Information about Asia and the Pacific Asia y el Pacífico
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India: Selected Issues

International Monetary Fund. Asia and Pacific Dept
Published Date:
February 2017
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The background papers for the 2017 Article IV explore key issues affecting the Indian economy, and implications for fiscal, monetary, financial sector and other structural policies.

The first chapter evaluates corporate and banking sector vulnerabilities in India. The analysis shows that while corporate sector risks have subsided, debt repayment capacity remains strained and high leverage levels continue to weigh on corporate resilience, which may pose further risks to banks’ asset quality. Public sector banks have stepped up recognition of non-performing assets, but their debt recovery capacity remains weak. Simulations suggest that potential recapitalization needs, at current provisioning levels, should have a modest fiscal impact.

The second chapter assesses a safe public debt level based on the debt intolerance approach. Many countries use debt-to-GDP targets to anchor fiscal policies. This chapter finds that that based on regression analysis, the threshold for the safe level of debt for India falls in the range of 60-65 percent of GDP, taking into account buffers needed to accommodate existing contingent liabilities.

Chapter 3 assesses the extent to which center-state fiscal transfers smooth regional shocks and help income redistribution across Indian states. The analysis suggests that fiscal transfers from the central government to the states offset about twelve percent of permanent shocks to states’ income (redistribution effect). However, the analysis also points to the need to improve the stabilization features of India’s central government finances, as transfers appear to be pro-cyclical with respect to both idiosyncratic shocks (interregional risk-sharing) and common shocks (macroeconomic stabilization).

The fourth chapter explores the feasibility of universal basic income (UBI) proposals in the Indian context. In India, the existing social protection system—primarily based on subsidies—has flaws. These subsidy schemes are often associated with high administrative costs and ineffectiveness, particularly leakages to non-targeted better-off people. While UBI may help overcome some failures of the current system, concerns on fiscal affordability and political feasibility weigh heavily on policy discussions.

The fifth chapter analyzes India’s export competitiveness and examines the recent slowdown of exports. India’s trade weakness can be attributed to both external and domestic factors—weak trading partners’ demand and real appreciation of the Indian rupee were the key drivers of the export slowdown. India’s high tariffs and trade costs have also weighed on its export performance and new investment that is needed to better integrate Indian exports into global value chains.

Chapter 6 discusses recent trends in capital flows and the evolution of capital account openness indices for India. It finds that India’s recent capital account liberalization measures have not been reflected in these de jure indices, which have remained unchanged in recent decades. Structural policies, particularly those aiming on strengthening the financial sector and institutions, should complement capital account liberalization efforts to increase the benefits of capital flows to the economy.

The seventh chapter evaluates the effects of labor and product market deregulation policies in the presence of short-run reform costs. The analysis suggests that with limited policy space, sequencing of reforms should prioritize implementing labor market reforms as they reinforce the long-run gains in potential output and employment, minimize short-term costs, and increase the acceptability of these politically-difficult reforms.

Chapter 8 uses a practical spreadsheet tool to estimate the environmental, fiscal, economic, and incidence effects of a wide range of options for reducing fossil fuel use in India. Progressively increasing the (recently introduced) coal tax would substantially reduce air pollution mortality, raise significant revenue, and ensure India meets its mitigation pledges for the Paris Agreement on climate change. The environmental effectiveness of the coal tax easily exceeds that for a wide range of other mitigation instruments (e.g., emissions trading systems, incentives for energy efficiency and renewables) and is almost as effective as a carbon charge applied to all fossil fuels.

Chapter 9 examines the key macro-financial linkages between gender gaps in access to formal finance and macroeconomic performance in India. Policies that relax financial constraints faced by females are found to increase female entrepreneurship, output and employment. However, to lower gender gaps in labor market outcomes, policies that alleviate labor market rigidities should be implemented simultaneously to maximize long-run gains from greater financial inclusion.

Chapter 10 analyzes the relationship between education and inequality in the Indian economy. It finds that income inequality has increased, while enrollment and learning achievements have lagged behind. It concludes that policies need to aim at increasing returns to education in order to enhance educational achievements, while cash transfers can support liquidity-constrained households and reduce inequality.

The eleventh chapter analyzes developments in per capita incomes across Indian states over the last five decades, and tests whether cross-state income convergence has occurred. It finds some evidence of income convergence during the pre-1990s economic reform period, but Indian state income growth has further widened disparities in the post-1990 economic reform period.

The final chapter focusses on the role of food security and agriculture sector policies in affecting health and nutrition in India. A multi-sectoral approach—including addressing inherent long-term structural bottlenecks within the agricultural sector and improving productivity of pulses (a major source of protein), along with improvements in sanitation and gender equality, is needed to lower the high rates of undernourishment and hunger currently prevalent in India.

Corporate and Banking Sector Vulnerabilities in India1

The Asset Quality Review (AQR) initiated by the Reserve Bank of India (RBI) has led to an uptick in the recognition of non-performing assets (NPAs) across public sector banks (PSBs). Policy steps to address supply-side bottlenecks—notably in the infrastructure sector—have ameliorated corporate sector vulnerabilities. However, Indian corporates continue to be highly levered. and some sectors are still subject to debt repayment capacity strains. Sensitivity analysis of corporate balance sheets confirm that exposure to potential shocks is still high and, thus, continues to weigh on PSBs’ asset quality. Altogether, PSBs are expected to require further capital augmentation in the coming years, but simulations suggest that, at current provisioning levels, its scale should have a modest fiscal impact.

1. A strong policy impetus to enforce robust asset quality recognition across PSBs has induced a considerable uptick in NPAs. The AQR, initiated by the RBI in December 2015, is intended to lead to a full recognition of NPAs by March 2017. As a result, NPA slippages across PSBs have accelerated noticeably, and their aggregate NPA ratio increased to 9.3 percent in FY2015/16, from 5 percent a year earlier.2 The accumulation of NPAs reflected both an intensified transition of previously restructured loans into NPAs, and a broader recognition of NPAs among previously un-restructured exposures. The brisk re-classification of standard restructured loans into NPAs accounted for a sizable contraction in restructured assets, whose share in total advances receded to 4.1 percent from 7.1 percent a year earlier. Most AQR-related recognition of NPAs appears to have already materialized, albeit with some potential for a further rise in NPAs, due to remaining, still unrecognized, vulnerable accounts.

PSBs: Gross NPAs and Restructured Loans

(In percent of gross advances)

Source: Reserve Bank of India (RBI).

NPA Formation at Indian Banks, end-FY2016

(In percent of standard assets at end-FY2015)

Sources: Reserve Bank of India (RBI); and IMF staff calculations.

2. Low NPA provisioning and weak debt recovery remain key challenges for PSBs. Intensified NPA recognition has led to a considerable uptick in provisioning allocation and a further decline in PSBs’ profitability, with return of assets (ROAs) of PSBs turning negative in FY2015/16. However, PSBs’ aggregate provision coverage ratio continues to be low, at 39 percent as of end-FY2015/16, raising concerns about the sufficiency of provisioning, particularly in view of weaknesses in the loan resolution process.3 While banks with less robust provisioning coverage (i.e. those below the PSBs’ average in FY2014/15) bolstered provisioning in FY2016, previously better-provisioned banks saw provisioning coverage slip to 44 percent in FY2015/16 from 50 percent a year earlier. Overall, PSBs’ loan recovery capacity remains weak. The rise in NPAs in FY2015/16 was offset primarily via write-offs, which accounted for a 1.2 percentage-point offset in NPA slippage rates in FY2015/16, compared to only 0.6 percentage points for loan recoveries, underscoring the need for timely implementation of debt resolution reforms.

NPA Provision Coverage Ratios of Public Sector Banks

(In percent)

Sources: Banks’ annual reports; and IMF staff calculations.

