Inflation Dynamics And Monetary Policy in India1
Indian food and fuel inflation has remained high for several years, and second-round effects on core inflation are estimated to be large. In order to durably reduce inflation, the monetary policy stance needs to be tightened. Analysis suggests that the Reserve Bank of India (RBI) may need to raise rates decisively, and maintain a tight stance for a prolonged period of time. Moreover, progress on structural reforms to raise potential growth is critical to reduce the burden on monetary policy.
1. Drawing from a wider mandate, monetary policy in India has evolved to have multiple objectives of price stability, financial stability and growth. The Reserve Bank’s approach recognizes that price and financial stability are important for sustaining high levels of growth which is the ultimate objective of public policy (Mohanty, 2012). An appropriate monetary policy stance depends on inflation dynamics, the distribution of exogenous shocks affecting the economy, and the monetary transmission mechanism. India as a small economy (compared to the global economy) faces internal shocks as well as external shocks from the rest of the world.
Sources: Haver Analytics; and IMF staff calculations.
2. Persistent and elevated food inflation presents challenges for monetary management. While it is a widely-held view that central banks should only respond to changes in the underlying core inflation and second-round effects on core inflation of commodity price shocks, there is growing evidence that the dynamics of food price inflation are very different in emerging economies. Unlike advanced economies, food-price inflation shocks are more volatile and persistent, and are propagated strongly into nonfood inflation (Walsh, 2011). Also, they tend to have stronger and longer-lasting effects on inflation in economies with high food shares in the consumption basket, and in economies with less firmly anchored expectations (IMF, 2011). Accordingly, excluding commodity-price inflation in economies where food and fuel represent a large share of household expenditure, and where commodity price changes affect core inflation through second-round effects, may not be appropriate (Catão and Chang, 2010; Walsh, 2011). Anand and Prasad (2010) also conclude that in an environment of credit-constrained consumers, a narrow policy focus on nonfood inflation can lead to suboptimal outcomes. In sum, ignoring food inflation in monetary policy action may lead to policy mistakes.
Household Inflation Expectations and Food Inflation
Sources: CEIC, Haver Analytics and IMF staff calculations.
3. The dynamics of headline inflation with respect to core inflation in India is assessed to formalize the relationship between food inflation and its pass-through to core inflation. Following Cecchetti and Moessner (2008) and Clark (2001), the following questions are examined:
Does headline inflation revert to core inflation?
If headline inflation reverts quickly to core inflation, then the impact of food and energy price shocks is temporary, and second-round effects are probably limited. On the other hand, if headline inflation does not revert to core, either the shocks are persistent or the second-round effects are large due to higher inflation expectations and accelerating wages. Empirically, the issue is addressed here by examining the following regression estimated on monthly data for 1996M1–2013M9:
Does core inflation revert to headline inflation?
If core inflation reverts to headline inflation, it would indicate that shocks to headline inflation, such as those caused by commodity-price spikes, feed into inflation expectations and price setting, driving core inflation to catch up with headline inflation. Empirically, the issue is addressed here by examining the following regression estimated on monthly data for 1996M1–2013M9:
4. The empirical results suggest that second-round effects may indeed be significant. Specifically, if headline inflation reverts to core inflation, the coefficient β is expected to be negative. The results, however, suggest that the null of β = 0 can’t be rejected, which implies that headline inflation does not revert to core inflation. At the same time, individually both the hypothesis that β = −1 and that β = −1 and α = 0, i.e. that headline fully reverts to core within a year, are rejected. Therefore, it can be concluded that headline does not revert to core, suggesting that either food shocks are persistent or second-round effects are large. On the other hand, the estimate of γ is −0.7, which is highly statistically significant, suggests that core inflation reverts to headline inflation. At the same time, the null hypothesis of γ = 0, which corresponds to a situation where core does not revert to headline, is rejected. Moreover, both the hypothesis that γ = −1 and that γ = −1 and δ = 0 cannot be rejected. This suggests that core inflation catches up with headline inflation and reverts to headline quickly. Therefore, large second-round effects are likely to be present.2
5. Thus, incorporating the possibility of second-round effects of food price inflation is essential for monetary policy formulation. A practical model that builds on a stylized gap model (each variable is expressed in terms of its deviation from equilibrium, in other words in “gap” terms)3, tailored to India’s fundamentals, is used to estimate second-round effects in a general equilibrium setting. The model features a small open economy including forward-looking aggregate supply and demand with micro foundations, and with stylized (realistic) lags in the different monetary transmission channels. Output developments in the rest of the world feed directly into the small economy as they characterize foreign demand for Indian products. Changes in foreign inflation and/or interest rates affect the exchange rate and, subsequently, demand and inflation in the Indian economy. A New Keynesian Phillips Curve (NKPC), incorporating the effect of the output gap, lagged inflation, exchange rate and inflation expectation on current inflation is estimated in a dynamic small open economy setting. To estimate the second-round effects the model includes the pass-through from headline inflation to core inflation.4
6. The baseline model has four behavioral equations: (1) an aggregate demand or IS curve that relates the level of real activity to expected and past real activity, the real interest rate, the real exchange rate, and the foreign output gap; (2) a price setting or Phillips curve that relates core inflation to past and expected inflation, the output gap, and the exchange rate, as well as the pass-through from the headline to core inflation; (3) an uncovered interest parity condition for the exchange rate, with some allowance for backward looking expectations and risk premium; and (4) a rule for setting the policy interest rate as a function of the output gap and expected inflation. Finally, a food and fuel inflation equation prescribes persistent underlying inflation dynamics.
