals 1.433 138.6 137.5 141.5 142.4 142.4 1.3.10.2 Fertilizers and Nitrogen compounds 1.485 143.1 143.3 142.3 142.9 143.3 1.3.10.3 Plastic and Synthetic rubber in primary form 1.001 133.6 131.2 134.1 135.0 133.5 1.3.10.4 Pesticides and Other agrochemical products 0.454 128.8 127.8 130.0 130.2 130.2 1.3.10.5 Paints, Varnishes and Similar coatings, Printing ink and Mastics 0.491 139.5 140.4 138.2 138.5 137.5 1.3.10.6 Soap and Detergents, Cleaning and Polishing preparations, Perfumes and Toilet preparations 0.612 139.7 138.7 141.1 141.9 142.0 1.3.10.7 Other chemical products 0.692 135.4 135.0 133.4 133.9 133.9 1.3.10.8 Man-made fibres 0.296 104.9 104.9 104.3 102.4 101.3 1.3.11 MANUFACTURE OF PHARMACEUTICALS, MEDICINAL CHEMICAL AND BOTANICAL PRODUCTS 1.993 144.3 144.0 144.8 144.9 145.5 1.3.11.1 Pharmaceuticals, Medicinal chemical and Botanical products 1.993 144.3 144.0 144.8 144.9 145.5 1.3.12 MANUFACTURE OF RUBBER AND PLASTICS PRODUCTS 2.299 129.0 128.3 129.9 130.2 129.5 1.3.12.1 Rubber Tyres and Tubes; Retreading and Rebuilding of Rubber Tyres 0.609 115.6 113.4 117.0 117.1 116.1 1.3.12.2 Other Rubber Products 0.272 112.1 109.3 113.5 113.7 113.6 1.3.12.3 Plastics products 1.418 138.1 138.3 138.6 139.0 138.2 1.3.13 MANUFACTURE OF OTHER NON-METALLIC MINERAL PRODUCTS 3.202 131.5 132.3 132.4 132.7 133.2 1.3.13.1 Glass and Glass products 0.295 163.2 163.8 162.8 163.6 163.9 1.3.13.2 Refractory products 0.223 121.6 119.1 126.0 122.5 123.1 1.3.13.3 Clay Building Materials 0.121 124.4 120.2 133.5 130.5 133.5 1.3.13.4 Other Porcelain and Ceramic Products 0.222 124.6 124.8 124.7 124.9 125.9 1.3.13.5 Cement, Lime and Plaster 1.645 130.4 132.8 131.0 131.7 132.1 136 RBI Bulletin June 2025CURRENT STATISTICS No. 21: Wholesale Price Index (Contd.) (Base: 2011-12 = 100) Commodities Weight 2024-25 2024 2025 May Mar. Apr.(P) May(P) 1 2 3 4 5 6 1.3.13.6 Articles of Concrete, Cement and Plaster 0.292 139.2 139.3 138.9 140.7 140.6 1.3.13.7 Cutting, Shaping and Finishing of Stone 0.234 134.4 131.2 136.8 137.3 137.8 1.3.13.8 Other Non-Metallic Mineral Products 0.169 95.2 97.2 92.9 94.2 94.2 1.3.14 MANUFACTURE OF BASIC METALS 9.646 139.7 144.7 139.5 140.5 140.2 1.3.14.1 Inputs into steel making 1.411 133.6 143.5 131.9 133.7 132.9 1.3.14.2 Metallic Iron 0.653 141.8 154.6 136.3 136.5 134.5 1.3.14.3 Mild Steel - Semi Finished Steel 1.274 117.9 122.0 118.3 118.7 118.7 1.3.14.4 Mild Steel -Long Products 1.081 140.4 144.5 140.0 140.8 138.6 1.3.14.5 Mild Steel - Flat products 1.144 134.2 140.7 130.3 134.3 135.4 1.3.14.6 Alloy steel other than Stainless Steel- Shapes 0.067 135.4 142.2 133.6 135.1 136.2 1.3.14.7 Stainless Steel - Semi Finished 0.924 131.1 140.5 130.9 132.8 137.4 1.3.14.8 Pipes & tubes 0.205 164.7 166.7 164.4 165.2 166.4 1.3.14.9 Non-ferrous metals incl. precious metals 1.693 157.4 157.4 161.8 160.8 160.1 1.3.14.10 Castings 0.925 144.9 144.1 146.2 146.4 143.1 1.3.14.11 Forgings of steel 0.271 172.2 173.1 174.2 174.3 176.6 1.3.15 MANUFACTURE OF FABRICATED METAL PRODUCTS, EXCEPT MACHINERY AND EQUIPMENT 3.155 136.0 136.4 136.4 137.1 137.4 1.3.15.1 Structural Metal Products 1.031 130.8 131.1 132.1 132.7 131.5 1.3.15.2 Tanks, Reservoirs and Containers of Metal 0.660 149.5 153.3 148.3 152.4 153.4 1.3.15.3 Steam generators, Except Central Heating Hot Water Boilers 0.145 109.8 108.0 110.8 110.8 110.6 1.3.15.4 Forging, Pressing, Stamping and Roll-Forming of Metal; Powder Metallurgy 0.383 138.0 133.9 138.8 135.9 135.8 1.3.15.5 Cutlery, Hand Tools and General Hardware 0.208 102.0 102.0 102.4 102.5 103.6 1.3.15.6 Other Fabricated Metal Products 0.728 144.9 145.5 145.2 145.2 147.2 1.3.16 MANUFACTURE OF COMPUTER, ELECTRONIC AND OPTICAL PRODUCTS 2.009 121.5 122.2 121.2 121.5 122.0 1.3.16.1 Electronic Components 0.402 117.9 117.9 119.4 119.0 120.4 1.3.16.2 Computers and Peripheral Equipment 0.336 134.2 135.3 131.8 131.8 131.4 1.3.16.3 Communication Equipment 0.310 146.0 146.3 146.6 146.6 146.8 1.3.16.4 Consumer Electronics 0.641 101.1 103.3 99.4 100.4 100.9 1.3.16.5 Measuring, Testing, Navigating and Control equipment 0.181 119.9 119.8 121.9 121.9 121.9 1.3.16.6 Watches and Clocks 0.076 167.9 162.7 173.1 172.2 174.5 1.3.16.7 Irradiation, Electromedical and Electrotherapeutic equipment 0.055 114.4 113.5 110.6 111.3 111.7 1.3.16.8 Optical instruments and Photographic equipment 0.008 107.4 105.9 107.5 107.5 111.8 1.3.17 MANUFACTURE OF ELECTRICAL EQUIPMENT 2.930 133.7 133.4 134.5 134.7 134.4 1.3.17.1 Electric motors, Generators, Transformers and Electricity distribution and Control apparatus 1.298 132.3 131.7 133.9 133.6 132.8 1.3.17.2 Batteries and Accumulators 0.236 141.3 140.5 142.1 143.1 144.4 1.3.17.3 Fibre optic cables for data transmission or live transmission of images 0.133 118.6 119.6 113.3 113.7 114.8 1.3.17.4 Other electronic and Electric wires and Cables 0.428 154.4 154.6 157.3 157.8 158.0 1.3.17.5 Wiring devices, Electric lighting & display equipment 0.263 118.4 118.9 117.8 118.4 117.8 1.3.17.6 Domestic appliances 0.366 131.8 131.9 131.3 131.2 130.0 1.3.17.7 Other electrical equipment 0.206 123.4 122.4 123.5 125.0 125.3 1.3.18 MANUFACTURE OF MACHINERY AND EQUIPMENT 4.789 130.8 130.7 131.7 131.9 131.8 1.3.18.1 Engines and Turbines, Except aircraft, Vehicle and Two wheeler engines 0.638 132.8 132.3 132.7 134.1 134.3 1.3.18.2 Fluid power equipment 0.162 134.5 133.4 135.7 135.2 134.6 1.3.18.3 Other pumps, Compressors, Taps and Valves 0.552 118.5 117.9 118.9 118.9 119.5 1.3.18.4 Bearings, Gears, Gearing and Driving elements 0.340 128.5 128.2 131.7 130.5 128.9 1.3.18.5 Ovens, Furnaces and Furnace burners 0.008 86.6 85.2 86.9 87.1 88.1 1.3.18.6 Lifting and Handling equipment 0.285 130.0 129.8 130.6 130.6 131.1 RBI Bulletin June 2025 137CURRENT STATISTICS No. 21: Wholesale Price Index (Concld.) (Base: 2011-12 = 100) Commodities Weight 2024-25 2024 2025 May Mar. Apr.(P) May(P) 1 2 3 4 5 6 1.3.18.7 Office machinery and Equipment 0.006 130.2 130.2 130.2 130.2 130.2 1.3.18.8 Other general-purpose machinery 0.437 145.3 147.8 142.7 143.5 144.8 1.3.18.9 Agricultural and Forestry machinery 0.833 145.5 145.2 146.7 146.8 146.8 1.3.18.10 Metal-forming machinery and Machine tools 0.224 123.2 122.4 126.2 126.2 126.0 1.3.18.11 Machinery for mining, Quarrying and Construction 0.371 89.8 89.7 91.6 92.2 92.4 1.3.18.12 Machinery for food, Beverage and Tobacco processing 0.228 126.1 125.3 127.0 127.2 126.3 1.3.18.13 Machinery for textile, Apparel and Leather production 0.192 141.4 139.2 148.8 148.7 139.0 1.3.18.14 Other special-purpose machinery 0.468 144.9 146.1 144.7 144.5 145.8 1.3.18.15 Renewable electricity generating equipment 0.046 69.2 70.0 69.3 69.1 69.2 1.3.19 MANUFACTURE OF MOTOR VEHICLES, TRAILERS AND SEMI-TRAILERS 4.969 129.9 129.8 130.3 130.5 130.5 1.3.19.1 Motor vehicles 2.600 130.6 130.6 131.2 131.3 131.0 1.3.19.2 Parts and Accessories for motor vehicles 2.368 129.1 128.9 129.4 129.6 129.9 1.3.20 MANUFACTURE OF OTHER TRANSPORT EQUIPMENT 1.648 145.2 143.9 148.4 149.6 149.6 1.3.20.1 Building of ships and Floating structures 0.117 180.5 177.9 188.4 190.6 190.7 1.3.20.2 Railway locomotives and Rolling stock 0.110 108.9 108.3 109.5 109.5 109.7 1.3.20.3 Motor cycles 1.302 146.0 144.6 149.3 150.5 150.3 1.3.20.4 Bicycles and Invalid carriages 0.117 134.9 135.9 135.4 136.1 136.7 1.3.20.5 Other transport equipment 0.002 163.2 162.5 165.8 165.1 165.9 1.3.21 MANUFACTURE OF FURNITURE 0.727 160.3 158.7 163.2 163.5 163.4 1.3.21.1 Furniture 0.727 160.3 158.7 163.2 163.5 163.4 1.3.22 OTHER MANUFACTURING 1.064 183.8 178.5 204.2 204.2 219.3 1.3.22.1 Jewellery and Related articles 0.996 185.4 179.7 207.2 207.1 223.2 1.3.22.2 Musical instruments 0.001 201.9 211.6 201.4 201.4 202.1 1.3.22.3 Sports goods 0.012 164.9 160.1 168.1 170.4 171.0 1.3.22.4 Games and Toys 0.005 163.1 161.3 164.5 164.3 164.3 1.3.22.5 Medical and Dental instruments and Supplies 0.049 158.6 159.1 158.6 158.6 158.6 2 FOOD INDEX 24.378 192.9 186.3 189.3 189.3 189.5 Source: Office of the Economic Adviser, Ministry of Commerce and Industry, Government of India. 138 RBI Bulletin June 2025CURRENT STATISTICS No. 22: Index of Industrial Production (Base:2011-12=100) Industry Weight 2023-24 2024-25 March April 2024 2025 2024 2025 1 2 3 4 5 6 7 General Index 100.00 146.7 152.6 160.0 166.3 148.0 152.0 1 Sectoral Classification 1.1 Mining 14.37 128.9 132.8 156.2 158.1 130.9 130.6 1.2 Manufacturing 77.63 144.7 150.6 156.2 162.4 144.6 149.5 1.3 Electricity 7.99 198.3 208.6 204.2 219.5 212.0 214.4 2 Use-Based Classification 2.1 Primary Goods 34.05 147.7 153.5 163.1 169.5 152.2 151.6 2.2 Capital Goods 8.22 106.6 112.6 131.6 136.3 95.0 114.3 2.3 Intermediate Goods 17.22 157.3 164.0 169.2 175.6 157.8 164.2 2.4 Infrastructure/ Construction Goods 12.34 176.3 188.2 195.2 214.6 184.2 191.6 2.5 Consumer Durables 12.84 118.6 128.0 129.9 138.8 119.5 127.2 2.6 Consumer Non-Durables 15.33 153.7 151.4 155.2 149.0 150.9 148.4 Source : Central Statistics Office, Ministry of Statistics and Programme Implementation, Government of India. Government Accounts and Treasury Bills No. 23: Union Government Accounts at a Glance (₹ Crore) 2025-26 2024-25 April 2025 Provisional Accounts as Budget Percent to per cent to Estimates Actuals Budget Provisional Revised Revised Estimates Accounts Estimates Estimates Item 1 2 3 4 5 6 1 Revenue Receipts 3420409 256829 7.5 3036429 3087960 98.3 1.1 Tax Revenue (Net) 2837409 189669 6.7 2498885 2556960 97.7 1.2 Non-Tax Revenue 583000 67160 11.5 537544 531000 101.2 2 Non Debt Capital Receipt 76000 22459 29.6 41818 59000 70.9 2.1 Recovery of Loans 29000 1048 3.6 24616 26000 94.7 2.2 Other Receipts 47000 21411 45.6 17202 33000 52.1 3 Total Receipts (excluding borrowings) (1+2) 3496409 279288 8.0 3078247 3146960 97.8 4 Revenue Expenditure of which : 3944255 305830 7.8 3603510 3698058 97.4 4.1 Interest Payments 1276338 93460 7.3 1116343 1137940 98.1 5 Capital Expenditure 1121090 159790 14.3 1052007 1018429 103.3 6 Total Expenditure (4+5) 5065345 465620 9.2 4655517 4716487 98.7 7 Revenue Deficit (4-1) 523846 49001 9.4 567081 610098 92.9 8 Fiscal Deficit (6-3) 1568936 186332 11.9 1577270 1569527 100.5 9 Gross Primary Deficit (8-4.1) 292598 92872 31.7 460927 431587 106.8 Source: Controller General of Accounts (CGA), Ministry of Finance, Government of India and Union Budget 2025-26. RBI Bulletin June 2025 139CURRENT STATISTICS No. 24: Treasury Bills – Ownership Pattern (₹ Crore) 2024-25 2024 2025 Item Apr. 26 Mar. 21 Mar. 28 Apr. 04 Apr. 11 Apr. 18 Apr. 25 1 2 3 4 5 6 7 8 1 91-day 1.1 Banks 26554 8989 13884 26554 17184 14441 12637 13756 1.2 Primary Dealers 25258 22711 20137 25258 24563 25236 23228 23981 1.3 State Governments 40315 31670 53128 40315 40918 35918 24417 43217 1.4 Others 115688 114700 126479 115688 122754 122623 123435 118563 2 182-day 2.1 Banks 44887 77964 43990 44887 40572 46806 46504 43713 2.2 Primary Dealers 62218 78906 52239 62218 64068 61865 62287 66918 2.3 State Governments 11078 7406 10928 11078 10340 10340 7632 8932 2.4 Others 104994 114134 103871 104994 105660 100629 99510 96669 3 364-day 3.1 Banks 72304 91933 68305 72304 63863 69748 69847 67854 3.2 Primary Dealers 86939 160059 94604 86939 90745 87217 86096 85280 3.3 State Governments 37389 37488 37132 37389 37311 45060 45432 45879 3.4 Others 162757 164008 161091 162757 164393 159036 157057 156866 4 14-day Intermediate 4.1 Banks 4.2 Primary Dealers 4.3 State Governments 273670 223837 326396 273670 140737 186371 199559 187551 4.4 Others 572 537 378 572 1319 551 461 1005 Total Treasury Bills (Excluding 14 day 790381 909968 785787 790381 782369 778918 758082 771628 Intermediate T Bills) # # 14D intermediate T-Bills are non-marketable unlike 91D, 182D and 364D T-Bills. These bills are ‘intermediate’ by nature as these are liquidated to replenish shortfall in the daily minimum cash balances of State Governments. Note: