Research

Abstract: The Earned Income Tax Credit (EITC) is the largest cash-based means-tested transfer program in the United States. In 2021, 31 million households received $64 billion from the federal EITC. Twenty-eight states also offer eligible taxpayers a supplement to the federal program. An estimated one-fifth of eligible households fail to claim the federal credit, but little is known about take-up of these state programs. We use administrative data from California on the population of Supplemental Nutrition Assistance Program (SNAP) recipients linked to state tax records to estimate the number of households who are eligible for California’s supplement to the federal EITC (CalEITC) but do not claim it. We find that over 400,000 households who received SNAP benefits and who were eligible for the state EITC in 2017 did not receive the credit. This includes approximately 40,000 eligible households who claimed the federal EITC but not the state credit; nearly 98,000 eligible households who filed a state tax return but did not claim the state or federal credit; and roughly 270,000 eligible households who did not file a state tax return. The corresponding take-up rate for the CalEITC among eligible SNAP-enrolled households was 54%. Altogether, these households left a total of $71 million in state EITC funds on the table. If received, these credits would have increased incomes among these households by 2.7% and increased total state EITC outlays by 20%.

Abstract: The Earned Income Tax Credit (EITC) distributes more than $60 billion to over 20 million low-income families annually. Nevertheless, an estimated one-fifth of eligible households do not claim it. We ran six pre-registered, large-scale field experiments, involving over one million subjects, to test whether “nudges” could increase EITC take-up. Despite varying the content, design, messenger, and mode of our messages, we find no evidence that they affected households’ likelihood of filing a tax return or claiming the credit. We conclude that even the most behaviorally informed low-touch outreach efforts cannot overcome the barriers faced by low-income households who do not file returns.

Abstract: We use traditional and non-traditional data to measure the collapse and partial recovery of the U.S. labor market from March to early July, contrast this downturn to previous recessions, and provide preliminary evidence on the effects of the policy response. For hourly workers at both small and large businesses, nearly all of the decline in employment occurred between March 14 and 28. It was driven by low-wage services, particularly the retail and leisure and hospitality sectors. A large share of the job losses in small businesses reflected firms that closed entirely, though many subsequently reopened. Firms that were already unhealthy were more likely to close and less likely to reopen, and disadvantaged workers were more likely to be laid off and less likely to return. Most laid off workers expected to be recalled, and this was predictive of rehiring. Shelter-in-place orders drove only a small share of job losses. Last, states that received more small business loans from the Paycheck Protection Program and states with more generous unemployment insurance benefits had milder declines and faster recoveries. We find no evidence that high UI replacement rates drove job losses or slowed rehiring.

Abstract: Many U.S. safety-net programs condition benefit eligibility on work. Eliminating work requirements would better target benefits to the neediest families but attenuates pro-work incentives. Using administrative records, we study how expanding a California child tax credit to non-workers affected maternal labor supply. We rely on quasi-random birth-timing and a novel method for using placebo analyses to maximize estimator precision. Eliminating the work requirement caused very few mothers to exit the labor force; our 95% confidence interval excludes reductions over one-third of one percent. Our results suggest expanding tax benefits to the lowest-income families need not meaningfully reduce workforce participation.

Abstract: Many households eligible for the Supplemental Nutrition Assistance Program (SNAP) do not enroll. Using a new dataset of monthly enrollment histories for all SNAP participants in California between 2005 and 2020, this paper documents how procedures required to verify eligibility lower retention and contribute to incomplete take-up. Whether this non-participation is optimal depends on whether these hassles most deter enrollment among more advantaged prospective applicants. I find that the vast majority of households who exit SNAP are income eligible in the months before and after their exit. At the same time, no longer eligible households, those with higher earnings and those less likely to be food insecure are more likely to exit. My findings underscore the policy tradeoff inherent to administering means-tested programs.

Abstract: Accurately measuring household income and poverty is essential to understanding the nation’s overall economic well-being. Many studies show that measurement error stemming from unit nonresponse, item non-response and misreporting biases key official statistics such as mean or median income and the official poverty rate. The direction of bias differs between these sources of measurement error. Unit and item nonresponse have been found to bias income up and poverty down (Rothbaum et al., 2021; Rothbaum and Bee, 2022; Bollinger et al., 2018; Hokayem, Raghunathan and Rothbaum, 2022), while misreporting can bias income down and poverty up (Bee and Mitchell, 2017; Meyer et al., 2021b; Larrimore, Mortenson and Splinter, 2020). Since these error components are typically studied in isolation, their overall impact on the accuracy of survey estimates remains unclear. This paper summarizes the National Experimental Well-being Statistics (NEWS) Project, which integrates this research and address each of these sources of bias simultaneously in order to produce more accurate estimates of household income and poverty. The NEWS project makes three unique contributions. First, we address as many sources of measurement error as we can simultaneously – including unit and item nonresponse and underreporting in surveys as well as the various challenges in administrative data such as measurement error, conceptual misalignment, and incomplete coverage. Second, we bring together all of the available survey and administrative data, which allows to address many of the shortcomings of individual data sources. Third, we propose a model to combine survey and administrative earnings data given measurement error in both sources, replacing ad hoc assumptions that have been used in prior work.

Abstract: Identifying the effect of taxes on the labor supply of people who would work regardless has been a longstanding empirical challenge. This paper proposes a new source of variation -- changes in projected year-end tax rates -- to measure households' intensive-margin labor supply elasticity. I extend the standard non-linear budget set approach to model multiple periods and uncertainty about future employment to predict how households will adjust labor supply throughout the tax year as a function of to-date earnings. I use survey and administrative data to measure how low-income households' earnings and employment vary within and across tax years and study how these households respond to changes in tax incentives. In contrast to most work studying employment responses to the Earned Income Tax Credit, I find a non-zero response to tax incentives among workers. My preferred estimates of intensive margin labor supply elasticity that ranges between .06 and .2, which are are similar to those estimated in an older literature which used non-linear budget set to estimate labor supply elasticities.