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The Inflation Expectations Survey of Households, conducted by the Reserve Bank of India (RBI), indicates that there is considerable disparity in inflation expectations across cities in India. The purpose of this paper is to investigate why different cities exhibit heterogeneous inflation expectations despite coming under a central monetary policy umbrella.

First, the correspondence between city-level inflation expectations and city-specific economic characteristics is mapped. Second, how the disagreement in inflation expectations across cities, measured by dispersion, behaves over the business cycle is investigated. Finally, using seemingly unrelated regression technique, the economic factors that play a role in explaining inflation expectations heterogeneity across cities are estimated.

Cities with higher economic activity and cost of living have higher inflation expectations. Disagreement across cities regarding inflation expectations rise with an increase in output gap and inflation. Information friction plays an important role in explaining the disparity in inflation expectations across cities, and the effects of macro-level factors vary across cities, thereby accentuating expectations dispersion.

Monetary policy-related communication by the RBI (toward the general public) should increase in order to address information friction, which, in turn, would temper down the extent of inflation expectations heterogeneity across cities in India.

This is a novel application of the data from the monetary policy perspective. Heterogeneity in inflation expectations across cities or regions is an unexplored area. The use of nightlights as a proxy for city-level economic activity in India (in absence of data on city-level income) is another original contribution.

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.

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.

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.

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.