Primary Dealers (PDs) include banks undertaking PD business. No. 25: Auctions of Treasury Bills (Amount in ₹ Crore) Date of Notified Bids Received Bids Accepted Total Cut- Implicit Yield Auction Amount Total Face Value Total Face Value Issue off at Cut-off Price Number Number (6+7) Price (per cent) Competitive Non- Competitive Non- ( ₹ ) Competitive Competitive 1 2 3 4 5 6 7 8 9 10 91-day Treasury Bills 2025-26 Apr. 02 9000 94 22500 615 41 8989 615 9604 98.45 6.3017 Apr. 09 9000 106 27662 2042 38 8958 2042 11000 98.52 6.0300 Apr. 16 9000 91 21436 1915 48 8985 1915 10900 98.54 5.9354 Apr. 23 9000 94 28246 26227 43 8973 26227 35200 98.55 5.9048 Apr. 30 9000 75 21082 27123 32 8977 27123 36100 98.55 5.9036 182-day Treasury Bills 2025-26 Apr. 02 5000 83 28267 5 3 4995 5 5000 96.96 6.2930 Apr. 09 5000 89 23035 19 5 4981 19 5000 97.05 6.0984 Apr. 16 5000 95 19505 20 33 4980 20 5000 97.09 6.0198 Apr. 23 5000 88 18537 3814 28 4986 3814 8800 97.12 5.9514 Apr. 30 5000 82 19717 1723 18 4977 1723 6700 97.13 5.9258 364-day Treasury Bills 2025-26 Apr. 02 5000 97 36075 141 7 4994 141 5135 94.09 6.2973 Apr. 09 5000 124 42472 7773 6 4980 7773 12753 94.28 6.0880 Apr. 16 5000 102 23520 458 29 4989 458 5448 94.34 6.0154 Apr. 23 5000 106 24947 638 31 4968 638 5605 94.40 5.9500 Apr. 30 5000 92 23359 187 30 4978 187 5165 94.43 5.9146 140 RBI Bulletin June 2025CURRENT STATISTICS Financial Markets No. 26: Daily Call Money Rates (Per cent per annum) Range of Rates Weighted Average Rates As on Borrowings/ Lendings Borrowings/ Lendings 1 2 April 02 ,2025 5.15-6.35 6.19 April 03 ,2025 5.00-6.10 5.99 April 04 ,2025 5.00-6.40 6.08 April 05 ,2025 5.25-6.35 5.77 April 07 ,2025 5.10-6.35 6.16 April 08 ,2025 5.15-6.25 6.15 April 09 ,2025 5.00-6.10 5.91 April 11 ,2025 5.00-6.00 5.79 April 15 ,2025 5.00-5.95 5.84 April 16 ,2025 4.95-5.95 5.85 April 17 ,2025 4.95-5.95 5.85 April 19 ,2025 5.30-5.95 5.50 April 21 ,2025 4.95-6.05 5.86 April 22 ,2025 5.00-6.15 5.87 April 23 ,2025 5.00-6.05 5.91 April 24 ,2025 4.95-5.96 5.85 April 25 ,2025 4.95-5.95 5.86 April 28 ,2025 4.95-6.05 5.87 April 29 ,2025 4.95-6.10 5.90 April 30 ,2025 5.00-6.05 5.94 May 02 ,2025 4.95-6.00 5.86 May 03 ,2025 5.25-5.95 5.55 May 05 ,2025 4.95-6.16 5.89 May 06 ,2025 4.95-5.95 5.84 May 07 ,2025 4.90-5.95 5.83 May 08 ,2025 4.90-5.90 5.82 May 09 ,2025 4.90-6.00 5.84 May 13 ,2025 4.90-5.90 5.83 May 14 ,2025 4.90-5.90 5.84 May 15 ,2025 4.90-5.90 5.83 Note: Includes Notice Money. RBI Bulletin June 2025 141CURRENT STATISTICS No. 27: Certificates of Deposit 2024 2025 2025 Item Apr. 19 Mar. 7 Mar. 21 Apr. 4 Apr. 18 May. 2 May. 16 May. 30 1 2 3 4 5 6 7 8 1 Amount Outstanding (₹ Crore) 372841.80 511207.89 532971.66 522896.64 518759.57 512999.59 511818.07 513762.66 1.1 Issued during the fortnight (₹ Crore) 16991.88 70936.37 117053.02 32045.52 7213.32 9185.58 48202.31 38388.15 2 Rate of Interest (per cent) 6.95-7.83 7.02-8.02 6.98-8.05 6.45-8.05 6.43-7.37 6.35-7.22 6.21-7.24 6.01-7.37 No. 28: Commercial Paper Item 2024 2025 2025 Apr. 30 Mar. 15 Mar. 31 Apr. 15 Apr. 30 May 15 May 31 1 2 3 4 5 6 7 1 Amount Outstanding (₹ Crore) 411533.60 457051.30 442892.70 521558.10 545586.95 541591.10 553874.25 1.1 Reported during the fortnight (₹ Crore) 60407.45 107624.20 77133.85 91006.40 72418.90 48973.55 81053.80 2 Rate of Interest (per cent) 6.89-12.59 6.67-11.78 7.00-14.46 6.31-11.65 6.26-13.00 6.44-10.14 5.97-12.23 No. 29: Average Daily Turnover in Select Financial Markets (₹ Crore) Item 2024-25 2024 2025 Apr. 26 Mar. 21 Mar. 28 Apr. 4 Apr. 11 Apr. 18 Apr. 25 1 2 3 4 5 6 7 8 1 Call Money 18990 18120 30499 27595 17640 26502 23766 28038 2 Notice Money 2506 655 442 4915 7789 431 9941 181 3 Term Money 941 969 1271 1167 1818 1151 1233 1900 4 Triparty Repo 692068 628164 644998 818746 653565 679080 827215 706111 5 Market Repo 578912 570483 579795 671533 389018 528545 810602 626465 6 Repo in Corporate Bond 5212 3178 8851 6386 5897 6319 6241 6915 7 Forex (US $ million) 131877 120418 149709 183528 159811 155293 150795 136963 8 Govt. of India Dated Securities 56065 73593 115324 58942 164906 240487 169877 201467 9 State Govt. Securities 3971 4343 14316 7083 6292 11254 9104 11158 10 Treasury Bills 10.1 91-Day 2514 4848 9185 7631 14363 5321 6693 5042 10.2 182-Day 2218 6214 3835 1689 7887 7970 4092 3911 10.3 364-Day 1854 4593 3974 3012 7320 9779 6627 4433 10.4 Cash Management Bills 0 0 0 0 0 0 0 11 Total Govt. Securities (8+9+10) 66622 93592 146635 78357 200768 274810 196393 226012 11.1 RBI 1715 16 10497 9793 6901 5032 427 12079 142 RBI Bulletin June 2025CURRENT STATISTICS No. 30: New Capital Issues by Non-Government Public Limited Companies (Amount in ₹ Crore) 2024-25 2024-25 (Apr.) 2025-26 (Apr.) * Apr. 2024 Apr. 2025 * Security & Type of Issue No. of Amount No. of Amount No. of Amount No. of Amount No. of Amount Issues Issues Issues Issues Issues 1 2 3 4 5 6 7 8 9 10 1 Equity Shares 464 210190 35 25371 14 435 35 25371 14 435 1.1 Public 322 190478 27 23727 8 255 27 23727 8 255 1.2 Rights 142 19712 8 1643 6 180 8 1643 6 180 2 Public Issue of 43 8149 4 687 5 777 4 687 5 777 Bonds/ Debentures 3 Total (1+2) 507 218339 39 26057 19 1212 39 26057 19 1212 3.1 Public 365 198627 31 24414 13 1032 31 24414 13 1032 3.2 Rights 142 19712 8 1643 6 180 8 1643 6 180 Notes : 1. Since April 2020, monthly data on equity issues is compiled on the basis of their listing date. 2. Figures in the columns might not add up to the total due to rounding off numbers. 3. The table covers only public and rights issuances of equity and debt. It does not include data on private placement of debt, qualified institutional placements and preferential allotments. Source : Securities and Exchange Board of India. * : Data is Provisional RBI Bulletin June 2025 143CURRENT STATISTICS External Sector No. 31: Foreign Trade 2024 2025 2024-25 Item Unit Apr. Dec. Jan. Feb. Mar. Apr. 1 2 3 4 5 6 7 1 Exports ₹ Crore 3701070 294453 321275 313532 320532 363598 329794 US $ Million 437416 35304 37803 36345 36820 41968 38488 1.1 Oil ₹ Crore 534917 58761 40022 29943 49785 42467 63097 US $ Million 63341 7045 4709 3471 5719 4902 7374 1.2 Non-oil ₹ Crore 3166153 235693 281253 283588 270747 321131 266697 US $ Million 374075 28258 33094 32874 31101 37066 31113 2 Imports ₹ Crore 6089909 454463 496989 512680 443663 550211 555392 US $ Million 720241 54488 58479 59430 50964 63507 64912 2.1 Oil ₹ Crore 1570226 137565 115543 115941 103528 164684 177245 US $ Million 185779 16493 13595 13440 11892 19008 20716 2.2 Non-oil ₹ Crore 4519683 316898 381447 396739 340135 385527 378147 US $ Million 534462 37995 44883 45990 39071 44499 44196 3 Trade Balance ₹ Crore -2388839 -160010 -175714 -199148 -123131 -186613 -225598 US $ Million -282825 -19184 -20676 -23085 -14144 -21539 -26424 3.1 Oil ₹ Crore -1035309 -78804 -75521 -85998 -53743 -122217 -114148 US $ Million -122438 -9448 -8886 -9969 -6173 -14107 -13341 3.2 Non-oil ₹ Crore -1353530 -81205 -100193 -113150 -69388 -64395 -111450 US $ Million -160387 -9736 -11789 -13117 -7971 -7433 -13083 Note: Data in the table are provisional. Source: Directorate General of Commercial Intelligence and Statistics. No. 32: Foreign Exchange Reserves 2024 2025 Item Unit Jun. 07 Apr. 25 May. 02 May. 09 May. 16 May. 23 May. 30 1 2 3 4 5 6 7 1 Total Reserves ₹ Crore 5468448 5879208 5797792 5897173 5865523 5902926 5916602 US $ Million 655817 688129 686064 690617 685729 692721 691485 1.1 Foreign Currency Assets ₹ Crore 4805700 4960996 4911665 4964245 4975264 4994767 4998795 US $ Million 576337 580663 581177 581373 581652 586167 584215 1.2 Gold ₹ Crore 475139 720785 691478 737220 694701 712210 721351 US $ Million 56982 84365 81820 86337 81217 83582 84305 Volume (Metric Tonnes) 834.23 879.58 879.58 879.58 879.58 879.58 879.58 1.3 SDRs SDRs Million 13699 13706 13706 13706 13707 13707 13707 ₹ Crore 151432 158817 156841 158246 158155 158241 158885 US $ Million 18161 18589 18558 18532 18490 18571 18569 1.4 Reserve Tranche Position in IMF ₹ Crore 36177 38610 37807 37462 37404 37708 37571 US $ Million 4336 4512 4509 4374 4371 4401 4395 * Difference, if any, is due to rounding off. Note: Exclude investment in foreign currency denominated bonds issued by IIFC (UK), SDRs transferred by Government of India to RBI, foreign currency received under SAARC and ACU currency swap arrangements and RBI’s contribution to funding of Nexus Global Payments. Foreign currency assets in US dollar take into account appreciation/depreciation of non- US currencies (such as Euro, Sterling, Yen and Australian Dollar) held in reserves. Foreign exchange holdings are converted into rupees at rupee-US dollar RBI holding rates. No. 33: Non-Resident Deposits (US $ Million) Scheme Outstanding Flows 2024 2025 2024-25 2025-26 2024-25 Apr. Mar. Apr. (P) Apr. Apr.(P) 1 2 3 4 5 6 1 NRI Deposits 164677 153009 164677 165432 1078 751 1.1 FCNR(B) 32809 26216 32809 33081 483 272 1.2 NR(E)RA 100733 99229 100733 101112 564 376 1.3 NRO 31135 27564 31135 31239 31 103 P: Provisional. 144 RBI Bulletin June 2025CURRENT STATISTICS No. 34: Foreign Investment Inflows (US $ Million) 2024-25 2025-26 (P) 2024 (P) 2025 (P) Item 2024-25 Apr. Apr. Apr. Mar. Apr. 1 2 3 4 5 6 1.1 Net Foreign Direct Investment (1.1.1-1.1.2) 2291 1917 3945 1917 -438 3945 1.1.1 Direct Investment to India (1.1.1.1-1.1.1.2) 29554 3105 7135 3105 3322 7135 1.1.1.1 Gross Inflows/Gross Investments 81043 7162 8803 7162 5938 8803 1.1.1.1.1 Equity 50993 4984 6634 4984 3240 6634 1.1.1.1.1.1 Government (SIA/FIPB) 2208 11 297 11 307 297 1.1.1.1.1.2 RBI 34686 4732 4696 4732 2440 4696 1.1.1.1.1.3 Acquisition of shares 13124 166 1566 166 405 1566 1.1.1.1.1.4 Equity capital of unincorporated bodies 976 75 75 75 88 75 1.1.1.1.2 Reinvested earnings 23545 1801 1801 1801 2130 1801 1.1.1.1.3 Other capital 6505 377 368 377 567 368 1.1.1.2 Repatriation/Disinvestment 51489 4057 1668 4057 2616 1668 1.1.1.2.1 Equity 49529 3891 1513 3891 2525 1513 1.1.1.2.2 Other capital 1960 166 155 166 90 155 1.1.2 Foreign Direct Investment by India 27262 1188 3190 1188 3760 3190 (1.1.2.1+1.1.2.2+1.1.2.3-1.1.2.4) 1.1.2.1 Equity capital 16043 653 1812 653 2290 1812 1.1.2.2 Reinvested Earnings 6555 546 546 546 546 546 1.1.2.3 Other Capital 8238 371 949 371 1233 949 1.1.2.4 Repatriation/Disinvestment 3575 382 118 382 309 118 1.2 Net Portfolio Investment (1.2.1+1.2.2+1.2.3-1.2.4) 2667 -2683 -3097 -2683 3877 -3097 1.2.1 GDRs/ADRs - - - - - - 1.2.2 FIIs 2429 -2699 -2440 -2699 3827 -2440 1.2.3 Offshore funds and others - - - - - - 1.2.4 Portfolio investment by India -238 -16 658 -16 -50 658 1 Foreign Investment Inflows 4959 -766 847 -766 3439 847 P: Provisional No. 35: Outward Remittances under the Liberalised Remittance Scheme (LRS) for Resident Individuals (US $ Million) 2024 2025 Item 2024-25 Apr. Feb. Mar. Apr. 1 2 3 4 5 1 Outward Remittances under the LRS 29563.12 2285.77 1964.21 2547.57 2481.41 1.1 Deposit 705.26 72.67 51.62 173.17 94.15 1.2 Purchase of immovable property 322.82 23.19 28.76 45.10 44.69 1.3 Investment in equity/debt 1698.94 98.94 173.84 306.39 203.44 1.4 Gift 2938.69 311.16 190.82 299.59 290.89 1.5 Donations 11.81 1.70 0.59 2.20 1.57 1.6 Travel 16964.57 1144.31 1090.61 1125.55 1270.44 1.7 Maintenance of close relatives 3722.03 391.69 234.99 421.47 397.97 1.8 Medical Treatment 81.19 10.38 3.43 3.57 5.08 1.9 Studies Abroad 2918.91 208.02 182.17 160.03 163.56 1.10 Others 198.90 23.70 7.38 10.51 9.61 RBI Bulletin June 2025 145CURRENT STATISTICS No. 36: Indices of Nominal Effective Exchange Rate (NEER) and Real Effective Exchange Rate (REER) of the Indian Rupee 2024 2025 2023-24 2024-25 May Apr May Item 1 2 3 4 5 40-Currency Basket (Base: 2015-16=100) 1 Trade-Weighted 1.1 NEER 90.75 91.05 91.96 89.71 89.14 1.2 REER 103.71 105.28 104.40 100.78 101.08 2 Export-Weighted 2.1 NEER 93.13 93.53 94.24 92.39 91.98 2.2 REER 101.22 102.35 101.40 97.85 98.32 6-Currency Basket (Trade-weighted) 1 Base : 2015-16 =100 1.1 NEER 83.62 82.39 83.60 80.36 80.29 1.2 REER 101.66 102.74 102.11 99.12 99.25 2 Base : 2022-23 =100 2.1 NEER 97.31 95.89 97.29 93.52 93.44 2.2 REER 99.86 100.92 100.31 97.37 97.50 Note: Data for 2023-24 and 2024-25 so far is provisional. 