Research

Publications and Forthcoming:

This paper presents a new data infrastructure for measuring economic activity. The infrastructure records transactions and account balances, yielding measurements with scope and accuracy that have little precedent in economics. The data are drawn from a diverse population that overrepresents males and younger adults but contains large numbers of underrepresented groups. The data infrastructure permits evaluation of a benchmark theory in economics that predicts that individuals should use a combination of cash management, saving, and borrowing to make the timing of income irrelevant for the timing of spending. As in previous studies and in contrast to the predictions of the theory, there is a response of spending to the arrival of anticipated income. The data also show, however, that this apparent excess sensitivity of spending results largely from the coincident timing of regular income and regular spending. The remaining excess sensitivity is concentrated among individuals with less liquidity.

Using comprehensive account records, this paper examines how individuals adjusted spending and saving in response to a temporary drop in liquidity due to the 2013 U.S. government shutdown. The shutdown cut paychecks by 40% for affected employees, which was recovered within 2 weeks. Because the shutdown affected only the timing of payments, it provides a distinctive experiment allowing estimates of the response to a liquidity shock holding income constant. Spending dropped sharply, implying a naïve estimate of 58 cents less spending for every dollar of lost liquidity. This estimate overstates the consumption response. While many individuals had low liquid assets, they used multiple sources of short-term liquidity to smooth consumption. Sources of short-term liquidity include delaying recurring payments such as for mortgages and credit card balances.

Many empirical studies show that cash on hand is the most important source of variation in explaining heterogeneity in the marginal propensity to consume (MPC). To explain this, one class of models focuses on the role of heterogeneity in persistent characteristics across individuals while the other class focuses on the role of circumstances within individuals. This paper provides the first empirical measure of the relative importance of circumstances and characteristics in explaining the variance of the MPC. It then maps this empirical measure into a buffer stock model with discount factor heterogeneity to assess how well it explains the data.

Many studies have shown that consumption responds to the arrival of predictable income (excess sensitivity). This paper uses a buffer stock model of consumption to understand what causes excess sensitivity and to test which parametrization is consistent with empirical excess sensitivity estimates. Using high frequency granular data from a personal finance app, it finds that while liquidity constraints are a proximate cause, preferences are the ultimate cause of excess sensitivity. Furthermore, it finds that for feasible parameters, a quasi hyperbolic version of the model is more consistent with the level of excess sensitivity relative to a standard exponential model.

There is a tight relationship between having low liquidity and a high marginal propensity to consume both in theoretical models and in econometric evidence about behavior.  This paper analyzes the theory and behavior surrounding income tax withholding and refunds. It develops a model where rational cash management with asymmetric cost of increasing or decreasing liquidity endogenizes the relationship between illiquidity and excess sensitivity. The analysis accounts for the finding that households tend to spend tax refunds as if they were liquidity constrained despite the fact that they could increase liquidity by reducing withholding. The model’s predictions are supported by evidence from a large panel of individuals.

We examine the more than $800 billion in cash that was distributed to all but the highest-income households in the three rounds of Economic Impact Payments (EIPs). Although there were delays in getting the money to some vulnerable, low-income households, electronic disbursement allowed the Treasury to make payments quickly—about two weeks after the initial legislation was signed and even more quickly in the subsequent rounds. The available evidence suggests that the payments led to a rapid increase in spending; consumers spent about the same or a smaller fraction of these payments relative to similar payments in past downturns. The payments were not, of course, well targeted. Some households that weren’t adversely affected by the pandemic received the money, but other recipients were adversely affected but weren’t eligible for or didn’t promptly receive more targeted benefits (such as UI or rental assistance) and were greatly aided by the EIPs.  

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 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.

Working Papers:

This paper estimates the consumption response to a delay in the receipt of unemployment insurance (UI) benefits using transaction-level debit card data on a sample of low-income individuals. The historic increase in UI claims from 250,000 to roughly 6.2 million in March 2020 overwhelmed state UI agencies and led to widespread delays in processing claims. Workers who experienced periods of uninsured job loss during processing delays were retroactively compensated with lump sum payments. UI processing delays therefore caused a shift to both the timing and to the smoothness of benefit receipt. We find that delay-affected individuals reduced spending during periods of uninsured job loss and sharply increased spending when lump sum payments arrived. The results highlight the financial fragility of individuals in our sample as well as the valuable consumption-smoothing role of UI for this group.

Works in Progress: