The dynamics of survey-based household inflation expectations in India

Abstract

PurposeThe authors analyze households' inflation expectations data for India, collected quarterly by the RBI for more than a decade. The contribution of this paper lies in two folds. First, this study examines the relationship between relatively recent inflation expectations survey of households (IESH) and the actual inflation for India. Secondly, the authors employ a structural VAR with the time period 2006 Q2 to 2020 Q2 on inflation expectation survey data of India. A short-term non-recursive restriction is imposed in the model in order to capture the simultaneous co-dependence causal effect of inflation expectation and realized inflation.Design/methodology/approachThis paper studies the dynamic behavior of inflation expectations survey data in two folds. First, the authors analyze the time series property of the survey data. The authors begin with testing the stationarity property of the series, followed by the casual relationship between the expected and actual inflation. The authors further examine the short-run and long-run behavior of the IESH with actual inflation. Employing autoregressive distributed lag and Johansen co-integration, the authors tested if a long-run relationship exists between the variables. In the second approach, the authors investigate the determinants of inflation expectations by employing a non-recursive SVAR model.FindingsThe preliminary explanatory test reveals that inflation expectation is a policy variable and should be used in monetary policy as an instrument variable. The model identifies the price puzzle for India. The authors find that the response of inflation to a monetary policy shock is neutral. The results also indicate that the expectations of the general public are self-fulfilling.Originality/valueIESH has only commenced from September 2005, hence is relatively new as compared to other survey in developed countries. Being a new data set so far, the authors could not locate any study devoted in analyzing the behavior of the data with other macroeconomic variables.