146 RBI Bulletin June 2025CURRENT STATISTICS No. 37: External Commercial Borrowings (ECBs) – Registrations (Amount in US $ Million) Item 2024-25 2024 2025 Apr. Mar. Apr. 1 2 3 4 1 Automatic Route 1.1 Number 1328 100 142 119 1.2 Amount 47800 3891 8346 1907 2 Approval Route 2.1 Number 51 1 17 3 2.2 Amount 13384 394 2697 1010 3 Total (1+2) 3.1 Number 1379 101 159 122 3.2 Amount 61184 4285 11043 2917 4 Weighted Average Maturity (in years) 5.05 5.00 4.50 4.20 5 Interest Rate (per cent) 5.1 Weighted Average Margin over alternative reference rate (ARR) for Floating Rate Loans@ 1.48 1.32 1.39 1.41 5.2 Interest rate range for Fixed Rate Loans 0.00-11.67 0.00-10.50 0.00-10.63 0.00-10.25 Borrower Category I. Corporate Manufacturing 13900 410 2273 817 II. Corporate-Infrastructure 15462 1814 3507 48 a.) Transport 614 43 0 0 b.) Energy 6900 380 1828 0 c.) Water and Sanitation 28 0 0 0 d.) Communication 13 0 0 0 e.) Social and Commercial Infrastructure 184 46 2 45 f.) Exploration,Mining and Refinery 5356 550 1675 0 g.) Other Sub-Sectors 2367 795 2 3 III. Corporate Service-Sector 3226 18 522 337 IV. Other Entities 1026 0 0 8 a.) units in SEZ 26 0 0 8 b.) SIDBI 0 0 0 0 c.) Exim Bank 1000 0 0 0 V. Banks 0 0 0 0 VI. Financial Institution (Other than NBFC ) 0 0 0 0 VII. NBFCs 26318 1875 4718 1530 a). NBFC- IFC/AFC 12389 411 1567 1159 b). NBFC-MFI 459 28 100 0 c). NBFC-Others 13470 1436 3051 371 VIII. Non-Government Organization (NGO) 0 0 0 0 IX. Micro Finance Institution (MFI) 0 0 0 0 X. Others 1252 168 23 177 Note: Based on applications for ECB/Foreign Currency Convertible Bonds (FCCBs) which have been allotted loan registration number during the period. @ With effect from July 01, 2023, the benchmark rate is changed to Alternative Reference Rate (ARR). RBI Bulletin June 2025 147CURRENT STATISTICS No. 38: India’s Overall Balance of Payments (US$ Million) Oct-Dec 2023 Oct-Dec 2024 (P) Credit Debit Net Credit Debit Net Item 1 2 3 4 5 6 Overall Balance Of Payments (1+2+3) 452267 446269 5998 544591 582251 -37660 1 Current Account (1.1+ 1.2) 236020 246451 -10431 261653 273133 -11480 1.1 Merchandise 106626 178267 -71641 109817 188970 -79153 1.2 Invisibles (1.2.1+1.2.2+1.2.3) 129394 68184 61210 151837 84164 67673 1.2.1 Services 87785 42778 45007 103487 52277 51210 1.2.1.1 Travel 9850 7487 2363 10068 8371 1698 1.2.1.2 Transportation 6950 6457 493 8278 8847 -569 1.2.1.3 Insurance 811 856 -46 870 894 -24 1.2.1.4 G.n.i.e. 182 280 -98 167 307 -139 1.2.1.5 Miscellaneous 69993 27699 42294 84104 33859 50245 1.2.1.5.1 Software Services 41041 4774 36267 47619 6561 41057 1.2.1.5.2 Business Services 22647 14067 8581 29603 18252 11352 1.2.1.5.3 Financial Services 2491 956 1535 2086 741 1346 1.2.1.5.4 Communication Services 701 397 303 580 616 -37 1.2.2 Transfers 31539 2237 29302 36081 2898 33182 1.2.2.1 Official 94 230 -135 89 334 -244 1.2.2.2 Private 31445 2007 29438 35992 2565 33427 1.2.3 Income 10069 23168 -13099 12268 28988 -16720 1.2.3.1 Investment Income 8058 22292 -14233 10088 27943 -17854 1.2.3.2 Compensation of Employees 2010 876 1134 2180 1046 1135 2 Capital Account (2.1+2.2+2.3+2.4+2.5) 216247 198955 17291 282367 309118 -26751 2.1 Foreign Investment (2.1.1+2.1.2) 144352 128388 15964 192195 206344 -14148 2.1.1 Foreign Direct Investment 18875 14923 3952 20783 23560 -2776 2.1.1.1 In India 18309 9947 8362 19870 16218 3653 2.1.1.1.1 Equity 11912 8773 3140 11135 15637 -4501 2.1.1.1.2 Reinvested Earnings 5155 5155 6131 6131 2.1.1.1.3 Other Capital 1242 1175 67 2604 581 2024 2.1.1.2 Abroad 566 4976 -4410 913 7342 -6429 2.1.1.2.1 Equity 566 2355 -1789 913 3211 -2297 2.1.1.2.2 Reinvested Earnings 0 1446 -1446 0 1639 -1639 2.1.1.2.3 Other Capital 0 1174 -1174 0 2493 -2493 2.1.2 Portfolio Investment 125477 113465 12012 171412 182784 -11372 2.1.2.1 In India 124485 112814 11671 170667 182102 -11435 2.1.2.1.1 FIIs 124485 112814 11671 170667 182102 -11435 2.1.2.1.1.1 Equity 108785 102117 6668 144811 156671 -11860 2.1.2.1.1.2 Debt 15701 10697 5003 25856 25431 425 2.1.2.1.2 ADR/GDRs 0 0 0 0 0 0 2.1.2.2 Abroad 991 651 341 745 682 63 2.2 Loans (2.2.1+2.2.2+2.2.3) 25440 28191 -2751 42894 33992 8901 2.2.1 External Assistance 4605 1401 3204 2955 2289 666 2.2.1.1 By India 9 48 -40 6 26 -20 2.2.1.2 To India 4596 1353 3244 2949 2263 686 2.2.2 Commercial Borrowings 6600 11067 -4466 20838 16462 4375 2.2.2.1 By India 2712 4503 -1791 9621 9593 28 2.2.2.2 To India 3888 6564 -2676 11217 6869 4348 2.2.3 Short Term to India 14235 15723 -1489 19101 15241 3860 2.2.3.1 Buyers' credit & Suppliers' Credit >180 days 12535 15723 -3188 14260 15241 -980 2.2.3.2 Suppliers' Credit up to 180 days 1700 0 1700 4840 0 4840 2.3 Banking Capital (2.3.1+2.3.2) 40849 24492 16358 39538 49311 -9774 2.3.1 Commercial Banks 40654 24492 16162 39530 49306 -9776 2.3.1.1 Assets 16550 5276 11274 11853 25923 -14070 2.3.1.2 Liabilities 24103 19215 4888 27677 23383 4294 2.3.1.2.1 Non-Resident Deposits 22381 18461 3921 25912 22771 3141 2.3.2 Others 196 0 196 8 5 2 2.4 Rupee Debt Service 2 -2 0 0 2.5 Other Capital 5606 17884 -12278 7740 19471 -11730 3 Errors & Omissions 0 862 -862 571 0 571 4 Monetary Movements (4.1+ 4.2) 0 5998 -5998 37660 0 37660 4.1 I.M.F. 0 0 0 0 0 0 4.2 Foreign Exchange Reserves (Increase - / Decrease +) 5998 -5998 37660 37660 Note: P: Preliminary. 148 RBI Bulletin June 2025CURRENT STATISTICS No. 39: India’s Overall Balance of Payments (₹ Crore) Oct-Dec 2023 Oct-Dec 2024 (P) Credit Debit Net Credit Debit Net Item 1 2 3 4 5 6 Overall Balance Of Payments (1+2+3) 3766056 3716109 49947 4599615 4917695 -318081 1 Current Account (1.1+ 1.2) 1965353 2052216 -86862 2209923 2306886 -96963 1.1 Merchandise 887883 1484446 -596562 927511 1596038 -668527 1.2 Invisibles (1.2.1+1.2.2+1.2.3) 1077470 567770 509700 1282412 710849 571564 1.2.1 Services 730995 356218 374778 874055 441534 432521 1.2.1.1 Travel 82022 62341 19681 85035 70697 14338 1.2.1.2 Transportation 57875 53767 4108 69915 74723 -4807 1.2.1.3 Insurance 6749 7130 -381 7347 7553 -206 1.2.1.4 G.n.i.e. 1512 2328 -816 1413 2590 -1177 1.2.1.5 Miscellaneous 582837 230650 352187 710344 285971 424373 1.2.1.5.1 Software Services 341751 39756 301995 402186 55417 346769 1.2.1.5.2 Business Services 188585 117135 71450 250030 154153 95877 1.2.1.5.3 Financial Services 20739 7958 12781 17623 6256 11367 1.2.1.5.4 Communication Services 5834 3309 2524 4896 5207 -310 1.2.2 Transfers 262631 18628 244002 304738 24479 280259 1.2.2.1 Official 785 1913 -1127 753 2817 -2064 1.2.2.2 Private 261845 16716 245130 303985 21662 282323 1.2.3 Income 83844 192924 -109080 103619 244836 -141216 1.2.3.1 Investment Income 67103 185626 -118523 85206 236005 -150799 1.2.3.2 Compensation of Employees 16741 7298 9443 18413 8831 9582 2 Capital Account (2.1+2.2+2.3+2.4+2.5) 1800703 1656716 143987 2384871 2610809 -225938 2.1 Foreign Investment (2.1.1+2.1.2) 1202027 1069092 132935 1623281 1742779 -119498 2.1.1 Foreign Direct Investment 157173 124264 32909 175537 198987 -23449 2.1.1.1 In India 152460 82832 69628 167826 136974 30852 2.1.1.1.1 Equity 99194 73050 26144 94049 132068 -38019 2.1.1.1.2 Reinvested Earnings 42926 0 42926 51780 0 51780 2.1.1.1.3 Other Capital 10340 9783 557 21996 4905 17091 2.1.1.2 Abroad 4713 41432 -36718 7712 62013 -54301 2.1.1.2.1 Equity 4713 19610 -14897 7712 27116 -19405 2.1.1.2.2 Reinvested Earnings 0 12044 -12044 0 13842 -13842 2.1.1.2.3 Other Capital 0 9777 -9777 0 21055 -21055 2.1.2 Portfolio Investment 1044854 944828 100026 1447744 1543792 -96048 2.1.2.1 In India 1036599 939411 97188 1441453 1538030 -96577 2.1.2.1.1 FIIs 1036599 939411 97188 1441453 1538030 -96577 2.1.2.1.1.1 Equity 905860 850336 55523 1223076 1323243 -100167 2.1.2.1.1.2 Debt 130739 89075 41664 218376 214787 3590 2.1.2.1.2 ADR/GDRs 0 0 0 0 0 0 2.1.2.2 Abroad 8255 5417 2838 6291 5762 529 2.2 Loans (2.2.1+2.2.2+2.2.3) 211839 234747 -22908 362279 287097 75181 2.2.1 External Assistance 38345 11667 26679 24961 19334 5626 2.2.1.1 By India 72 404 -331 52 217 -166 2.2.1.2 To India 38273 11263 27010 24909 19117 5792 2.2.2 Commercial Borrowings 54961 92153 -37192 175994 139042 36953 2.2.2.1 By India 22583 37494 -14911 81258 81026 232 2.2.2.2 To India 32378 54659 -22281 94736 58016 36720 2.2.3 Short Term to India 118532 130928 -12396 161324 128721 32602 2.2.3.1 Buyers' credit & Suppliers' Credit >180 days 104379 130928 -26549 120442 128721 -8280 2.2.3.2 Suppliers' Credit up to 180 days 14154 0 14154 40882 0 40882 2.3 Banking Capital (2.3.1+2.3.2) 340156 203943 136212 333936 416483 -82547 2.3.1 Commercial Banks 338525 203943 134582 333872 416438 -82566 2.3.1.1 Assets 137815 43936 93879 100112 218949 -118837 2.3.1.2 Liabilities 200710 160008 40702 233760 197489 36271 2.3.1.2.1 Non-Resident Deposits 186372 153723 32648 218851 192322 26530 2.3.2 Others 1630 0 1630 64 45 19 2.4 Rupee Debt Service 0 13 -13 0 0 0 2.5 Other Capital 46682 148921 -102239 65376 164450 -99074 3 Errors & Omissions 0 7177 -7177 4820 0 4820 4 Monetary Movements (4.1+ 4.2) 0 49947 -49947 318081 0 318081 4.1 I.M.F. 0 0 0 0 0 0 4.2 Foreign Exchange Reserves (Increase - / Decrease +) 0 49947 -49947 318081 0 318081 Note: P: Preliminary. RBI Bulletin June 2025 149CURRENT STATISTICS No. 40: Standard Presentation of BoP in India as per BPM6 (US$ Million) Item Oct-Dec 2023 Oct-Dec 2024 (P) Credit Debit Net Credit Debit Net 1 2 3 4 5 6 1 Current Account (1.A+1.B+1.C) 236013 246429 -10416 261647 273103 -11457 1.A Goods and Services (1.A.a+1.A.b) 194412 221046 -26634 213304 241247 -27943 1.A.a Goods (1.A.a.1 to 1.A.a.3) 106626 178267 -71641 109817 188970 -79153 1.A.a.1 General merchandise on a BOP basis 106094 164567 -58473 109391 169503 -60112 1.A.a.2 Net exports of goods under merchanting 532 0 532 426 0 426 1.A.a.3 Nonmonetary gold 0 13701 -13701 0 19467 -19467 1.A.b Services (1.A.b.1 to 1.A.b.13) 87785 42778 45007 103487 52277 51210 1.A.b.1 Manufacturing services on physical inputs owned by others 330 20 310 244 31 213 1.A.b.2 Maintenance and repair services n.i.e. 49 297 -248 82 305 -223 1.A.b.3 Transport 6950 6457 493 8278 8847 -569 1.A.b.4 Travel 9850 7487 2363 10068 8371 1698 1.A.b.5 Construction 1097 624 473 1047 834 213 1.A.b.6 Insurance and pension services 811 856 -46 870 894 -24 1.A.b.7 Financial services 2491 956 1535 2086 741 1346 1.A.b.8 Charges for the use of intellectual property n.i.e. 434 4633 -4199 621 4573 -3952 1.A.b.9 Telecommunications, computer, and information services 41837 5400 36437 48296 7416 40880 1.A.b.10 Other business services 22647 14067 8581 29603 18252 11352 1.A.b.11 Personal, cultural, and recreational services 1006 1464 -459 1148 1242 -95 1.A.b.12 Government goods and services n.i.e. 182 280 -98 167 307 -139 1.A.b.13 Others n.i.e. 103 239 -136 977 465 513 1.B Primary Income (1.B.1 to 1.B.3) 10069 23168 -13099 12268 28988 -16720 1.B.1 Compensation of employees 2010 876 1134 2180 1046 1135 1.B.2 Investment income 6557 21972 -15415 8021 27150 -19128 1.B.2.1 Direct investment 2104 13735 -11631 2558 17331 -14772 1.B.2.2 Portfolio investment 51 1911 -1860 95 2596 -2502 1.B.2.3 Other investment 557 6102 -5545 690 7019 -6329 1.B.2.4 Reserve assets 3845 224 3621 4678 204 4474 1.B.3 Other primary income 1501 320 1181 2067 793 1274 1.C Secondary Income (1.C.1+1.C.2) 31532 2215 29317 36074 2868 33206 1.C.1 Financial corporations, nonfinancial corporations, households, and NPISHs 31445 2007 29438 35992 2565 33427 1.C.1.1 Personal transfers (Current transfers between resident and/non-resident households) 30589 1430 29160 35063 1871 33192 1.C.1.2 Other current transfers 856 578 278 928 694 234 1.C.2 General government 87 208 -120 83 303 -221 2 Capital Account (2.1+2.2) 191 280 -89 185 322 -137 2.1 Gross acquisitions (DR.)