Abstract
This chapter attempts to evaluate the performance of monetary policy in terms of its effectiveness in influencing the rate of economic growth and controlling inflation. The importance of these two policy objectives comes to the fore, especially when viewed through the lens of the Sustainable Development Goals (SDGs) of the United Nations. Growth is critical for combating poverty and undertaking redistributive measures to mitigate inequality within nations (SDGs 1 and 10), whereas managing inflation, especially food inflation, lies at the core of strategies designed to end hunger and achieve food and nutrition security (SDG 2). The performance evaluation undertaken in the paper is based on a review of relevant literature in the Indian context, focusing especially on the post-liberalization period. Given the centrality of monetary policy measures in the Indian government’s response to the economic pandemic wrought by COVID-19, perhaps such an appraisal is needed now, more than ever before. To begin with, a brief overview of the conduct of monetary policy in India provides the necessary background for the remaining analysis. The effectiveness of monetary transmission in affecting aggregate demand and output in the Indian context, especially in recent times, is examined thereafter. The phenomenon of inflation, especially food price inflation and the efficacy of monetary measures in controlling it, is discussed next. Findings from the literature are then used to assess recent liquidity measures of the Indian government for economic revival in pandemic times and conclude.
The authors would like to thank the editors for this opportunity to contribute to this volume in honour of Prof. Ramprasad Sengupta, one of the finest economists in our country. In particular, the first author, who has been a student of Professor Sengupta at JNU, is extremely grateful to him for the many lessons he imparted in class and through his exemplary sincerity as a teacher and practitioner of the discipline. The authors would especially like to thank Soumyen Sikdar for extremely helpful comments and suggestions on an earlier draft. Lastly, the usual disclaimer applies.
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Notes
- 1.
Recommendations of landmark committees such as the Chakravarty Committee in 1985, Narasimham Committees (I and II) in 1991 and 1998, the Tarapore Committee in 2006, the Raghuram Rajan Committee in 2008 and the more recent Urjit Patel Committee in 2014 (which led to setting up of Monetary Policy Committee in 2016) have profoundly influenced the path of monetary reforms in India. These have also been shaped by detailed recommendations made by various Working Groups constituted by the RBI from time to time (e.g. Working Group on Sterilization in 2003, Working Group on Operating Procedure of Monetary Policy in 2011, etc.).
- 2.
Prohibition on the issue of fixed interest, ad hoc treasury bills since 1997–98, steady reduction in the statutory liquidity ratio or SLR (from 38.5 in 1990 to its statutory minimum of 25% by 1997) and enactment of the FRBM Act in 2003 (which put a stop to direct government borrowing from RBI 2006–07 onwards) were three important milestones that served to limit automatic fiscal accommodation by monetary policy. The first contributed to emergence of a market for government securities and transition to market-based interest rates (even as it raised cost of borrowing for the government). The third enhanced ‘space’ for using monetary policy by reducing the scope for monetization and imposing strict constraints on size of the fiscal deficit (Ray, 2013).
- 3.
The repo (short for repurchase) and reverse repo rates are used by the RBI, under the LAF to temporarily inject and withdraw liquidity, respectively, into and from the commercial banking system. The collateralized transactions involve lending to and borrowing from the commercial banks against government securities. These stand reversed within a very short time span as they simply involve digital entries, with no change in title of the holder of the securities used for the transactions.
- 4.
E.g. higher magnitude of the weight for inflation gap indicates that the central bank cares more about inflation than unemployment. So it is more likely to raise interest rates to curb inflation when it exceeds target, even if that comes at the cost of lowering output and raising unemployment (Carlin & Soskice, 2015).
- 5.
It has also been suggested though that Taylor rule is appropriate for emerging economies only after suitable modifications (Taylor, 2000).
- 6.
E.g. Lags in the effect of interest rate changes on the output gap range from two to three quarters (Mohanty, 2012; Patra & Kapur, 2010) and on inflation, from three quarters (Mohanty, 2012) to as much as two years (Chand and Singh, 2006). Real appreciation of the rupee has also been found to lower output with a lag of two quarters (Patra and Kapur, 2010).
- 7.
For instance, results depend on whether a forward-looking or backward-looking specification is used for the IS curve in empirical models. Moreover, use of restricted forms of the IS equation that ignore relevant factors such as real exchange rates and asset prices which also affect aggregate demand (especially private investments) may also lead to misspecification.
- 8.
