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 construct our estimates by drawing from comprehensive internal accounting information and audit-level enforcement logs. We begin by estimating the average initial return to all audits of U.S. taxpayers filing in tax years 2010–2014. On average, $1 in audit spending initially raises $2.17 in 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 initial 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 effect of an initial audit on future revenue. This individual 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.

We develop a set of frameworks for welfare analysis of Medicaid and apply them to the Oregon Health Insurance Experiment, a Medicaid expansion for low-income, uninsured adults that occurred via random assignment. Across different approaches, we estimate recipient willingness to pay for Medicaid between $0.5 and $1.2 per dollar of the resource cost of providing Medicaid; estimates of the expected transfer Medicaid provides to recipients are relatively stable across approaches, but estimates of its additional value from risk protection are more variable. We also estimate that the resource cost of providing Medicaid to an additional recipient is only 40% of Medicaid's total cost; 60% of Medicaid spending is a transfer to providers of uncompensated care for the low-income uninsured.

We present new evidence on trends in intergenerational mobility in the United States using administrative earnings records. We find that percentile rank-based measures of intergenerational mobility have remained extremely stable for the 1971-1993 birth cohorts. For children born between 1971 and 1986, we measure intergenerational mobility based on the correlation between parent and child income percentile ranks. For more recent cohorts, we measure mobility as the correlation between a child's probability of attending college and her parents' income rank. We also calculate transition probabilities, such as a child's chances of reaching the top quintile of the income distribution starting from the bottom quintile. Based on all of these measures, we find that children entering the labor market today have the same chances of moving up in the income distribution (relative to their parents) as children born in the 1970s. However, because inequality has risen, the consequences of the “birth lottery” - the parents to whom a child is born - are larger today than in the past.

We study the welfare impacts of 96 climate-related tax and spending policies. We extend and apply the marginal value of public funds (MVPF) framework, most notably providing a new method for incorporating learning-by-doing spillovers. We find subsidies for the production of clean energy (such as wind production tax credits) have higher MVPFs than all other subsidies in our sample, including EV subsidies. Conservation nudges have large MVPFs when targeting regions with dirty grids. Fuel taxes and cap-and-trade policies are highly efficient means of raising revenue. We also construct traditional cost-per-ton estimates and compare and contrast the lessons they provide.

We show that differences in childhood environments shape gender gaps in adulthood by documenting three facts using population tax records for children born in the 1980s. First, gender gaps in employment rates, earnings, and college attendance vary substantially across the parental income distribution. Notably, the traditional gender gap in employment rates is reversed for children growing up in poor families: boys in families in the bottom quintile of the income distribution are less likely to work than girls. Second, these gender gaps vary substantially across counties and commuting zones in which children grow up. The degree of variation in outcomes across places is largest for boys growing up in poor, single-parent families. Third, the spatial variation in gender gaps is highly correlated with proxies for neighborhood disadvantage. Low-income boys who grow up in high-poverty, high-minority areas work significantly less than girls. These areas also have higher rates of crime, suggesting that boys growing up in concentrated poverty substitute from formal employment to crime. Together, these findings demonstrate that gender gaps in adulthood have roots in childhood, perhaps because childhood disadvantage is especially harmful for boys.

We study the sources of racial disparities in income using anonymized longitudinal data covering nearly the entire U.S. population from 1989 to 2015. We document three results. First, black Americans and American Indians have much lower rates of upward mobility and higher rates of downward mobility than whites, leading to persistent disparities across generations. Conditional on parent income, the black-white income gap is driven by differences in wages and employment rates between black and white men; there are no such differences between black and white women. Hispanic Americans have rates of intergenerational mobility more similar to whites than blacks, leading the Hispanic-white income gap to shrink across generations. Second, differences in parental marital status, education, and wealth explain little of the black-white income gap conditional on parent income. Third, the black-white gap persists even among boys who grow up in the same neighborhood. Controlling for parental income, black boys have lower incomes in adulthood than white boys in 99% of Census tracts. The few areas with small black-white gaps tend to be low-poverty neighborhoods with low levels of racial bias among whites and high rates of father presence among blacks. Black males who move to such neighborhoods earlier in childhood have significantly better outcomes. However, less than 5% of black children grow up in such areas. Our findings suggest that reducing the black-white income gap will require efforts whose impacts cross neighborhood and class lines and increase upward mobility specifically for black men.

We construct a public atlas of mean outcomes in adulthood by childhood census tract. Outcomes vary sharply across neighborhoods: For children whose parents earn $27,000, the standard deviation of mean household income in adulthood is $10,420 across tracts within counties. Only half the variation in outcomes is explained by traditional measures of neighborhood opportunity like poverty rates. Experimental and quasi-experimental estimates indicate 60 percent of the variation in outcomes across neighborhoods is driven by causal effects. We demonstrate how our statistics can be applied to better target policies to improve low-opportunity areas and help families move to affordable high-opportunity areas.

Low-income families often live in low-upward-mobility neighborhoods. We study why by using a randomized trial with housing voucher recipients that provided information, financial support, and customized search assistance to move to high-opportunity neighborhoods. The treatment increased the fraction moving to high-upward-mobility areas from 15 to 53 percent. A second trial reveals this treatment effect is driven primarily by customized search assistance. Qualitative interviews show that the intervention relaxed bandwidth constraints and addressed family-specific needs. Our findings imply many low-income families do not have strong preferences to stay in low-opportunity areas and that barriers in housing search significantly increase residential segregation by income.