/disposals (CR.) of non-produced nonfinancial assets 36 86 -50 16 151 -135 2.2 Capital transfers 155 194 -38 169 171 -2 3 Financial Account (3.1 to 3.5) 216063 204696 11367 319849 308826 11023 3.1 Direct Investment (3.1A+3.1B) 18875 14923 3952 20783 23560 -2776 3.1.A Direct Investment in India 18309 9947 8362 19870 16218 3653 3.1.A.1 Equity and investment fund shares 17067 8773 8295 17266 15637 1629 3.1.A.1.1 Equity other than reinvestment of earnings 11912 8773 3140 11135 15637 -4501 3.1.A.1.2 Reinvestment of earnings 5155 0 5155 6131 6131 3.1.A.2 Debt instruments 1242 1175 67 2604 581 2024 3.1.A.2.1 Direct investor in direct investment enterprises 1242 1175 67 2604 581 2024 3.1.B Direct Investment by India 566 4976 -4410 913 7342 -6429 3.1.B.1 Equity and investment fund shares 566 3801 -3235 913 4849 -3936 3.1.B.1.1 Equity other than reinvestment of earnings 566 2355 -1789 913 3211 -2297 3.1.B.1.2 Reinvestment of earnings 0 1446 -1446 1639 -1639 3.1.B.2 Debt instruments 0 1174 -1174 0 2493 -2493 3.1.B.2.1 Direct investor in direct investment enterprises 0 1174 -1174 2493 -2493 3.2 Portfolio Investment 125477 113465 12012 171412 182784 -11372 3.2.A Portfolio Investment in India 124485 112814 11671 170667 182102 -11435 3.2.1 Equity and investment fund shares 108785 102117 6668 144811 156671 -11860 3.2.2 Debt securities 15701 10697 5003 25856 25431 425 3.2.B Portfolio Investment by India 991 651 341 745 682 63 3.3 Financial derivatives (other than reserves) and employee stock options 5776 7904 -2128 6569 12105 -5536 3.4 Other investment 65936 62407 3529 83424 90377 -6953 3.4.1 Other equity (ADRs/GDRs) 0 0 0 0 0 0 3.4.2 Currency and deposits 22577 18461 4117 25919 22776 3143 3.4.2.1 Central bank (Rupee Debt Movements; NRG) 196 0 196 8 5 2 3.4.2.2 Deposit-taking corporations, except the central bank (NRI Deposits) 22381 18461 3921 25912 22771 3141 3.4.2.3 General government 0 0 0 0 3.4.2.4 Other sectors 0 0 0 0 3.4.3 Loans (External Assistance, ECBs and Banking Capital) 29477 18499 10979 37411 45287 -7876 3.4.3.A Loans to India 26757 13948 12809 27784 35668 -7883 3.4.3.B Loans by India 2721 4551 -1830 9627 9619 8 3.4.4 Insurance, pension, and standardized guarantee schemes 37 158 -121 52 59 -7 3.4.5 Trade credit and advances 14235 15723 -1489 19101 15241 3860 3.4.6 Other accounts receivable/payable - other -390 9566 -9957 941 7015 -6074 3.4.7 Special drawing rights 0 0 0 0 3.5 Reserve assets 0 5998 -5998 37660 0 37660 3.5.1 Monetary gold 0 0 0 0 3.5.2 Special drawing rights n.a. 0 0 0 0 3.5.3 Reserve position in the IMF n.a. 0 0 0 0 3.5.4 Other reserve assets (Foreign Currency Assets) 0 5998 -5998 37660 0 37660 4 Total assets/liabilities 216063 204696 11367 319849 308826 11023 4.1 Equity and investment fund shares 133222 123403 9819 170356 190003 -19647 4.2 Debt instruments 83231 65728 17503 110891 111808 -916 4.3 Other financial assets and liabilities -390 15565 -15955 38601 7015 31586 5 Net errors and omissions 0 862 -862 571 0 571 Note: P: Preliminary. 150 RBI Bulletin June 2025CURRENT STATISTICS No. 41: Standard Presentation of BoP in India as per BPM6 (₹ Crore) Oct-Dec 2023 Oct-Dec 2024 (P) Item Credit Debit Net Credit Debit Net 1 2 3 4 5 6 1 Current Account (1.A+1.B+1.C) 1965295 2052031 -86736 2209867 2306632 -96765 1.A Goods and Services (1.A.a+1.A.b) 1618879 1840663 -221785 1801566 2037572 -236006 1.A.a Goods (1.A.a.1 to 1.A.a.3) 887883 1484446 -596562 927511 1596038 -668527 1.A.a.1 General merchandise on a BOP basis 883452 1370357 -486905 923914 1431621 -507707 1.A.a.2 Net exports of goods under merchanting 4432 0 4432 3597 0 3597 1.A.a.3 Nonmonetary gold 0 114089 -114089 0 164417 -164417 1.A.b Services (1.A.b.1 to 1.A.b.13) 730995 356218 374778 874055 441534 432521 1.A.b.1 Manufacturing services on physical inputs owned by others 2746 163 2583 2061 262 1798 1.A.b.2 Maintenance and repair services n.i.e. 407 2474 -2067 689 2574 -1886 1.A.b.3 Transport 57875 53767 4108 69915 74723 -4807 1.A.b.4 Travel 82022 62341 19681 85035 70697 14338 1.A.b.5 Construction 9139 5196 3942 8843 7044 1799 1.A.b.6 Insurance and pension services 6749 7130 -381 7347 7553 -206 1.A.b.7 Financial services 20739 7958 12781 17623 6256 11367 1.A.b.8 Charges for the use of intellectual property n.i.e. 3611 38576 -34965 5245 38627 -33383 1.A.b.9 Telecommunications, computer, and information services 348376 44964 303412 407907 62636 345271 1.A.b.10 Other business services 188585 117135 71450 250030 154153 95877 1.A.b.11 Personal, cultural, and recreational services 8373 12194 -3820 9693 10492 -799 1.A.b.12 Government goods and services n.i.e. 1512 2328 -816 1413 2590 -1177 1.A.b.13 Others n.i.e. 861 1991 -1130 8255 3926 4329 1.B Primary Income (1.B.1 to 1.B.3) 83844 192924 -109080 103619 244836 -141216 1.B.1 Compensation of employees 16741 7298 9443 18413 8831 9582 1.B.2 Investment income 54604 182963 -128359 67749 229307 -161558 1.B.2.1 Direct investment 17522 114371 -96848 21607 146374 -124767 1.B.2.2 Portfolio investment 425 15915 -15490 800 21930 -21130 1.B.2.3 Other investment 4636 50812 -46176 5827 59279 -53452 1.B.2.4 Reserve assets 32021 1866 30155 39515 1724 37791 1.B.3 Other primary income 12499 2663 9836 17457 6698 10760 1.C Secondary Income (1.C.1+1.C.2) 262572 18444 244128 304682 24225 280457 1.C.1 Financial corporations, nonfinancial corporations, households, and NPISHs 261845 16716 245130 303985 21662 282323 1.C.1.1 Personal transfers (Current transfers between resident and/non-resident households) 254718 11904 242814 296144 15800 280343 1.C.1.2 Other current transfers 7127 4811 2316 7842 5862 1980 1.C.2 General government 727 1728 -1001 697 2563 -1866 2 Capital Account (2.1+2.2) 1590 2328 -739 1564 2720 -1156 2.1 Gross acquisitions (DR.)/disposals (CR.) of non-produced nonfinancial assets 296 715 -419 136 1275 -1139 2.2 Capital transfers 1293 1613 -320 1428 1445 -17 3 Financial Account (3.1 to 3.5) 1799172 1704519 94652 2701444 2608343 93101 3.1 Direct Investment (3.1A+3.1B) 157173 124264 32909 175537 198987 -23449 3.1.A Direct Investment in India 152460 82832 69628 167826 136974 30852 3.1.A.1 Equity and investment fund shares 142120 73050 69070 145829 132068 13761 3.1.A.1.1 Equity other than reinvestment of earnings 99194 73050 26144 94049 132068 -38019 3.1.A.1.2 Reinvestment of earnings 42926 0 42926 51780 0 51780 3.1.A.2 Debt instruments 10340 9783 557 21996 4905 17091 3.1.A.2.1 Direct investor in direct investment enterprises 10340 9783 557 21996 4905 17091 3.1.B Direct Investment by India 4713 41432 -36718 7712 62013 -54301 3.1.B.1 Equity and investment fund shares 4713 31654 -26941 7712 40958 -33246 3.1.B.1.1 Equity other than reinvestment of earnings 4713 19610 -14897 7712 27116 -19405 3.1.B.1.2 Reinvestment of earnings 0 12044 -12044 0 13842 -13842 3.1.B.2 Debt instruments 0 9777 -9777 0 21055 -21055 3.1.B.2.1 Direct investor in direct investment enterprises 0 9777 -9777 0 21055 -21055 3.2 Portfolio Investment 1044854 944828 100026 1447744 1543792 -96048 3.2.A Portfolio Investment in India 1036599 939411 97188 1441453 1538030 -96577 3.2.1 Equity and investment fund shares 905860 850336 55523 1223076 1323243 -100167 3.2.2 Debt securities 130739 89075 41664 218376 214787 3590 3.2.B Portfolio Investment by India 8255 5417 2838 6291 5762 529 3.3 Financial derivatives (other than reserves) and employee stock options 48093 65814 -17720 55483 102239 -46756 3.4 Other investment 549051 519667 29385 704599 763325 -58727 3.4.1 Other equity (ADRs/GDRs) 0 0 0 0 0 0 3.4.2 Currency and deposits 188002 153723 34279 218915 192367 26549 3.4.2.1 Central bank (Rupee Debt Movements; NRG) 1630 0 1630 64 45 19 3.4.2.2 Deposit-taking corporations, except the central bank (NRI Deposits) 186372 153723 32648 218851 192322 26530 3.4.2.3 General government 0 0 0 0 0 0 3.4.2.4 Other sectors 0 0 0 0 0 0 3.4.3 Loans (External Assistance, ECBs and Banking Capital) 245460 154040 91420 315976 382492 -66517 3.4.3.A Loans to India 222804 116142 106662 234666 301249 -66583 3.4.3.B Loans by India 22656 37898 -15242 81310 81243 67 3.4.4 Insurance, pension, and standardized guarantee schemes 306 1315 -1009 437 497 -59 3.4.5 Trade credit and advances 118532 130928 -12396 161324 128721 32602 3.4.6 Other accounts receivable/payable - other -3249 79661 -82910 7947 59249 -51302 3.4.7 Special drawing rights 0 0 0 0 0 0 3.5 Reserve assets 0 49947 -49947 318081 0 318081 3.5.1 Monetary gold 0 0 0 0 0 0 3.5.2 Special drawing rights n.a. 0 0 0 0 0 0 3.5.3 Reserve position in the IMF n.a. 0 0 0 0 0 0 3.5.4 Other reserve assets (Foreign Currency Assets) 0 49947 -49947 318081 0 318081 4 Total assets/liabilities 1799172 1704519 94652 2701444 2608343 93101 4.1 Equity and investment fund shares 1109347 1027586 81762 1438829 1604767 -165939 4.2 Debt instruments 693073 547325 145748 936587 944327 -7740 4.3 Other financial assets and liabilities -3249 129608 -132857 326028 59249 266779 5 Net errors and omissions 0 7177 -7177 4820 0 4820 Note: P: Preliminary. RBI Bulletin June 2025 151CURRENT STATISTICS No. 42: India’s International Investment Position (US$ Million) Item As on Financial Year/Quarter End 2023-24 2023 2024 Dec. Sep. Dec. Assets Liabilities Assets Liabilities Assets Liabilities Assets Liabilities 1 2 3 4 5 6 7 8 1. Direct investment Abroad/in India 242271 542950 236506 536935 253846 555666 260275 547588 1.1 Equity Capital* 153343 511142 149394 505572 161794 523146 165730 513545 1.2 Other Capital 88927 31808 87112 31363 92053 32520 94545 34043 2. Portfolio investment 12469 276739 11744 268727 12503 293843 12173 276024 2.1 Equity 10942 162061 9523 161206 11241 170934 9356 155573 2.2 Debt 1527 114678 2220 107521 1262 122909 2817 120451 3. Other investment 132654 575284 128316 561466 146714 622795 170554 619611 3.1 Trade credit 33450 123723 31689 123290 32953 130938 33280 135136 3.2 Loan 17547 221894 18510 214954 22147 239779 22523 240977 3.3 Currency and Deposits 53519 154787 44339 149326 56105 164076 68630 165713 3.4 Other Assets/Liabilities 28138 74880 33777 73895 35510 88002 46121 77784 4. Reserves 646419 622452 705782 635701 5. Total Assets/ Liabilities 1033812 1394973 999018 1367128 1118845 1472304 1078704 1443223 6. Net IIP (Assets - Liabilities) -361161 -368110 -353459 -364519 Note: * Equity capital includes share of investment funds and reinvested earnings. 