“The Response of Consumer Spending to Changes in Gasoline Prices,” was co-authored by Michael Gelman (U-M Job Candidate), Yuriy Gorodnichenko (University of California, Berkeley; U-M PhD alumnus), Shachar Kariv (University of California, Berkeley), Dmitri Koustas (University of California, Berkeley), Matthew D. Shapiro (University of Michigan), Dan Silverman (Arizona State University), and Steven Tadelis (University of California, Berkeley).

This study estimates the marginal propensity to consume (MPC) to be around one, so the average consumer spends all of their gasoline savings on non-gasoline items. This estimate is higher than those of past studies.

The authors examine daily transaction-level data collected from over one million consumers. This unprecedented data has allowed them to create a fuller picture of consumer spending habits and how they react to changes in the price of gasoline. Previous studies that have looked at MPC were based on small samples, noisy data, or a non-comprehensive picture of consumers’ spending. This study is based on a data infrastructure developed by University of Michigan and University of California researchers the links individuals’ accounts to accurately measure spending, income, assets, and debt.  This study uses machine-learning techniques to identify spending on gasoline.

Development of the infrastructure for this research is supported by a grant from the Alfred P. Sloan Foundation to the University of Michigan.

“The Response of Consumer Spending to Changes in Gasoline Prices,”

Abstract

This paper estimates how overall consumer spending responds to changes in gasoline prices. It uses the differential impact across consumers of the sudden, large drop in gasoline prices in 2014 for identification. This estimation strategy is implemented using comprehensive, daily transaction-level data for a large panel of individuals. The estimated marginal propensity to consume (MPC) is approximately one, a higher estimate than estimates found in less comprehensive or well-measured data. This estimate takes into account the elasticity of demand for gasoline and potential slow adjustment to changes in prices. The high MPC implies that changes in gasoline prices have large aggregate effects.

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