Note: PSBs are determined as better or worse provisioned, based on whether they were above or below PSBs’ average provisioning coverage ratio of 41 percent in FY2015.

3. Simulations of further PSB asset quality deterioration suggests that potential capitalization needs, under current provisioning levels, should have a modest fiscal impact. The simulations assume a 25 percent transition of restructured advances to NPAs in each year to end-FY2018/19, with a minimum 40 percent and 70 percent provisioning against NPAs.4 The analysis is carried out on a bank-by-bank basis, with slippage, recovery and write-off rates calibrated to banks’ performance in FY2015/16, and using the Tier 1 capital ratio as a hurdle rate (including the 2.5 percent capital conservation buffer (CCB) and additional buffers of up to 2 percent, the latter meant to ensure market confidence). Even in a severe scenario of continuous deterioration of PSBs’ asset quality on a scale commensurate with their recent experience, recapitalization costs should be manageable, at 1.5 to 2.4 percent of FY2018/19 GDP, and a government share of 1.0-1.6 percent (cumulatively over four years), with the range reflecting up to 2 percentage-point buffers above the minimum requirement. However, recapitalization costs would be considerably higher if there is a policy shift to more conservative provisioning requirements. In case of a rise in the required provisioning ratio to 70 percent, cumulative recapitalization needs would increase to 3.3-4.2 percent of FY2018/19 GDP, with a government share of 2.2-2.8 percent.

PSBs: Simulated Capitalization Needs under Stress, At 25 percent Migration of Restructured Loans

(Cumulative over 3-year horizon, in percent of 2018/19 GDP)

Sources: Banks’ balance sheets; and IMF staff estimates.

Note: Rapid credit growth assumed at 1.1xGDP growth; and slow at 0.9xGDP growth. Migration refers to the reclassification of restructured loans into NPAs.

4. PSBs continue to be exposed to risks related to the slowly improving, but still elevated, corporate sector vulnerabilities.5 The link between the financial performance of the banking and corporate sectors in India is strong. With the corporate sector accounting for about 40 percent of banks’ (particularly PSBs’) credit portfolios, PSB’s soundness and their ability to provide effective intermediation in the economy rest on effective debt restructuring and deleveraging in the corporate sector. Corporate vulnerabilities subsided in FY2015/16 on concerted policy efforts to address structural bottlenecks, including delays in environmental clearances and land acquisition permits. Debt-at-risk—the share of debt held by firms with weak debt-repayment capacity (interest coverage ratio below one)—declined to 16.6 percent from 20.2 percent a year earlier, pointing to improved debt-repayment capacity.6,7 However, the high debt-at-risk and NPAs in some sectors—as high as 36 percent in metals and mining—pose NPA slippage risks for banks.

Corporate Sector Vulnerabilities

(In percent)

Sources: CapitalIQ; and IMF staff estimates.

Note: Based on a sample of 2,057 firms. Top 50 firms based on total assets. Leverage is the median debt-to-equity ratio within each group, excluding 227 firms with negative equity. Debt-at-risk is the share of debt of firms with interest coverage ratio (ICR) less than 1 in each group’s overall debt.

Sectoral Distribution of Debt-at-Risk

(In percent of debt; end-FY2015/16)

Sources: Reserve Bank of India; and IMF staff estimates.

Notes: Debt-at-risk is the debt of firms with interest coverage ratio (ICR) less than 1. Textiles includes apparel luxury goods; construction includes engineering; automobiles includes components; telecommunications includes telecommunication services only.

5. Corporate deleveraging has been slow and uneven, particularly among larger firms and across certain sectors, exposing corporates to elevated risks. In the aggregate, firms’ indebtedness has been declining consistently, with the median debt-to-equity ratio falling to 56 percent at end-FY2016, from 67 percent two years earlier. However, leverage levels continue to be high relative to other emerging markets (EMs). The debt of highly-levered firms (debt-to-equity ratios above 150 percent) accounts for about half of outstanding corporate debt, and such concentration of debt at the tail-end of the leverage distribution raises corporate vulnerabilities to shocks. Importantly, leverage is also uneven across sectors and firm size. Certain industries—including metals and mining, construction and engineering, and transportation infrastructure—which jointly account for a large share of the system’s debt-at-risk, also have a high share of debt (more than ¾) in each sector belonging to highly-levered firms (debt-to-equity ratios over 150 percent). India’s largest firms (accounting for the top one to three percent of corporate sector assets) have also been persistently more levered than other firms.

Distribution of Corporate Debt by Debt-to-Equity

(In percent; overall and select high leverage sectors)

Sources: CapitalIQ; and IMF staff estimates.

Note: Based on a sample of 2,057 firms. Textiles include textiles, apparel and luxury goods.

6. The resilience of the corporate sector to potential domestic and external shocks is assessed via sensitivity tests based on a tail-risk balance sheet approach.8 Under this approach, the strength of corporates’ debt-repayment capacity under extreme stress serves as a gauge of financial soundness. Potential shocks are applied both individually and jointly, and are evaluated under two extremely severe scenarios, entailing: (i) a sharp rise in overseas funding rates (200 and 400 basis points (bps), respectively); (ii) a depreciation of the rupee due to capital outflows (20 and 29 percent); (iii) a rise in the domestic policy rate to defend the currency (200 and 250 bps) (all assumed to impact non-operating income); and (iv) a decline in operating profits (25 percent under both scenarios).9 With the exception of the profitability shock, the scenario is calibrated based on extreme past movements in the risk factors (the 90+ percentile of joint bilateral distributions of annual changes in risk factors in the first scenario and at unprecedented levels in the second scenario. The shocks were applied to each corporate’s balance sheet, and the share of aggregate debt of firms with an ICR below one relative to total corporate sector debt was estimated to assess overall debt repayment capacity.

Schematic Overview of the Corporate Sensitivity Analysis Approach

Joint Distribution of Risk Factors

Source: Author’s calculations.

7. The sensitivity tests confirm that corporates continue to face potential debt repayment risks. In extreme stress conditions, entailing a confluence of heightened external and domestic risks, the corporate sector’s debt-at-risk is expected to rise from 16 percent to up to 35 percent in the more severe scenario. Downward profitability pressures and a potential upward shift in domestic interest rates continue to be key risks for Indian corporates. A 25-percent decline in profitability or a 250 bps rise in domestic rates are associated with a marked uptick in debt-at-risk to 24 percent of overall debt. In the aggregate, Indian firms are less exposed to a sharp foreign currency (FX) depreciation or a rise in LIBOR rates, though the level of vulnerabilities to external risks is reasonably high. A joint materialization of both external-risk factors accounts for a rise in debt-at-risk to 19 percent, a considerably higher level relative to years prior to the most recent rise in corporate vulnerabilities (e.g., FY2011/12). Altogether, the exposure of Indian corporates to all types of financial risks remains elevated.

Corporate Debt at Risk, Severe and Extreme Stress

(In percent of total corporate debt; by type of shock)

Sources: CapitalIQ; and IMF staff estimates.

Note: Debt at risk is the debt owned by firms with interest coverage ratio (ICR) less than 1. Based on 1,874 corporates with available data for each year in FY2011/12 - FY2015/16.

8. Dependence on external funding continues to expose Indian corporates to potential shocks. Corporates are exposed to rollover risks (of not being able to renew funding), a potential rise in the LIBOR (which underpins ECB funding) or an Indian rupee (INR) depreciation, the latter in case FX funding is insufficiently hedged. Nonetheless, FX hedging across Indian corporates has increased considerably in recent times. RBI data on intentions to hedge ECBs and foreign currency convertible bonds (FCCBs) suggests that the aggregate hedging ratio (excluding natural hedges) rose to about 41 percent of corporate borrowings in the first quarter of FY2015/16 from about 15 percent in FY2013/14. However, uncertainty about the level of corporate hedging over time and about the ability of FX hedging to fully mitigate potential risks—including due to possible maturity mismatches between FX hedges and underlying positions or a potential rise in hedging costs, particularly in case of a large depreciation—leave corporates exposed to FX risks. FX currency risks should be further mitigated by the recent introduction of rupee-denominated ECBs and overseas bonds (Masala bonds) in September 2015.