152 RBI Bulletin June 2025CURRENT STATISTICS Payment and Settlement Systems No.43: Payment System Indicators PART I - Payment System Indicators - Payment & Settlement System Statistics System Volume (Lakh) Value (₹ Crore) FY 2024-25 2024 2025 FY 2024-25 2024 2025 Apr. Mar. Apr. Apr. Mar. Apr. 1 -2 -1 0 5 2 3 4 A. Settlement Systems Financial Market Infrastructures (FMIs) 1 CCIL Operated Systems (1.1 to 1.3) 47.40 3.53 4.36 5.07 296218030 22115118 27936158 29399814 1.1 Govt. Securities Clearing (1.1.1 to 1.1.3) 17.87 1.25 1.33 1.89 185733719 14132535 15356048 16657576 1.1.1 Outright 10.56 0.68 0.76 1.30 16056018 1023439 1297378 2017823 1.1.2 Repo 4.72 0.38 0.36 0.38 77286611 6510577 6589738 7078422 1.1.3 Tri-party Repo 2.58 0.19 0.21 0.20 92391091 6598519 7468932 7561331 1.2 Forex Clearing 28.06 2.17 2.94 3.07 100639565 7343662 11758724 11992139 1.3 Rupee Derivatives @ 1.46 0.11 0.09 0.11 9844746 638922 821387 750099 B. Payment Systems I Financial Market Infrastructures (FMIs) - - - - - - - - 1 Credit Transfers - RTGS (1.1 to 1.2) 3024.55 235.59 307.03 262.41 201387682 14433296 21401969 16895789 1.1 Customer Transactions 3010.32 234.46 305.71 261.16 181153129 12800746 19394683 15060026 1.2 Interbank Transactions 14.23 1.12 1.32 1.24 20234553 1632550 2007287 1835763 II Retail 2 Credit Transfers - Retail (2.1 to 2.6) 2061014.91 149083.29 202008.61 194925.94 79781976 5845989 8242601 7126205 2.1 AePS (Fund Transfers) @ 3.64 0.29 0.31 0.30 190 19 16 16 2.2 APBS $ 32964.43 2535.32 3506.60 2610.51 554034 36959 66841 57566 2.3 IMPS 56249.68 5503.65 4616.39 4492.53 7139110 592279 667813 621666 2.4 NACH Cr $ 16938.86 964.06 1861.26 1200.84 1670223 121718 176401 154683 2.5 NEFT 96198.05 7040.03 9008.97 7687.52 44361464 3130549 4854308 3897348 2.6 UPI @ 1858660.25 133039.94 183015.08 178934.24 26056955 1964465 2477222 2394926 2.6.1 of which USSD @ 17.24 1.52 1.26 1.22 185 18 14 13 3 Debit Transfers and Direct Debits (3.1 to 3.3) 21659.95 1644.10 1891.35 1869.90 2208583 159006 211047 198565 3.1 BHIM Aadhaar Pay @ 230.08 20.50 19.59 17.39 6907 563 611 601 3.2 NACH Dr $ 19762.28 1494.37 1724.79 1709.27 2199327 158223 210246 197780 3.3 NETC (linked to bank account) @ 1667.59 129.23 146.97 143.24 2349 220 191 184 4 Card Payments (4.1 to 4.2) 63861.15 4960.12 5789.52 5673.64 2605110 200409 240549 222351 4.1 Credit Cards (4.1.1 to 4.1.2) 47740.76 3441.51 4586.50 4502.70 2109197 156498 201494 184237 4.1.1 PoS based $ 24571.10 1843.36 2302.66 2281.41 795022 61982 71473 67899 4.1.2 Others $ 23169.66 1598.15 2283.84 2221.29 1314175 94516 130021 116338 4.2 Debit Cards (4.2.1 to 4.2.1 ) 16120.39 1518.61 1203.02 1170.93 495914 43911 39055 38113 4.2.1 PoS based $ 11980.33 1126.31 895.82 875.30 332556 30022 25818 26187 4.2.2 Others $ 4140.06 392.30 307.20 295.63 163358 13889 13237 11926 5 Prepaid Payment Instruments (5.1 to 5.2) 70254.08 5288.79 6783.69 6768.43 216751 14964 21465 21254 5.1 Wallets 52898.40 3993.29 5061.17 5157.38 154066 10507 16077 15896 5.2 Cards (5.2.1 to 5.2.2) 17355.68 1295.49 1722.52 1611.04 62686 4457 5388 5358 5.2.1 PoS based $ 8240.14 695.13 648.24 649.25 11512 962 1016 1093 5.2.2 Others $ 9115.54 600.37 1074.28 961.79 51174 3495 4372 4265 6 Paper-based Instruments (6.1 to 6.2) 6095.38 525.73 531.76 494.77 7113350 667829 659873 645079 6.1 CTS (NPCI Managed) 6095.38 525.73 531.76 494.77 7113350 667829 659873 645079 6.2 Others 0.00 – – – – – – – Total - Retail Payments (2+3+4+5+6) 2222885.46 161502.02 217004.93 209732.67 91925771 6888198 9375535 8213454 Total Payments (1+2+3+4+5+6) 2225910.01 161737.61 217311.96 209995.08 293313453 21321494 30777505 25109243 Total Digital Payments (1+2+3+4+5) 2219814.63 161211.88 216780.20 209500.31 286200103 20653665 30117631 24464164 RBI Bulletin June 2025 153CURRENT STATISTICS PART II - Payment Modes and Channels System Volume (Lakh) Value (₹ Crore) FY 2024-25 2024 2025 FY 2024-25 2024 2025 Apr. Mar. Apr. Apr. Mar. Apr. 1 2 3 4 5 6 7 8 A. Other Payment Channels 1 Mobile Payments (mobile app based) (1.1 to 1.2) 1756976.91 127302.31 171174.23 165744.58 39206221 2962262 3769671 3498574 1.1 Intra-bank $ 110801.96 8373.78 9863.76 9301.40 7207439 552044 670272 617100 1.2 Inter-bank $ 1646174.95 118928.53 161310.47 156443.19 31998782 2410218 3099400 2881474 2 Internet Payments (Netbanking / Internet Browser Based) @ (2.1 to 2.2) 47478.09 3796.75 4096.24 3642.69 131858133 9637480 13992340 11585683 2.1 Intra-bank @ 13056.37 966.25 1009.09 837.78 69086996 5089149 7319249 6047105 2.2 Inter-bank @ 34421.72 2830.50 3087.15 2804.91 62771136 4548332 6673091 5538579 B. ATMs 3 Cash Withdrawal at ATMs $ (3.1 to 3.3) 60308.11 5240.40 4983.78 4602.65 3063077 265905 263892 244747 3.1 Using Credit Cards $ 97.25 9.07 7.43 6.86 5084 458 410 373 3.2 Using Debit Cards $ 59965.70 5207.60 4957.22 4578.06 3046987 264457 262540 243494 3.3 Using Pre-paid Cards $ 245.16 23.73 19.13 17.73 11005 990 942 881 4 Cash Withdrawal at PoS $ (4.1 to 4.2) 3.58 0.52 0.22 0.17 37 5 2 2 4.1 Using Debit Cards $ 3.33 0.50 0.19 0.15 35 5 2 1 4.2 Using Pre-paid Cards $ 0.25 0.02 0.03 0.02 3 0 0 0 5 Cash Withrawal at Micro ATMs @ 11640.55 919.05 1102.31 928.36 296622 24502 29561 25662 5.1 AePS @ 11640.55 919.05 1102.31 928.36 296622 24502 29561 25662 PART III - Payment Infrastructures (Lakh) System As on March 2024 2025 2025 Apr. Mar. Apr. 1 2 3 4 Payment System Infrastructures 1 Number of Cards (1.1 to 1.2) 11006.97 10534.85 11006.97 11064.20 1.1 Credit Cards 1098.85 1025.40 1098.85 1104.36 1.2 Debit Cards 9908.12 9509.45 9908.12 9959.84 2 Number of PPIs @ (2.1 to 2.2) 13396.53 14716.82 13396.53 13444.93 2.1 Wallets @ 8673.62 11294.83 8673.62 8719.54 2.2 Cards @ 4722.91 3421.99 4722.91 4725.39 3 Number of ATMs (3.1 to 3.2) 2.56 2.57 2.56 2.55 3.1 Bank owned ATMs $ 2.20 2.23 2.20 2.19 3.2 White Label ATMs $ 0.36 0.35 0.36 0.36 4 Number of Micro ATMs @ 14.82 17.44 14.82 14.74 5 Number of PoS Terminals 110.98 88.39 110.98 112.91 6 Bharat QR @ 67.18 60.73 67.18 66.84 7 UPI QR * 6579.30 5597.20 6579.30 6624.75 @: New inclusion w.e.f. November 2019 #: Data reported by Co-operative Banks, LABs and RRBs included with effect from December 2021. $ : Inclusion separately initiated from November 2019 - would have been part of other items hitherto. *: New inclusion w.e.f. September 2020; Includes only static UPI QR Code Notes : 1. D ata is provisional. 2. ECS (Debit and Credit) has been merged with NACH with effect from January 31, 2020. 3. The data from November 2019 onwards for card payments (Debit/Credit cards) and Prepaid Payment Instruments (PPIs) may not be comparable with earlier months/ periods, as more granular data is being published along with revision in data definitions. 4. Only domestic financial transactions are considered. The new format captures e-commerce transactions; transactions using FASTags, digital bill payments and card-to-card transfer through ATMs, etc.. Also, failed transactions, chargebacks, reversals, expired cards/ wallets, are excluded. Part I-A. Settlement systems 1.1.3: Tri- party Repo under the securities segment has been operationalised from November 05, 2018. Part I-B. Payments systems 4.1.2: ‘Others’ includes e-commerce transactions and digital bill payments through ATMs, etc. 4.2.2: ‘Others’ includes e-commerce transactions, card to card transfers and digital bill payments through ATMs, etc. 5: Available from December 2010. 5.1: includes purchase of goods and services and fund transfer through wallets. 5.2.2: includes usage of PPI Cards for online transactions and other transactions. 6.1: Pertain to three grids – Mumbai, New Delhi and Chennai. 6.2: ‘Others’ comprises of Non-MICR transactions which pertains to clearing houses managed by 21 banks. Part II-A. Other payment channels 1: Mobile Payments – o Include transactions done through mobile apps of banks and UPI apps. o The data from July 2017 includes only individual payments and corporate payments initiated, processed, and authorised using mobile device. Other corporate payments which are not initiated, processed, and authorised using mobile device are excluded. 2: Internet Payments – includes only e-commerce transactions through ‘netbanking’ and any financial transaction using internet banking website of the bank. Part II-B. ATMs 3.3 and 4.2: only relates to transactions using bank issued PPIs. Part III. Payment systems infrastructure 3: Includes ATMs deployed by Scheduled Commercial Banks (SCBs) and White Label ATM Operators (WLAOs). WLAs are included from April 2014 onwards. 154 RBI Bulletin June 2025CURRENT STATISTICS Occasional Series No. 44: Small Savings (₹ Crore) Scheme 2023-24 2024 2025 Feb. Dec. Jan. Feb. 1 2 3 4 5 1 Small Savings Receipts 232460 14570 11133 12581 11379 Outstanding 1865029 1819758 1982465 1994553 2005585 1.1 Total Deposits Receipts 161344 10025 8734 9178 8077 Outstanding 1298795 1268920 1395484 1404661 1412738 1.1.1 Post Office Saving Bank Deposits Receipts 17229 1520 1090 2702 814 Outstanding 191692 218498 201999 204701 205515 1.1.2 Sukanya Samriddhi Yojna Receipts 35174 2233 2244 2347 2282 Outstanding 157611 109222 177007 179354 181636 1.1.3 National Saving Scheme, 1987 Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.1.4 National Saving Scheme, 1992 Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.1.5 Monthly Income Scheme Receipts 26696 1927 827 1279 1045 Outstanding 269007 267205 282142 283421 284466 1.1.6 Senior Citizen Scheme 2004 Receipts 38167 2153 1531 1922 1952 Outstanding 175472 173476 194605 196527 198479 1.1.7 Post Office Time Deposits Receipts 25341 2632 2125 2853 2108 Outstanding 305776 303000 330912 333764 335872 1.1.7.1 1 year Time Deposits Outstanding 140423 138552 159174 161578 163358 1.1.7.2 2 year Time Deposits Outstanding 11967 11730 14299 14476 14637 1.1.7.3 3 year Time Deposits Outstanding 8932 8782 10308 10487 10645 1.1.7.4 5 year Time Deposits Outstanding 144454 143936 147131 147223 147232 1.1.8 Post Office Recurring Deposits Receipts 18713 -420 1025 -1831 -25 Outstanding 197134 195727 207269 205438 205413 1.1.9 Post Office Cumulative Time Deposits Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.1.10 Other Deposits Receipts 8 -20 -108 -95 -100 Outstanding 1754 1444 1195 1100 1000 1.1.11 PM Care for children Receipts 16 0 0 1 1 Outstanding 349 348 355 356 357 1.2 Saving Certificates Receipts 56069 3940 2226 3019 2858 Outstanding 418021 414597 438074 440601 443112 1.2.1 National Savings Certificate VIII issue Receipts 16853 1446 430 796 762 Outstanding 183905 180181 192621 193417 194179 1.2.2 Indira Vikas Patras Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.2.3 Kisan Vikas Patras Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.2.4 Kisan Vikas Patras - 2014 Receipts 20939 1428 1113 1376 1247 Outstanding 220560 219498 228707 230083 231330 1.2.5 National Saving Certificate VI issue Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.2.6 National Saving Certificate VII issue Receipts 0 0 0 0 0 Outstanding 0 0 0 0 0 1.2.7 M.S. Certificates Receipts 18277 1066 683 847 849 Outstanding 18277 17235 25303 26150 26999 1.2.8 Other Certificates Outstanding -4721 -2317 -8557 -9049 -9396 1.3 Public Provident Fund Receipts 15047 605 173 384 444 Outstanding 148213 136241 148907 149291 149735 Note : Data on receipts from April 2017 are net receipts, i.e., gross receipt minus gross payment. Source: Accountant General, Post and Telegraphs. RBI Bulletin June 2025 155CURRENT STATISTICS No. 45 : Ownership Pattern of Central and State Governments Securities (Per cent) Central Government Dated Securities 2024 2025 Category Mar. Jun. Sep. Dec. Mar. 1 2 3 4 5 (A) Total (in ₹ Crore) 10740389 10946860 11271589 11422728 11642652 1 Commercial Banks 37.66 37.52 37.55 37.98 36.18 2 Co-operative Banks 1.47 1.42 1.35 1.36 1.29 3 Non-Bank PDs 0.66 0.70 0.77 0.65 0.76 4 Insurance Companies 25.98 26.11 25.95 26.14 25.81 5 Mutual Funds 2.90 2.87 3.14 3.11 2.68 6 Provident Funds 4.47 4.41 4.25 4.25 4.24 7 Pension Funds 4.52 4.74 4.86 5.05 4.91 8 Financial Institutions 0.55 0.57 0.63 0.64 0.71 9 Corporates 1.35 1.44 1.60 1.45 1.49 10 Foreign Portfolio Investors 2.34 2.34 2.80 2.81 3.12 11 RBI 12.31 11.92 11.16 10.55 12.78 12 Others 5.79 5.97 5.92 6.01 6.01 12.1 State Governments 2.04 2.13 2.19 2.21 2.25 State Governments Securities 2024 2025 Category Mar. Jun. Sep. Dec. Mar. 1 2 3 4 5 (B) Total (in ₹ Crore) 5646219 5727482 5909490 6055711 6399564 1 Commercial Banks 34.14 33.85 34.39 35.11 35.40 2 Co-operative Banks 3.39 3.38 3.29 3.22 3.08 3 Non-Bank PDs 0.60 0.59 0.60 0.53 0.61 4 Insurance Companies 26.14 25.85 25.56 25.16 24.07 5 Mutual Funds 2.09 2.08 1.93 1.89 1.93 6 Provident Funds 22.35 22.94 23.02 22.90 23.60 7 Pension Funds 4.76 4.87 4.87 4.82 5.07 8 Financial Institutions 1.59 1.58 1.57 1.58 1.48 9 Corporates 2.02 2.03 1.95 1.97 2.05 10 Foreign Portfolio Investors 0.07 0.05 0.04 0.03 0.05 11 RBI 0.63 0.62 0.60 0.58 0.55 12 Others 2.20 2.17 2.18 2.19 2.10 12.1 State Governments 0.25 0.26 0.26 0.26 0.25 Treasury Bills 2024 2025 Category Mar. Jun. Sep. Dec. Mar. 1 2 3 4 5 (C) Total (in ₹ Crore) 871662 858193 747242 760045 790381 1 Commercial Banks 58.53 47.79 44.74 40.45 46.58 2 Co-operative Banks 1.67 1.49 1.58 1.22 2.17 3 Non-Bank