7. The estimated Phillips curve for core inflation is backward looking, and suggests sizable second-round effects:
8. The estimated aggregate demand equation suggests that expectations about future output and real policy rates matter for economic activity:
where RRgap is the real interest rate gap, zgap is the gap of real effective exchange rate, and ygapRW is the output gap in the rest of the world, as proxied by the United States. The coefficient estimate on the lead of the output gap indicates that expectations regarding the future level of the output gap are important. This corroborates the importance of confidence effects in promoting growth (Anand and Tulin, 2014). The negative impact of real rate tightening indicates a trade-off between inflation and growth. Specifically, a one percent increase in the real interest rate is associated with a 0.1 percentage point widening of the output gap in the next quarter. However, the exchange rate impact on the output gap is positive but small, reflecting low short-term trade elasticities.
9. The estimated policy reaction function suggests that the RBI focuses on multiple objectives:
There is a high degree of interest-rate (RS) smoothing in India (the coefficient is 0.8), which is in line with the estimates of this parameter by Anand and others (2010). The weight on inflation stabilization is 1.7. The estimate of the coefficient on output gap is 0.6, suggesting that the RBI puts weight on stabilizing real activity. This broadly corresponds to the RBI’s multiple objectives approach.
10. Monetary policy needs to respond decisively to tackle India’s high and persistent inflation. At the current juncture, with food inflation remaining persistently high for five years, monetary policy needs to be tightened to control generalized inflation. Given elevated and persistent inflation, the analysis suggests that the RBI may need to raise rates decisively to tackle inflation durably. As inflation is mostly backward looking, monetary policy has to maintain a tight stance for a prolonged period of time. As well, given that Phillips curve is relatively flat, progress on structural reforms to raise potential growth is critical to reduce the burden of adjustment on monetary policy.
AnandR. and E.Prasad2010 “Optimal Price Indices for Targeting Inflation Under Incomplete Markets” IMF Working Paper 10/200 (Washington: International Monetary Fund).
AnandR.M.Saxegaard and S.Peiris2010 “An Estimated Model with Macrofinancial Linkages for India” IMF Working Paper 10/21 (Washington: International Monetary Fund).
AnandR. and V.Tulin2014 “Disentangling India’s Investment Slowdown” IMF Working Paper (forthcoming).
BergA.P.Karam and D.Laxton2006a “A Practical Model-Based Approach to Monetary Policy Analysis, Overview” IMF Working Paper 06/080 (Washington: International Monetary Fund).
BergA.P.Karam and D.Laxton2006b “Practical Model-Based Monetary Policy Analysis: A How-to Guide” IMF Working Paper 06/081 (Washington: International Monetary Fund).
CatãoL. and R.Chang2010 “World Food Prices and Monetary Policy” IMF Working Paper 10/161 (Washington: International Monetary Fund).
CecchettiS. and R.Moessner2008 “Commodity Prices and Inflation Dynamics” BIS Working Paper.
ClarkT.2001 “Comparing Measures of Core Inflation” Federal Reserve Bank of Kansas City Economic Review Vol. 86 No. 2 pp. 5–31.
International Monetary Fund2011 “Slowing Growth, Rising Risks” Chapter 3 of World Economic Outlook (Washington: International Monetary Fund).
MohantyD.2012 “Price Stability and Financial Stability An Emerging Market Perspective” Address at the 2012 Central Bank of Nigeria Board Cape Town South AfricaJune272012.
PatraM. and M.Kapur “A Monetary Policy Model without Money for India” IMF Working Paper 10/183 (Washington: International Monetary Fund).
Prepared by Rahul Anand and Volodymyr Tulin.
The estimates reported correspond to CPI-IW inflation. Conclusions remain the same if WPI inflation is used instead.
The reported results are based on the CPI-IW inflation.
Core CPI are compiled by staff by stripping out food and energy items from the consumption basket.
This is also consistent with the cross-country evidence that finds the co-efficient on expected inflation to be below 0.5 (Berg et al., 2006).