Kapoor and Ravi (2009 and 2010) exploit the natural experiment presented by this policy change and analyse two rounds of NSSO data, classifying households on the basis of age (e.g. households in which the head is a senior citizen and those where the head is below 60 years of age). Using a regression discontinuity approach, Kapoor and Ravi (2009) estimate substantial short-run impact of the hike in deposit rates on consumption expenditure on non-food, non-essential items (including durables, education, clothing, travel, medicine, etc.). However, consumption resumes its average value in the longer run, which they surmise this could be due to income effects (i.e. higher interest income leading to higher consumption in the long run). Using a difference-in-difference estimator, Kapoor and Ravi (2010) compare consumption of two groups of households (those where head is senior citizen vs those where head is not senior citizen). They find that consumption patterns were similar prior to 2001, but differed significantly in 2005 and attribute this difference to the hike in deposit rates for senior citizens between 2001 and 2004.
- 9.
See Dastidar and Ahuja (2019) for a recent survey on the determinants of private corporate investments in India.
- 10.
Fulford (2013) also shows that credit availability may have adverse long-run effects by undermining savings and hence future income streams. A theoretical model is used along with empirical analysis based on NSSO data to study the dynamic effects of enhancing access to credit.
- 11.
After the RBI increased the loan-to-value (LTV) ratio to 90% for home loans of up to Rs. 30 lakhs or less (that fall under ‘affordable’ category in urban areas) in 2015, there was a surge in housing loans in the following year (RBI press release 2016–2017/1277).
- 12.
Typically, expectations about future house price are based on the past trends. Using the past housing prices as proxy for house price expectations, Arora et al. (2020) show that real estate prices influence credit markets in Indian cities (Tier 1 as well as Tier 2 cities), with causality running from house price to credit. The result that housing prices are causing credit is indicative of the role of expectations in driving credit demand for housing.
- 13.
Even for studies that focus only on the post-1991 period, there is wide variation in the exact time period covered. For instance, the periods covered in some of the studies are as follows: Aleem (2010)—1996(Q4) to 2007(Q4); Das (2015)—March, 2002 to October, 2014; Kaur and Dastidar (2019)—May, 2001 to March, 2015; Kaur (2016)—1996 (Q1) to 2013 (Q3); Khundrakpam and Jain (2012)—1996–1997 (Q1) to 2011–2012 (Q1); RBI (2013)—2000–2001 to 2010–2011; Sengupta (2014)—1993–2012; Singh (2011)—March, 2001 to June, 2012; to mention a few.
- 14.
Holtemoller and Mallick (2016) also use SVAR model to show the impact of global food prices on food price and wholesale price inflation in India over the period 1996 (Q1) to 2013 (Q2).
- 15.
Bhattacharya et al. (2019) examine evidence on factors that weaken monetary transmission to output and inflation in the context of advanced and emerging economies in a meta-analysis framework.
- 16.
The RBI regularly conducts various enterprise surveys on capacity utilization, inventories, etc. (e.g. OBICUS or Order Book, Inventory and Capacity Utilization Surveys), to capture investment plans, business confidence, etc. This data can also serve as proxy for investment plans of the private sector. The problem is that this data covers a limited sample with potential issues of inter-temporal comparability owing to changes in the underlying sample and so on. These may be among the reasons that such data is still not widely explored in the empirical literature.
- 17.
‘Deflationary’ expectations led to prolonged periods of high real interest rates in a number of industrialized countries, jeopardizing prospects of recovery in business investments and pushing nominal interest rates into the negative zone!
- 18.
Periodic episodes of currency crises in Latin America in the 1990s and 2000s decades as well as the Asian crisis of 1997 have demonstrated the difficulties of managing fixed exchange rates with international capital mobility. Fiscal indiscipline and institutional weaknesses (e.g. weakly regulated financial and asset markets) have time and again jeopardized macroeconomic stability in emerging markets, especially in the face of volatile capital flows.
- 19.
E.g. Large fiscal deficits may lead to downgrading of credit ratings by international agencies like Fitch, Moodys, etc., that raises countries’ borrowing costs in international markets.
- 20.
Since commodity markets clear relatively quickly, this shows up in greater price fluctuations, compared to imperfectly competitive goods markets with sticky prices, that respond to cost changes only with lags.
- 21.
E.g. The presence of under-regulated commodity exchanges and futures markets may contribute to speculation and volatility in commodity prices.
- 22.
Frankel’s (2008) arguments are in context of advanced economies like the USA and a set of emerging economies from Latin America, where he observes fall in inflation, in response to rise in policy rates. However, his finding for Mexico is the opposite, where commodity prices increase following a rise in real interest rates.
- 23.
E.g. High price of commodities in the futures markets signals persistence of high commodity prices in times to come (Frankel, 2008).
- 24.
On 20 April 2020, the price of oil (West Texas Intermediate (WTI) benchmark oil price index) became negative (−$37.63) as economic activity came to a standstill and demand for oil crashed due to the global lockdown (Nawaz, 2020).
- 25.
