The first chapter examines the result that cash on hand is the most important source of variation in explaining heterogeneity in the marginal propensity to consume (MPC). While the standard hypothesis is that differences in financial circumstances caused by temporary income shocks explain this result, this paper finds that differences across persistent characteristics are just as important. To reach this finding, this paper develops a buffer stock model with discount factor heterogeneity and estimates it using a novel panel data set from a personal finance app that jointly measures spending, income, and liquid assets. In the model, within-individual variation in cash on hand results from temporary income shocks while across-individual variation in cash on hand results from differences in persistent characteristics. The panel nature of the data separately identifies temporary and persistent drivers of the MPC while previous studies using cross-sectional data typically confound these concepts. Simulations from the estimated model imply that ignoring heterogeneity in persistent characteristics leads to underestimating the aggregate MPC.The second chapter examines how individuals adjusted spending and saving in response to a temporary drop in income due to the 2013 U.S. government shutdown. The shutdown cut paychecks by 40% for affected employees, which was recovered within 2 weeks. Because it affected only the timing of payments, the shutdown provides a distinct experiment allowing estimates of the response to a liquidity shock holding income constant. Spending dropped sharply implying a naive estimate of the marginal propensity to spend of 0.58. This estimate overstates how consumption responded. While many individuals had low liquidity, they used multiple strategies to smooth consumption including delay of recurring payments such as mortgages and credit card balances. This is joint with Shachar Kariv, Matthew D. Shapiro, Dan Silverman, and Steven Tadelis.The third chapter 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 that 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. This is joint with Yuriy Gorodnichenko, Shachar Kariv, Dmitri Koustas, Matthew D. Shapiro, Dan Silverman, and Steven Tadelis.The fourth chapter examines the response of food expenditures to the receipt of paychecks using financial account data from a personal finance app. Similar to previous studies, this paper finds that food expenditures increase during the week the paycheck is received. While the standard explanation for this result is temporary liquidity constraints, this paper argues otherwise. Intuitively, it;;s unlikely that individuals will be liquidity constrained during the weeks they receive their paycheck. Therefore, their decision to spend more during weeks in which they have more liquidity likely reflects preferences and not constraints. The intuition is formalized through specifying a buffer stock model of consumption. Model simulations show that indeed consumption behavior is not affected by liquidity during the week of the paycheck. The empirical results match the theoretical predictions and confirm that liquidity constraints cannot explain excess sensitivity.
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Understanding Household Consumption and Saving Behavior using Account Data
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