We estimate the returns to IRS audits of taxpayers across the income distribution. We find an additional $1 spent auditing taxpayers above the 90th income percentile yields more than $12 in revenue, while audits of below-median income taxpayers yield $5. We draw upon comprehensive internal accounting information and audit-level enforcement logs to quantify the average costs and revenues associated with each audit. We begin by estimating the average initial return to all audits of US taxpayers filing in 2010-2014. On average, $1 in audit spending raises $2.17 in initial revenue. Audits of high-income taxpayers are more costly, but the additional revenue raised more than offsets the costs. Audits of the 99-99.9th percentile have a 3.2:1 return; audits of the top 0.1% return 6.3:1. We then exploit the 40% audit reduction between tax years 2010 and 2014 to examine the returns to marginal audits. We find they exceed the returns to average audits. Revenues remain relatively unchanged but marginal costs fall below average costs due to economies of scale. Next, we use randomly selected audits to examine the impact of an initial audit on future revenue. This specific deterrence effect produces at least three times more revenue than the initial audit. Deterrence effects are relatively consistent across the income distribution. This results in the 12:1 return above the 90th percentile. We conclude by estimating the welfare consequences of audits using the MVPF framework and comparing audits to other revenue raising policies. We find that audits raise revenue at lower welfare cost.
Paper Executive SummaryWe examine the geographic incidence of local labor market growth across locations of childhood residence. We ask: when wages grow in a given US labor market, do the benefits flow to individuals growing up in nearby or distant locations? We begin by constructing new statistics on migration rates across labor markets between childhood and young adulthood. This migration matrix shows 80% of young adults migrate less than 100 miles from where they grew up. 90% migrate less than 500 miles. Migration distances are shorter for Black and Hispanic individuals and for those from low-income families. These migration patterns provide information on the first order geographic incidence of local wage growth. Next, we explore the responsiveness of location choices to economic shocks. Using geographic variation induced by the recovery from the Great Recession, we estimate the elasticity of migration with respect to increases in local labor market wage growth. We develop and implement a novel test for validating whether our identifying wage variation is driven by changes in labor market opportunities rather than changes in worker composition due to sorting. We find that higher wages lead to increased in-migration, decreased out-migration and a partial capitalization of wage increases into local prices. Our results imply that for a 2 rank point increase in annual wages (approximately $1600) in a given commuting zone (CZ), approximately 99% of wage gains flow to those who would have resided in the CZ in the absence of the wage change. The geographically concentrated nature of most migration and the small magnitude of these migration elasticities suggest that the incidence of labor market conditions across childhood residences is highly local. For many individuals, the “radius of economic opportunity” is quite narrow.
Paper
This paper outlines the case for using the Marginal Value of Public Funds (MVPF) in empirical welfare analysis. It compares the MVPF approach with more traditional welfare metrics such as the Cost-Benefit Ratio and the Net Social Benefits criterion. It outlines the advantages of the MVPF approach relative to these metrics. In building the case for the MVPF, this paper also addresses several misconceptions about the MVPF that appear in recent literature.
PaperAn earlier draft circulated under the title "The Advantages of the MVPF: A Comment on Garcia and Heckman (2022)", and is availabe
here.
Investing in college carries high returns but comes with considerable risk. Financial products like equity contracts can mitigate this risk, yet college is typically financed through non-dischargeable, government-backed student loans. This paper argues that adverse selection has unraveled private markets for college-financing contracts that mitigate risk. We use survey data on students' expected post-college outcomes to estimate their knowledge about future outcomes and quantify the threat of adverse selection in markets for equity contracts and several state-contingent debt contracts. We find students hold significant private knowledge of their future earnings, academic persistence, employment, and loan repayment likelihood, beyond what is captured by observable characteristics. Our empirical results imply that a typical college-goer must expect to pay back $1.64 in present value for every $1 of equity financing to cover the financier's costs of covering those who would adversely select their contract. We estimate that college-goers are not willing to accept these terms so that private markets unravel. Nonetheless, our framework quantifies significant welfare gains from government subsidies that would open up these missing markets and partially insure college-going risks.
Paper Executive Summary Slides Unraveling Example SlidesWe construct a publicly available atlas of children’s outcomes in adulthood by Census tract using anonymized longitudinal data covering nearly the entire U.S. population. For each tract, we estimate children’s earnings distributions, incarceration rates, and other outcomes in adulthood by parental income, race, and gender. These estimates allow us to trace the roots of outcomes such as poverty and incarceration back to the neighborhoods in which children grew up. We find that children’s outcomes vary sharply across nearby tracts: for children of parents at the 25th percentile of the income distribution, the standard deviation of mean household income at age 35 is $5,000 across tracts within counties. We illustrate how these tract-level data can provide insight into how neighborhoods shape the development of human capital and support local economic policy using two applications. First, we show that the estimates permit precise targeting of policies to improve economic opportunity by uncovering specific neighborhoods where certain subgroups of children grow up to have poor outcomes. Neighborhoods matter at a very granular level: conditional on characteristics such as poverty rates in a child’s own Census tract, characteristics of tracts that are one mile away have little predictive power for a child’s outcomes. Our historical estimates are informative predictors of outcomes even for children growing up today because neighborhood conditions are relatively stable over time. Second, we show that the observational estimates are highly predictive of neighborhoods’ causal effects, based on a comparison to data from the Moving to Opportunity experiment and a quasi- experimental research design analyzing movers’ outcomes. We then identify high-opportunity neighborhoods that are affordable to low-income families, providing an input into the design of affordable housing policies. Our measures of children’s long-term outcomes are only weakly correlated with traditional proxies for local economic success such as rates of job growth, showing that the conditions that create greater upward mobility are not necessarily the same as those that lead to productive labor markets.