9. The slow deleveraging and repair of corporate balance sheets and the potential further build-up of NPAs can have negative effects on the real economy. The pace of credit growth has so far been supported by government capital injections in PSBs and a shift of credit demand toward alternatives to bank lending, such as commercial paper (CP) funding. However, the need for capital preservation has led to a marked slowdown of credit growth across PSBs, which, in the aggregate, slowed to 3.7 percent in FY2015/16 from an average of 15 percent in the preceding three years, and contracted particularly for those PSBs with the most problem assets. A larger-than-anticipated rise in new NPA formation due to shocks affecting corporates’ debt repayment capacity—e.g., due to weaker demand in certain sectors, or exchange rate or interest rate shocks—or PSBs’ inability to raise adequate capital, could further dampen the provision of credit to the real economy and impair growth. While the relatively low credit intensity of the Indian economy reduces the adverse growth effect of muted bank credit growth, the risk of an increase in NPAs is exacerbated by the high corporate leverage levels, which magnify banks’ losses in the event of potential shocks, and has already been a drag on domestic investment. Furthermore, the limited monetary and fiscal space in India constrains policymakers’ capacity to counteract any additional increase in NPAs.

Loan Growth by NPA quartiles, FY2015-16

(Average loan growth by quartile, in percent)

Sources: Reserve Bank of India; and IMF staff estimates.


    International Monetary Fund2014Global Financial Stability Report: Moving from Liquidity- to Growth-Driven MarketsApril2014 (International Monetary Fund: Washington).

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    LindnerP. and S.Jung2014Corporate Vulnerabilities in India and Banks’ Loan Performance,IMF Working Paper WP/14/232 (International Monetary Fund: Washington).

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    OuraH. and P.Topalova2009India’s Corporate Sector: Coping with the Global Financial Tsunami,India: Selected Issues IMF Country Report No. 09/186 (International Monetary Fund: Washington).

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Prepared by Silvia Iorgova.


NPA slippages among PSBs, accelerated to 7.2 percent in FY2015/16 from 3.4 percent in the previous year. The NPA slippage ratio is the ratio of gross new NPAs during the year to standard assets at the beginning of the year. Estimates of NPA slippages, and shares of restructured and stressed assets are from RBI data based on OSMOS returns.


The 2017 Financial Sector Assessment Program (FSAP) Update will examine in more detail provisioning across Indian banks.


The 25 percent transition rate of restructured assets into NPA is in line with that experienced by PSBs in FY2015/16. The increase of provisioning to 70 percent is motivated by the need for Indian banks to pursue more conservative provisioning, and is aligned with RBI’s past minimum provisioning level requirements.


Corporate sector here refers to incorporated entities in the non-priority sectors.


The corporate sector risk analysis is based on a sample of 1,830 to 2,057 firms with data from CapitalIQ available for each of the three years to FY2015/16.


The interest coverage ratio—the multiple of earnings before interest and taxes (EBIT) relative to interest expenses—of a firm measures its debt-repayment capacity (i.e. the availability of profitability buffers to support interest payments on outstanding debt).


The approach is similar to that used in IMF, GFSR (2014); Lindner and Jung (2014); and Oura and Topalova (2009). The corporate sector risk analysis is based on a sample of 1,830 to 2,057 firms with data from CapitalIQ.


Due to the lack of firm-by-firm data on corporates’ foreign currency (FX) liabilities and expenditures, estimates for the aggregate corporate sector were applied in the analysis.

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