PDs 1.66 2.69 2.28 1.41 2.09 4 Insurance Companies 5.06 5.78 5.26 4.73 4.23 5 Mutual Funds 11.89 14.50 15.06 15.41 16.15 6 Provident Funds 0.15 0.60 0.26 0.04 0.20 7 Pension Funds 0.01 0.00 0.00 0.00 0.02 8 Financial Institutions 7.16 6.56 6.36 6.77 7.73 9 Corporates 4.50 4.79 4.66 4.56 4.50 10 Foreign Portfolio Investors 0.01 0.20 0.15 0.12 0.09 11 RBI 0.00 0.00 0.00 0.00 0.00 12 Others 9.36 15.59 19.65 25.29 16.23 12.1 State Governments 5.88 11.55 14.95 20.11 11.23 Notes: (1) The table format is revised since monthly Bulletin for the month of June 2023. (2) Central Government Dated Securities include special securities and Sovereign Gold Bonds. (3) State Government Securities include special bonds issued under Ujwal DISCOM Assurance Yojana (UDAY). (4) Bank PDs are clubbed under Commercial Banks. (5) The category ‘Others’ comprises State Governments, DICGC, PSUs, Trusts, Foreign Central Banks, HUF/ Individuals etc. (6) Data since September 2023 includes the impact of the merger of a non-bank with a bank. 156 RBI Bulletin June 2025CURRENT STATISTICS No. 46: Combined Receipts and Disbursements of the Central and State Governments (₹ Crore) Item 2019-20 2020-21 2021-22 2022-23 2023-24 RE 2024-25 BE 1 2 3 4 5 6 1 Total Disbursements 5410887 6353359 7098451 7880522 9110725 9800798 1.1 Developmental 3074492 3823423 4189146 4701611 5514584 5862996 1.1.1 Revenue 2446605 3150221 3255207 3574503 3965270 4195108 1.1.2 Capital 588233 550358 861777 1042159 1453849 1526993 1.1.3 Loans 39654 122844 72163 84949 95464 140895 1.2 Non-Developmental 2253027 2442941 2810388 3069896 3467270 3800321 1.2.1 Revenue 2109629 2271637 2602750 2895864 3266628 3537378 1.2.1.1 Interest Payments 955801 1060602 1226672 1377807 1562660 1711972 1.2.2 Capital 141457 169155 175519 171131 196073 259346 1.2.3 Loans 1941 2148 32119 2902 4569 3597 1.3 Others 83368 86995 98916 109015 128871 137481 2 Total Receipts 5734166 6397162 7156342 7855370 9054999 9650488 2.1 Revenue Receipts 3851563 3688030 4823821 5447913 6379349 7209647 2.1.1 Tax Receipts 3231582 3193390 4160414 4809044 5456913 6142276 2.1.1.1 Taxes on commodities and services 2012578 2076013 2626553 2865550 3248450 3631569 2.1.1.2 Taxes on Income and Property 1216203 1114805 1530636 1939550 2204462 2506181 2.1.1.3 Taxes of Union Territories (Without Legislature) 2800 2572 3225 3943 4001 4526 2.1.2 Non-Tax Receipts 619981 494640 663407 638870 922436 1067371 2.1.2.1 Interest Receipts 31137 33448 35250 42975 49552 57273 2.2 Non-debt Capital Receipts 110094 64994 44077 62716 86733 118239 2.2.1 Recovery of Loans & Advances 59515 16951 27665 15970 55895 45125 2.2.2 Disinvestment proceeds 50578 48044 16412 46746 30839 73114 3 Gross Fiscal Deficit [ 1 - ( 2.1 + 2.2 ) ] 1449230 2600335 2230553 2369892 2644642 2472912 3A Sources of Financing: Institution-wise 3A.1 Domestic Financing 1440548 2530155 2194406 2332768 2619811 2456959 3A.1.1 Net Bank Credit to Government 571872 890012 627255 687904 346483 ... 3A.1.1.1 Net RBI Credit to Government 190241 107493 350911 529 -257913 ... 3A.1.2 Non-Bank Credit to Government 868676 1640143 1567151 1644864 2273328 ... 3A.2 External Financing 8682 70180 36147 37124 24832 15952 3B Sources of Financing: Instrument-wise 3B.1 Domestic Financing 1440548 2530155 2194406 2332768 2619811 2456959 3B.1.1 Market Borrowings (net) 971378 1696012 1213169 1651076 1962969 1983757 3B.1.2 Small Savings (net) 209232 458801 526693 358764 434151 447511 3B.1.3 State Provident Funds (net) 38280 41273 28100 13880 21386 19857 3B.1.4 Reserve Funds 10411 4545 42153 68803 52385 -33653 3B.1.5 Deposits and Advances -14227 25682 42203 51989 35819 -10138 3B.1.6 Cash Balances -323279 -43802 -57891 25152 55726 150310 3B.1.7 Others 548753 347643 399980 163104 57374 -100684 3B.2 External Financing 8682 70180 36147 37124 24832 15952 4 Total Disbursements as per cent of GDP 26.9 32.0 30.1 29.2 30.8 30.0 5 Total Receipts as per cent of GDP 28.5 32.2 30.3 29.1 30.7 29.6 6 Revenue Receipts as per cent of GDP 19.2 18.6 20.4 20.2 21.6 22.1 7 Tax Receipts as per cent of GDP 16.1 16.1 17.6 17.8 18.5 18.8 8 Gross Fiscal Deficit as per cent of GDP 7.2 13.1 9.5 8.8 9.0 7.6 … : Not available; RE: Revised Estimates; BE: Budget Estimates Source : Budget Documents of Central and State Governments. Notes: GDP data is based on 2011-12 base. GDP for 2024-25 is from Union Budget 2024-25. Data pertains to all States and Union Territories. 1 & 2: Data are net of repayments of the Central Government (including repayments to the NSSF) and State Governments. 1.3: Represents compensation and assignments by States to local bodies and Panchayati Raj institutions. 2: Data are net of variation in cash balances of the Central and State Governments and includes borrowing receipts of the Central and State Governments. 3A.1.1: Data as per RBI records. 3B.1.1: Borrowings through dated securities. 3B.1.2: Represent net investment in Central and State Governments’ special securities by the National Small Savings Fund (NSSF). This data may vary from previous publications due to adjustments across components with availability of new data. 3B.1.6: Include Ways and Means Advances by the Centre to the State Governments. 3B.1.7: Include Treasury Bills, loans from financial institutions, insurance and pension funds, remittances, cash balance investment account. RBI Bulletin June 2025 157CURRENT STATISTICS No. 47: Financial Accommodation Availed by State Governments under various Facilities (₹ Crore) During April-2025 Sr. State/Union Territory Special Drawing Ways and Means Overdraft (OD) No Facility (SDF) Advances (WMA) Average Number Average Number Average Number amount of days amount of days amount of days availed availed availed availed availed availed 1 2 3 4 5 6 7 1 Andhra Pradesh 4421.65 30 1230.88 11 2683.97 3 2 Arunachal Pradesh - - - - - - 3 Assam 618.47 16 - - - - 4 Bihar - - - - - - 5 Chhattisgarh - - - - - - 6 Goa - - - - - - 7 Gujarat - - - - - - 8 Haryana 159.83 1 - - - - 9 Himachal Pradesh - - 694.25 29 383.18 18 10 Jammu & Kashmir UT 17.78 16 1231.09 15 529.29 12 11 Jharkhand 883.91 10 - - - - 12 Karnataka - - - - - - 13 Kerala 1285.75 27 708.91 17 - - 14 Madhya Pradesh - - - - - - 15 Maharashtra 10183.89 21 - - - - 16 Manipur 76.44 24 73.91 11 - - 17 Meghalaya 658.41 30 246.23 11 308.13 10 18 Mizoram - - - - - - 19 Nagaland 136.56 17 - - - - 20 Odisha - - - - - - 21 Puducherry - - - - - - 22 Punjab 4682.69 30 1109.63 26 625.67 12 23 Rajasthan 3030.42 28 1006.65 10 - - 24 Tamil Nadu - - - - - - 25 Telangana 4881.13 30 1489.30 25 2693.24 9 26 Tripura - - - - - - 27 Uttar Pradesh - - - - - - 28 Uttarakhand 1060.37 30 - - - - 29 West Bengal - - - - - - Notes: 1. SDF is availed by State Governments against the collateral of Consolidated Sinking Fund (CSF), Guarantee Redemption Fund (GRF) & Auction Treasury Bills (ATBs) balances and other investments in government securities. 2. WMA is advance by Reserve Bank of India to State Governments for meeting temporary cash mismatches. 3. OD is advanced to State Governments beyond their WMA limits. 4. Average amount availed is the total accommodation (SDF/WMA/OD) availed divided by number of days for which accommodation was extended during the month. 5. - : Nil. Source: Reserve Bank of India. 158 RBI Bulletin June 2025CURRENT STATISTICS No. 48: Investments by State Governments (₹ Crore) As on end of April 2025 Consolidated Guarantee Sr. State/Union Government Auction Treasury Sinking Fund Redemption Fund No Territory Securities Bills (ATBs) (CSF) (GRF) 1 2 3 4 5 1 Andhra Pradesh 11771 1160 0 0 2 Arunachal Pradesh 2799 7 0 1800 3 Assam 7506 92 0 0 4 Bihar 12683 - 0 15500 5 Chhattisgarh 8364 973 0 5495 6 Goa 1096 465 0 0 7 Gujarat 15525 678 0 2500 8 Haryana 2654 1735 0 0 9 Himachal Pradesh - - 0 0 10 Jammu & Kashmir UT 37 36 0 0 11 Jharkhand 2444 - 0 780 12 Karnataka 20601 762 0 50177 13 Kerala 3278 - 0 0 14 Madhya Pradesh - 1296 0 1500 15 Maharashtra 72941 2187 0 0 16 Manipur 70 143 0 0 17 Meghalaya 1295 110 0 0 18 Mizoram 513 81 0 0 19 Nagaland 1924 47 0 0 20 Odisha 18582 2081 0 4258 21 Puducherry 590 - 0 1650 22 Punjab 9285 0 0 0 23 Rajasthan 1822 - 0 7750 24 Tamil Nadu 3494 - 0 2137 25 Telangana 8032 1761 0 0 26 Tripura 1339 30 0 0 27 Uttarakhand 5392 262 0 0 28 Uttar Pradesh 12825 1590 0 0 29 West Bengal 14052 1051 0 3000 Total 240916 16548 0 96546 Notes: 1. CSF and GRF are reserve funds maintained by some State Governments with the Reserve Bank of India. 2. ATBs include investment by State Governments in Treasury bills of 91 days, 182 days and 364 days in the primary market. 3. - : Not Applicable (not a member of the scheme). RBI Bulletin June 2025 159CURRENT STATISTICS No. 49: Market Borrowings of State Governments (₹ Crore) 2024-25 2025-26 Total amount 2023-24 2024-25 raised, so far in February March April 2025-26 Sr. No. State Gross Net Gross Net Gross Net Gross Net Gross Net Amount Amount Amount Amount Amount Amount Amount Amount Amount Amount Gross Net Raised Raised Raised Raised Raised Raised Raised Raised Raised Raised 1 2 3 4 5 6 7 8 9 10 11 12 13 1 Andhra Pradesh 68400 55330 78205 57123 6820 5820 8148 7148 5750 4750 5750 4750 2 Arunachal Pradesh 902 672 1010 704 - - 215 135 - -130 - -130 3 Assam 18500 16000 19000 13850 3650 2650 3300 1800 900 -50 900 -50 4 Bihar 47612 29910 47546 30890 7546 6946 - -478 - - - - 5 Chhattisgarh 32000 26213 24500 16913 4000 2000 14000 12613 1970 1970 1970 1970 6 Goa 2550 1560 1050 250 - - - - - -150 - -150 7 Gujarat 30500 11947 38200 16280 9700 5580 8000 5000 - -2560 - -2560 8 Haryana 47500 28364 49500 31710 4500 2750 12000 5690 2000 2000 2000 2000 9 Himachal Pradesh 8072 5856 7359 4725 - -384 659 659 2200 1550 2200 1550 10 Jammu & Kashmir UT 16337 13904 13170 11416 200 200 300 86 1000 1000 1000 1000 11 Jharkhand 1000 -2505 3500 -2005 - - 3500 1445 - - - - 12 Karnataka 81000 63003 92025 71525 13000 10000 20000 19000 - - - - 13 Kerala 42438 26638 53666 37966 4920 3920 12744 11744 2000 - 2000 - 14 Madhya Pradesh 38500 26264 63400 47206 6000 5000 22400 15306 - - - - 15 Maharashtra 110000 79738 123000 90917 14000 9617 24000 24000 13500 13500 13500 13500 16 Manipur 1426 1076 1500 1037 250 147 250 250 - -200 - -200 17 Meghalaya 1364 912 1882 997 - -125 - -73 350 250 350 250 18 Mizoram 901 641 1169 939 119 119 120 120 - - - - 19 Nagaland 2551 2016 1550 950 - -100 1000 850 - - - - 20 Odisha 0 -4658 20780 17780 7000 7000 11780 10780 - - - - 21 Puducherry 1100 475 1600 880 400 400 300 280 - - - - 22 Punjab 42386 29517 40828 32466 2000 1250 1998 540 5800 4200 5800 4200 23 Rajasthan 73624 49718 75185 49479 6000 4326 11620 5670 5500 3500 5500 3500 24 Sikkim 1916 1701 1951 1621 488 388 463 363 - - - - 25 Tamil Nadu 113001 75970 123625 89894 13000 9500 22600 20219 4000 1000 4000 1000 26 Telangana 49618 39385 56209 42199 3000 2000 6500 3608 4400 3400 4400 3400 27 Tripura 0 -550 0 -150 - - - -150 500 500 500 500 28 Uttar Pradesh 97650 85335 45000 23185 9000 5000 10000 7472 3000 -1000 3000 -1000 29 Uttarakhand 6300 3800 10400 8000 2000 2000 4000 3250 1000 1000 1000 1000 30 West Bengal 69910 48910 76500 54600 5000 2500 25000 23700 - -1000 - -1000 Grand Total 1007058 717140 1073310 753345 122593 88504 224897 181026 53870 33530 53870 33530 - : Nil. Note: The State of J&K has ceased to exist constitutionally from October 31, 2019 and the liabilities of the State continue to remain as liabilities of the new UT of Jammu and Kashmir. Source: Reserve Bank of India. 160 RBI Bulletin June 2025CURRENT STATISTICS No. 50 (a): Flow of Financial Assets and Liabilities of Households - Instrument-wise (Amount in ` Crore) 2021-22 Item Q1 Q2 Q3 Q4 Annual Net Financial Assets (I-II) 3,42,813 3,30,490 4,85,203 5,54,816 17,13,322 Per cent of GDP 6.6 5.9 7.7 8.5 7.3 I. Financial Assets 3,63,395 5,25,419 8,16,484 9,07,366 26,12,664 Per cent of GDP 7.0 9.3 13.0 13.9 11.1 of which: 1.Total Deposits (a)+(b) (81,064) 2,04,486 4,28,035 2,83,634 8,35,091 (a) Bank Deposits (1,06,429) 1,97,105 4,22,393 2,70,025 7,83,094 i. Commercial Banks (1,07,941) 1,95,442 4,18,267 2,62,326 7,68,094 ii. Co-operative Banks 1,512 1,663 4,126 7,699 15,000 (b) Non-Bank Deposits 25,365 7,380 5,642 13,610 51,997 of which: Other Financial Institutions (i+ii) 17,555 (435) (2,178) 5,770 20,712 i. Non-Banking Financial Companies 5,578 (1,371) 73 4,021 8,302 ii. Housing Finance Companies 11,977 936 (2,252) 1,748 12,410 2. Life Insurance Funds 1,15,539 1,28,277 1,04,076 1,38,998 4,86,889 3. Provident and Pension Funds (including PPF) 1,24,971 1,12,810 95,493 2,18,719 5,51,993 4. Currency 1,28,660 (68,631) 62,793 1,46,845 2,69,667 5. Investments 24,884 82,260 69,715 50,926 2,27,785 of which: (a) Mutual Funds 14,573 63,151 37,912 44,964 1,60,600 (b) Equity 4,502 13,218 27,808 3,084 48,613 6. Small Savings (excluding PPF) 50,405 66,218 56,372 68,243 2,41,238 II. Financial Liabilities 20,583 1,94,929 3,31,281 3,52,550 8,99,343 Per cent of GDP 0.4 3.5 5.3 5.4 3.8 Loans (Borrowings) from 1. Financial Corporations (a+b) 20,479 1,94,825 3,31,178 3,52,446 8,98,928 (a) Banking Sector 21,428 1,38,720 2,67,955 2,74,181 7,02,284 of which: i. Commercial Banks 26,979 1,40,269 2,65,271 3,37,010 7,69,529 (b) Other Financial Institutions (949) 56,105 63,223 78,266 1,96,644 i. Non-Banking Financial Companies (8,708) 30,151 32,177 40,003 93,623 ii. Housing Finance Companies 7,132 24,404 29,495 37,436 98,467 iii. Insurance Corporations 627 1,550 1,551 827 4,554 2. Non-Financial Corporations (Private 34 34 34 34 135 Corporate Business) 3. General Government 70 70 70 70 279 RBI Bulletin June 2025 161CURRENT STATISTICS No. 50 (a): Flow of Financial Assets and Liabilities of Households - Instrument-wise (Contd.) (Amount in ` Crore) 2022-23 Item Q1 Q2 Q3 Q4 Annual Net Financial Assets (I-II) 2,89,980 2,99,395 2,96,132 4,54,240 13,39,748 Per cent of GDP 4.5 4.6 4.3 6.4 5.0 I. Financial Assets 5,79,958 6,34,471 7,50,245 9,71,526 29,36,200 Per cent of GDP 8.9 9.8 10.9 13.6 10.9 of which: 1.Total Deposits (a)+(b) 1,85,429 3,17,361 2,80,233 3,25,853 11,08,876 (a) Bank Deposits 1,63,172 2,99,533 2,56,400 3,07,867 10,26,971 i. Commercial Banks 1,58,613 3,00,565 2,48,460 2,84,968 9,92,606 ii. Co-operative Banks 4,559 (1,032) 7,940 22,899 34,365 (b) Non-Bank Deposits 22,257 17,829 23,833 17,986 81,905 of which: Other Financial Institutions (i+ii) 6,505 2,077 8,082 2,234 18,897 i. Non-Banking Financial Companies 4,231 3,267 3,247 3,946 14,690 ii. Housing Finance Companies 2,274 (1,191) 4,835 (1,712) 4,207 2. Life Insurance Funds 73,298 1,51,677 1,67,522 1,56,613 5,49,109 3. Provident and Pension Funds (including PPF) 1,48,915 1,20,367 1,38,584 2,18,709 6,26,575 4. Currency 66,439 (54,579) 76,760 1,48,990 2,37,610 5. Investments 51,503 48,530 49,779 64,151 2,13,962 of which: (a) Mutual Funds 35,443 44,484 40,206 58,955 1,79,088 (b) Equity 13,561 1,378 6,434 1,665 23,038 6. Small Savings (excluding PPF) 54,375 51,115 37,368 57,211 2,00,068 II. Financial Liabilities 2,89,978 3,35,076 4,54,113 5,17,285 15,96,452 Per cent of GDP 4.5 5.2 6.6 7.3 5.9 Loans (Borrowings) from 1. Financial Corporations (a+b) 2,89,781 3,34,880 4,53,917 5,17,089 15,95,667 (a) Banking Sector 2,34,235 2,63,450 3,70,783 3,83,845 12,52,313 of which: i. Commercial Banks 2,30,284 2,61,265 3,68,305 3,31,293 11,91,146 (b) Other Financial Institutions 55,546 71,429 83,134 1,33,244 3,43,354 i. Non-Banking Financial Companies 30,532 36,650 55,792 94,565 2,17,539 ii. Housing Finance Companies 22,337 33,031 24,903 36,746 1,17,017 iii. Insurance Corporations 2,678 1,748 2,439 1,933 8,798 2. Non-Financial Corporations (Private 34 34 34 34 135 Corporate Business) 3. General Government 163 163 163 163 650 162 RBI Bulletin June 2025CURRENT STATISTICS No. 50 (a): Flow of Financial Assets and Liabilities of Households - Instrument-wise (Concld.) (Amount in ` Crore) 2023-24 Item Q1 Q2 Q3 Q4 Annual Net Financial Assets (I-II) 3,53,093 2,89,675 2,98,111 6,11,366 15,52,245 Per cent of GDP 5.0 4.1 3.9 7.8 5.3 I. Financial Assets 6,74,763 8,15,842 8,08,779 11,32,130 34,31,514 Per cent of GDP 9.6 11.5 10.7 14.5 11.6 of which: 1.Total Deposits (a)+(b) 2,68,925 4,12,388 2,99,372 4,10,559 13,91,244 (a) Bank Deposits 2,55,249 5,06,208 2,79,872 3,94,573 14,35,902 i. Commercial Banks 2,46,079 5,06,700 2,82,537 3,87,313 14,22,629 ii. Co-operative Banks 9,170 (492) (2,665) 7,260 13,273 (b) Non-Bank Deposits 13,676 (93,820) 19,499 15,986 (44,658) of which: Other Financial Institutions (i+ii) (485) (1,07,982) 5,338 1,825 (1,01,305) i. Non-Banking Financial Companies 6,119 4,782 4,896 1,943 17,740 ii. Housing Finance Companies (6,605) (1,12,764) 442 (118) (1,19,045) 2. Life Insurance Funds 1,58,358 1,41,413 1,61,192 1,30,036 5,90,999 3. Provident and Pension Funds (including PPF) 1,63,508 1,48,178 1,53,255 2,53,719 7,18,661 4. Currency (48,636) (36,701) 56,719 1,46,644 1,18,026 5. Investments 41,409 73,060 79,633 1,08,732 3,02,834 of which: (a) Mutual Funds 32,086 55,769 60,135 90,973 2,38,962 (b) Equity 3,757 7,146 9,941 8,236 29,080 6. Small Savings (excluding PPF) 91,198 77,504 58,607 82,441 3,09,751 II. Financial Liabilities 3,21,670 5,26,167 5,10,667 5,20,764 18,79,269 Per cent of GDP 4.6 7.4 6.7 6.7 6.4 Loans (Borrowings) from 1. Financial Corporations (a+b) 3,21,520 5,26,016 5,10,516 5,20,613 18,78,666 (a) Banking Sector 2,13,606 8,68,874 4,02,647 3,92,330 18,77,458 of which: i. Commercial Banks 2,08,027 8,75,654 3,89,898 3,82,558 18,56,136 (b) Other Financial Institutions 1,07,914 (3,42,858) 1,07,869 1,28,283 1,208 i. Non-Banking Financial Companies 81,449 59,684 85,032 1,00,836 3,27,001 ii. Housing Finance Companies 23,784 (4,04,294) 21,233 25,853 (3,33,424) iii. Insurance Corporations 2,681 1,753 1,604 1,594 7,631 2. Non-Financial Corporations (Private 34 35 35 35 138 Corporate Business) 3. General Government 116 116 116 116 465 Notes : 1. Net Financial Savings of households refer to the net financial assets, which are measured as difference of financial asset and liabilities flows. 2. Preliminary estimates for 2023-24 and revised estimates for 2021-22 and 2022-23. 3. The preliminary estimates for 2023-24 will undergo revision with the release of first revised estimates of national income, consumption expenditure, savings, and capital formation, 2023-24 by the National Statistical Office (NSO). 4. Non-bank deposits apart from other financial institutions, comprises state power utilities, co-operative non credit societies etc. 5. Figures in the columns may not add up to the total due to rounding off. RBI Bulletin June 2025 163CURRENT STATISTICS No. 50 (b): Stocks of Financial Assets and Liabilities of Households- Select Indicators (Amount in ` Crore) Item Jun-2021 Sep-2021 Dec-2021 Mar-2022 Financial Assets (a+b+c+d+e+f+g+h) 2,33,27,377 2,39,99,280 2,47,08,474 2,54,40,650 Per cent of GDP 110.4 108.9 108.2 107.8 (a) Bank Deposits (i+ii) 1,07,90,832 1,09,87,937 1,14,10,330 1,16,80,355 i. Commercial Banks 99,53,044 1,01,48,486 1,05,66,753 1,08,29,079 ii. Co-operative Banks 8,37,788 8,39,451 8,43,577 8,51,276 (b) Non-Bank Deposits of which: Other Financial Institutions 2,06,509 2,06,074 2,03,896 2,09,665 i. Non-Banking Financial Companies 67,840 66,469 66,542 70,564 ii. Housing Finance Companies 1,38,669 1,39,605 1,37,353 1,39,102 (c) Life Insurance Funds 49,29,725 51,42,279 52,13,527 53,57,350 (d) Currency 27,42,897 26,74,266 27,37,059 28,83,904 (e) Mutual funds 18,55,000 20,64,364 21,26,112 21,52,141 (f) Public Provident Fund (PPF) 7,57,398 7,62,264 7,67,287 8,34,148 (g) Pension Funds 6,16,517 6,67,379 6,99,173 7,36,592 (h) Small Savings (excluding PPF) 14,28,499 14,94,717 15,51,089 15,86,496 Financial Liabilities (a+b) 77,43,630 79,38,456 82,69,633 86,22,079 Per cent of GDP 36.6 36.0 36.2 36.5 Loans/Borrowings (a) Banking Sector 61,80,377 63,19,097 65,87,052 68,61,233 of which: i. Commercial Banks 56,47,239 57,87,508 60,52,779 63,89,789 ii. Co-operative Banks 5,31,728 5,30,164 5,32,833 4,69,989 (b) Other Financial Institutions 15,63,253 16,19,358 16,82,581 17,60,847 of which: i. Non-Banking Financial Companies 7,36,312 7,66,463 7,98,641 8,38,643 ii. Housing Finance Companies 7,21,510 7,45,914 7,75,408 8,1 2,845 iii. Insurance Corporations 1,05,431 1,06,981 1,08,532 1,09,359 164 RBI Bulletin June 2025CURRENT STATISTICS No. 50 (b): Stocks of Financial Assets and Liabilities of Households- Select Indicators (Contd.) (Amount in ` Crore) Item Jun-2022 Sep-2022 Dec-2022 Mar-2023 Financial Assets (a+b+c+d+e+f+g+h) 2,56,21,348 2,64,23,992 2,71,87,716 2,78,44,981 Per cent of GDP 102.8 102.6 103.2 103.3 (a) Bank Deposits (i+ii) 1,18,43,527 1,21,43,060 1,23,99,459 1,27,07,326 i. Commercial Banks 1,09,87,692 1,12,88,257 1,15,36,717 1,18,21,685 ii. Co-operative Banks 8,55,835 8,54,803 8,62,742 8,85,641 (b) Non-Bank Deposits of which: Other Financial Institutions 2,16,170 2,18,247 2,26,328 2,28,562 i. Non-Banking Financial Companies 74,794 78,061 81,308 85,254 ii. Housing Finance Companies 1,41,376 1,40,185 1,45,020 1,43,308 (c) Life Insurance Funds 53,25,967 55,59,682 57,86,593 57,95,431 (d) Currency 29,50,343 28,95,764 29,72,524 31,21,514 (e) Mutual funds 20,48,097 22,60,210 23,55,316 23,67,793 (f) Public Provident Fund (PPF) 8,51,913 8,58,591 8,64,731 9,39,449 (g) Pension Funds 7,44,459 7,96,454 8,53,412 8,98,343 (h) Small Savings (excluding PPF) 16,40,871 16,91,985 17,29,353 17,86,563 Financial Liabilities (a+b) 89,11,861 92,46,741 97,00,657 1,02,17,746 Per cent of GDP 35.8 35.9 36.8 37.9 Loans/Borrowings (a) Banking Sector 70,95,468 73,58,918 77,29,701 81,13,546 of which: i. Commercial Banks 66,20,073 68,81,338 72,49,643 75,80,936 ii. Co-operative Banks 4,73,897 4,76,025 4,78,487 5,30,915 (b) Other Financial Institutions 18,16,393 18,87,823 19,70,956 21,04,201 of which: i. Non-Banking Financial Companies 8,69,175 9,05,825 9,61,617 10,56,182 ii. Housing Finance Companies 8,35,181 8,68,213 8,93,116 9,29,862 iii. Insurance Corporations 1,12,037 1,13,785 1,16,223 1,18,157 RBI Bulletin June 2025 165CURRENT STATISTICS No. 50 (b): Stocks of Financial Assets and Liabilities of Households- Select Indicators (Concld.) (Amount in ` Crore) Item Jun-2023 Sep-2023 Dec-2023 Mar-2024 Financial Assets (a+b+c+d+e+f+g+h) 2,87,56,851 2,96,44,299 3,07,47,010 3,19,86,847 Per cent of GDP 104.6 105.4 106.6 108.3 (a) Bank Deposits (i+ii) 1,29,62,575 1,34,68,783 1,37,48,656 1,41,43,228 i. Commercial Banks 1,20,67,764 1,25,74,464 1,28,57,001 1,32,44,314 ii. Co-operative Banks 8,94,811 8,94,319 8,91,655 8,98,914 (b) Non-Bank Deposits of which: Other Financial Institutions 2,28,077 1,20,095 1,25,432 1,27,257 i. Non-Banking Financial Companies 91,373 96,156 1,01,051 1,02,994 ii. Housing Finance Companies 1,36,703 23,939 24,381 24,263 (c) Life Insurance Funds 60,64,437 62,55,801 65,53,726 67,69,272 (d) Currency 30,72,878 30,36,177 30,92,896 32,39,540 (e) Mutual funds 26,26,046 28,29,859 31,56,299 33,87,208 (f) Public Provident Fund (PPF) 9,55,061 9,60,344 9,64,852 10,51,376 (g) Pension Funds 9,70,016 10,17,975 10,91,276 11,72,651 (h) Small Savings (excluding PPF) 18,77,761 19,55,265 20,13,873 20,96,314 Financial Liabilities (a+b) 1,05,39,266 1,10,65,282 1,15,75,799 1,20,96,412 Per cent of GDP 38.3 39.3 40.2 41.0 Loans/Borrowings (a) Banking Sector 83,27,152 91,96,026 95,98,673 99,91,003 of which: i. Commercial Banks 77,88,962 86,64,616 90,54,514 94,37,072 ii. Co-operative Banks 5,36,409 5,29,528 5,42,241 5,51,852 (b) Other Financial Institutions 22,12,114 18,69,256 19,77,126 21,05,409 of which: i. Non-Banking Financial Companies 11,37,631 11,97,315 12,82,347 13,83,183 ii. Housing Finance Companies 9,53,646 5,49,352 5,70,585 5,96,438 iii. Insurance Corporations 1,20,837 1,22,590 1,24,194 1,25,788 Notes : 1. Data as ratios to GDP have been calculated based on the Provisional Estimates of National Income 2023-24, released by NSO on May 31, 2024. 