While global food prices rose sharply in 2016, individual country experience with food inflation over the same period showed wide variation (see Bhattacharya and Jain, 2020 for details).
- 26.
Holtemoller and Mallick (2016) find that global prices were important in affecting food inflation during the years 1999/2000, 2005, 2008 and 2010.
- 27.
Quarterly growth of the Chinese economy reported in July, 2020 was just over 3%, exceeding the 2% recovery that was expected in the post-COVID scenario (Mc Donald, 2020).
- 28.
The operation of the Keynesian multiplier may be impaired during the pandemic as marginal propensity to consume (MPC) may be unusually low. Further, the second and subsequent rounds of the multiplier may be severely limited in the presence of large-scale job losses, especially if these are concentrated in sectors where MPC is relatively high. Those losing jobs may receive transfer payments, but spending out of such transfers would not be coming back as income to the unemployed, limiting the effectiveness of the multiplier.
- 29.
The repo rate was reduced from 5.15 to 4.40% from with immediate effect. The marginal standing facility (MSF) rate and bank rate was reduced to 4.65% from 5.40%, and the reverse repo rate under LAF was reduced by 90 basis points to 4.0%.
- 30.
Rs. 500 per month is being transferred to the bank accounts women holding Jan Dhan Accounts (meant for those below poverty line(BPL)) for three months.
- 31.
The fiscal stimulus in other large emerging nations stands at 4.4% for Indonesia, 4.9% for Argentina and 11% for Brazil (https://www.statista.com/statistics/1107572/covid-19-value-g20-stimulus-packages-share-gdp/).
- 32.
Ways and means advances (WMA) are temporary advances (maximum expiry of three months) by the RBI to both the Central and State governments to meet temporary mismatches/shortfall in revenue over expenditure.
- 33.
The liquidity coverage ratio, introduced as part of Basel III reforms on Banking supervision, requires banks to hold enough high-quality liquid assets such as short-term government debt (which can be sold off) to meet short-term debt obligations.
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Appendix
Appendix
Details of measures adopted by the RBI to deal with the economic situation due to COVID-19 on May 22, 2020
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RBI announced a new Targeted Long-Term Repo Operation (TLTRO 2.0) of Rs 50,000 crore (in several tranches, and further possibility of expansion if needed) for mid- and small-sized nonbank financial companies (NBFCs) and microfinance institutions (MFIs) which have been more severely impacted by the disruptions of pandemic due to COVID-19.
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The RBI Governor, Shaktikanta Das announced a reduction in the repo rate by 40 basis points, from 4.4 to 4% and reverse repo rate to 3.35%, which would help in releasing surplus funds for providing higher credit for investment in the productive sectors of the economy.
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A special refinance facility of Rs 50,000 crore for National Bank for Agriculture and Rural Development (Rs 25,000 crore), the Small Industries Development Bank of India (Rs 15,000 crore) and the National Housing Bank (Rs 10,000 crore) to meet sectoral credit needs since they are facing difficulties in raising finances from the market.
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Ways and Means Advances (WMAs)Footnote 32 limit of states and union territories has been increased by 60% over and above the limit as on March 31, 2020, in order to provide greater comfort to states to deal with the present crisis.
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A major relaxation has been given in the asset classifications norm, wherein the moratorium period will be excluded while considering the 90-day NPA norm for those accounts for which lending institutions decide to grant moratorium or deferment and which were standard as on March 1, 2020. The NBFCs are thereby allowed to grant relaxed NPA classification to their borrowers and; the banks will need to maintain additional provisioning of 10% on standstill accounts.
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An extension has been given for the implementation of a resolution plan for stressed assets (or likely NPAs) by 90 days. Under this, now the banks need not maintain additional provisioning of 20%, which they did earlier within 210 days of such default. LCR requirement was brought down from 100 to 80% with immediate effect.
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In order to enable banks to save on capital in the present uncertain times, the RBI has decided that scheduled commercial banks and cooperative banks shall not make any further dividend pay-outs from profits pertaining to FY 2019–20. This may be reviewed based on the financial position of banks at the end of the second quarter of the financial year 2019–20.
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The liquidity coverage ratioFootnote 33 for scheduled commercial banks has been brought down from 100 to 80% in two phases.
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NBFCs’ loans to delayed commercial real estate projects can be extended by a year without restructuring. Additionally, these loans to be given similar benefits as given by scheduled commercial banks.
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Dastidar, A.G., Kaur, K. (2021). An Evaluation of Monetary Policy in India: A Sustainable Development Perspective. In: Dasgupta, P., Saha, A.R., Singhal, R. (eds) Sustainable Development Insights from India. India Studies in Business and Economics. Springer, Singapore. https://doi.org/10.1007/978-981-33-4830-1_6
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