Abstract:
Purpose – The author analyzes 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 author employs 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/approach –This paper studies the dynamic behavior of inflation expectations survey
data in two folds. First, the author analyzes the time series property of the survey data. The author begins with
testing the stationarity property of the series, followed by the casual relationship between the expected and
actual inflation. The author further examines the short-run and long-run behavior of the IESH with actual
inflation. Employing autoregressive distributed lag and Johansen co-integration, the author tested if a long-run
relationship exists between the variables. In the second approach, the author investigates the determinants of
inflation expectations by employing a non-recursive SVAR model.
Findings – The 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
author finds 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/value – IESH 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 author could not locate any study devoted
in analyzing the behavior of the data with other macroeconomic variables.