2. Pension funds comprises funds with the National Pension Scheme. 3. Outstanding deposits with Small Savings are sourced from the Controller General of Accounts, Government of India. 4. Non-bank deposits apart from other financial institutions, comprises state power utilities, co-operative non credit societies etc. Data for outstanding deposits are available only for other financial institutions. 5. Figures in the columns may not add up to the total due to rounding off. 166 RBI Bulletin June 2025CURRENT STATISTICS Explanatory Notes to the Current Statistics Table No. 1 1.2& 6: Annual data are average of months. 3.5 & 3.7: Relate to ratios of increments over financial year so far. 4.1 to 4.4, 4.8,4.9 &5: Relate to the last friday of the month/financial year. 4.5, 4.6 & 4.7: Relate to five major banks on the last Friday of the month/financial year. 4.10 to 4.12: Relate to the last auction day of the month/financial year. 4.13: Relate to last day of the month/ financial year 7.1&7.2: Relate to Foreign trade in US Dollar. Table No. 2 2.1.2: Include paid-up capital, reserve fund and Long-Term Operations Funds. 2.2.2: Include cash, fixed deposits and short-term securities/bonds, e.g., issued by IIFC (UK). Table No. 4 Maturity-wise position of outstanding forward contracts is available at http://nsdp.rbi.org.in under ‘‘Reserves Template’’. Table No. 5 Special refinance facility to Others, i.e. to the EXIM Bank, is closed since March 31, 2013. Table No. 6 For scheduled banks, March-end data pertain to the last reporting Friday. 2.2: Exclude balances held in IMF Account No.1, RBI employees’ provident fund, pension fund, gratuity and superannuation fund. Table Nos. 7 & 11 3.1 in Table 7 and 2.4 in Table 11: Include foreign currency denominated bonds issued by IIFC (UK). Table No. 8 NM and NM do not include FCNR (B) deposits. 2 3 2.4: Consist of paid-up capital and reserves. 2.5: includes other demand and time liabilities of the banking system. Table No. 9 Financial institutions comprise EXIM Bank, SIDBI, NABARD and NHB. L and L are compiled monthly and L quarterly. 1 2 3 Wherever data are not available, the last available data have been repeated. Table No. 13 Data against column Nos. (1), (2) & (3) are Final and for column Nos. (4) & (5) data are Provisional. RBI Bulletin June 2025 167CURRENT STATISTICS Table No. 14 Data in column Nos. (4) & (8) are Provisional. Table No. 17 2.1.1: Exclude reserve fund maintained by co-operative societies with State Co-operative Banks 2.1.2: Exclude borrowings from RBI, SBI, IDBI, NABARD, notified banks and State Governments. 4: Include borrowings from IDBI and NABARD. Table No. 24 Primary Dealers (PDs) include banks undertaking PD business. Table No. 30 Exclude private placement and offer for sale. 1: Exclude bonus shares. 2: Include cumulative convertible preference shares and equi-preference shares. Table No. 32 Exclude investment in foreign currency denominated bonds issued by IIFC (UK), SDRs transferred by Government of India to RBI and foreign currency received under SAARC and ACU currency swap arrangements. Foreign currency assets in US dollar take into account appreciation/depreciation of non-US currencies (such as Euro, Sterling, Yen and Australian Dollar) held in reserves. Foreign exchange holdings are converted into rupees at rupee-US dollar RBI holding rates. Table No. 34 1.1.1.1.2 & 1.1.1.1.1.4: Estimates. 1.1.1.2: Estimates for latest months. ‘Other capital’ pertains to debt transactions between parent and subsidiaries/branches of FDI enterprises. Data may not tally with the BoP data due to lag in reporting. Table No. 35 1.10: Include items such as subscription to journals, maintenance of investment abroad, student loan repayments and credit card payments. Table No. 36 Increase in indices indicates appreciation of rupee and vice versa. For 6-Currency index, base year 2022-23 is a moving one, which gets updated every year. REER figures are based on Consumer Price Index (combined). The details on methodology used for compilation of NEER/REER indices are available in December 2005, April 2014 and January 2021 issues of the RBI Bulletin. Table No. 37 Based on applications for ECB/Foreign Currency Convertible Bonds (FCCBs) which have been allotted loan registration number during the period. 168 RBI Bulletin June 2025CURRENT STATISTICS Table Nos. 38, 39, 40 & 41 Explanatory notes on these tables are available in December issue of RBI Bulletin, 2012. Table No. 43 Part I-A. Settlement systems 1.1.3: Tri- party Repo under the securities segment has been operationalised from November 05, 2018. Part I-B. Payments systems 4.1.2: ‘Others’ includes e-commerce transactions and digital bill payments through ATMs, etc. 4.2.2: ‘Others’ includes e-commerce transactions, card to card transfers and digital bill payments through ATMs, etc. 5: Available from December 2010. 5.1: includes purchase of goods and services and fund transfer through wallets. 5.2.2: includes usage of PPI Cards for online transactions and other transactions. 6.1: Pertain to three grids – Mumbai, New Delhi and Chennai. 6.2: ‘Others’ comprises of Non-MICR transactions which pertains to clearing houses managed by 21 banks. Part II-A. Other payment channels 1: Mobile Payments – Include transactions done through mobile apps of banks and UPI apps. o The data from July 2017 includes only individual payments and corporate payments initiated, o processed, and authorised using mobile device. Other corporate payments which are not initiated, processed, and authorised using mobile device are excluded. 2: Internet Payments – includes only e-commerce transactions through ‘netbanking’ and any financial transaction using internet banking website of the bank. Part II-B. ATMs 3.3 and 4.2: only relates to transactions using bank issued PPIs. Part III. Payment systems infrastructure 3: Includes ATMs deployed by Scheduled Commercial Banks (SCBs) and White Label ATM Operators (WLAOs). WLAs are included from April 2014 onwards. Table No. 45 (-) represents nil or negligible The table format is revised since monthly Bulletin for the month of June 2023. Central Government Dated Securities include special securities and Sovereign Gold Bonds. State Government Securities include special bonds issued under Ujwal DISCOM Assurance Yojana (UDAY). Bank PDs are clubbed under Commercial Banks. The category ‘Others’ comprises State Governments, DICGC, PSUs, Trusts, Foreign Central Banks, HUF/ Individuals etc. Data since September 2023 includes the impact of the merger of a non-bank with a bank. RBI Bulletin June 2025 169CURRENT STATISTICS Table No. 46 GDP data is based on 2011-12 base. GDP for 2023-24 is from Union Budget 2023-24. Data pertains to all States and Union Territories. 1 & 2: Data are net of repayments of the Central Government (including repayments to the NSSF) and State Governments. 1.3: Represents compensation and assignments by States to local bodies and Panchayati Raj institutions. 2: Data are net of variation in cash balances of the Central and State Governments and includes borrowing receipts of the Central and State Governments. 3A.1.1: Data as per RBI records. 3B.1.1: Borrowings through dated securities. 3B.1.2: Represent net investment in Central and State Governments’ special securities by the National Small Savings Fund (NSSF). This data may vary from previous publications due to adjustments across components with availability of new data. 3B.1.6: Include Ways and Means Advances by the Centre to the State Governments. 3B.1.7: Include Treasury Bills, loans from financial institutions, insurance and pension funds, remittances, cash balance investment account. Table No. 47 SDF is availed by State Governments against the collateral of Consolidated Sinking Fund (CSF), Guarantee Redemption Fund (GRF) & Auction Treasury Bills (ATBs) balances and other investments in government securities. WMA is advance by Reserve Bank of India to State Governments for meeting temporary cash mismatches. OD is advanced to State Governments beyond their WMA limits. Average amount Availed is the total accommodation (SDF/WMA/OD) availed divided by number of days for which accommodation was extended during the month. - : Nil. Table No. 48 CSF and GRF are reserve funds maintained by some State Governments with the Reserve Bank of India. ATBs include Treasury bills of 91 days, 182 days and 364 days invested by State Governments in the primary market. --: Not Applicable (not a member of the scheme). The concepts and methodologies for Current Statistics are available in Comprehensive Guide for Current Statistics of the RBI Monthly Bulletin (https://rbi.org.in/Scripts/PublicationsView.aspx?id=17618) Time series data of ‘Current Statistics’ is available at https://data.rbi.org.in. Detailed explanatory notes are available in the relevant press releases issued by RBI and other publications/releases of the Bank such as Handbook of Statistics on the Indian Economy. 170 RBI Bulletin June 2025RREECCEENNTT PPUUBBLLIICCAATTIIOONNSS Recent Publications of the Reserve Bank of India Name of Publication Price India Abroad 1. Reserve Bank of India Bulletin2025 `350 per copy US$ 15 per copy `250 per copy (concessional rate*) US$ 150 (one-year subscription) `4,000 (one year subscription) (inclusive of air mail courier charges) `3,000 (one year concessional rate*) 2. Handbook of Statistics on theIndian `550 (Normal) US$ 24 States 2023-24 `600 (inclusive of postage) (inclusive of air mail courier charges) 3. Handbook of Statistics on theIndian `600 (Normal) US$ 50 Economy 2023-24 `650 (inclusive of postage) (inclusive of air mail courier charges) `450 (concessional) `500 (concessional with postage) 4. State Finances - `600 per copy (over the counter) US$ 24 per copy A Study of Budgets of 2024-25 `650 per copy (inclusive of postal charges) (inclusive of air mail courier charges) 5. Report on Currency and Finance `575 per copy (over the counter) US$ 22 per copy 2023-24 `625 per copy (inclusive of postal charges) (inclusive of air mail courier charges) 6. 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Banking Glossary (English-Hindi) `100 per copy (over the counter) `150 per copy (inclusive of postal charges) Notes 1. Many of the above publications are available at the RBI website (www.rbi.org.in). 2. Time Series data are available at the Database on Indian Economy (https://data.rbi.org.in). 3. The Reserve Bank of India History 1935-2008 (5 Volumes) are available at leading book stores in India. * Concession is available for students, teachers/lecturers, academic/education institutions, public libraries and Booksellers in India provided the proof of eligibility is submitted. RBI Bulletin June 2025 171RREECCEENNTT PPUUBBLLIICCAATTIIOONNSS General Instructions 1. All communications should be addressed to: Director, Division of Reports and Knowledge Dissemination, Department of Economic and Policy Research (DRKD, DEPR), Reserve Bank of India, Amar Building, Ground Floor, Sir P. M. Road, Fort, P. B. No.1036, Mumbai - 400 001. 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Details required for NEFT transfer are as follows: Beneficiary Name Department of Economic and Policy Research, RBI Name of the Bank Reserve Bank of India Branch and address Fort, Mumbai IFSC of Bank Branch RBIS0MBPA04 Type of Account Current Account Account Number 41-8024129-19 b. In case of subscription through non-digital modes, please send the demand draft/cheque payable at Mumbai in favour of Reserve Bank of India, Mumbai. 8. Complaints regarding ‘non-receipt of publication’ may be sent within a period of two months. 172 RBI Bulletin June 2025