Working Papers:
Every Day Counts: Absenteeism and the Returns to Education in High-Poverty Schools
Abstract
Why do students in high-poverty schools perform worse academically and in the labor market than their peers in low-poverty schools? We show that a key difference is how regularly students attend school. We use transitory shocks to absences arising from factors like respiratory illnesses to estimate the effect of improving school-wide attendance. Among high-poverty schools, moving from the 75th to the 25th percentile of the absence distribution would raise high school graduation rates by 2.3 percentage points and increase average earnings at age 25 by $3,600. Our findings suggest that up to one-third of the achievement gap between low- and high-poverty schools can be attributed to absenteeism. We show that policies aimed at improving attendance in high-poverty schools can close these disparities in outcomes. We estimate that nationwide adoption of "Communities in Schools", the country's largest student support program, could reduce the achievement gap by 20%, primarily through its effect on attendance.
Summary | Slides | Data | Opportunity Atlas | Brookings Webinar
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Abstract
We show that intergenerational mobility changed rapidly by race and class in recent decades and use these trends to study the causal mechanisms underlying changes in economic mobility. For white children in the U.S. born between 1978 and 1992, earnings increased for children from high-income families but decreased for children from low-income families, increasing earnings gaps by parental income ("class") by 30%. Earnings increased for Black children at all parental income levels, reducing white-Black earnings gaps for children from low-income families by 30%. Class gaps grew and race gaps shrank similarly for non-monetary outcomes such as educational attainment, standardized test scores, and mortality rates. Using a quasi-experimental design, we show that the divergent trends in economic mobility were caused by differential changes in childhood environments, as proxied by parental employment rates, within local communities defined by race, class, and childhood county. Outcomes improve across birth cohorts for children who grow up in communities with increasing parental employment rates, with larger effects for children who move to such communities at younger ages. Children's outcomes are most strongly related to the parental employment rates of peers they are more likely to interact with, such as those in their own birth cohort, suggesting that the relationship between children's outcomes and parental employment rates is mediated by social interaction. Our findings imply that community-level changes in one generation can propagate to the next generation and thereby generate rapid changes in economic mobility.Growing Class Gaps, Shrinking Race Gaps
Who Marries Whom? The Role of Segregation by Race and Class
Summary | County Level Marriage Patterns
Abstract
Americans rarely marry outside of their race or class group. We distinguish between two possible explanations: a lack of exposure to other groups versus a preference to marry within group. We develop an instrument for neighborhood exposure to opposite-sex members of other race and class groups using variation in sex ratios among nearby birth cohorts in childhood neighborhoods. We then test whether increased exposure results in more interracial (white-Black) and interclass (top-to-bottom parent income quartile) marriages. Increased exposure to opposite-sex members of other class groups generates a substantial increase in interclass marriage, but increased exposure to other race groups has no detectable effect on interracial marriage. We use these results to estimate a spatial model of the marriage market and quantify the impact of reducing residential segregation in general equilibrium. For small changes in exposure, the model implies effects in line with recent estimates from policy experiments. We then use the model to assess the overall contribution of segregation and find that residential segregation has large effects on interclass, but not interracial, marriage.
Can Individualized Student Supports Improve Economic Outcomes for Children in High Poverty Schools?
Abstract
How can we improve outcomes for low-income students? We analyze the adult earnings impacts of the largest comprehensive student support program in the United States. Communities in Schools (CIS) places a “navigator” in high-poverty schools who provides an integrated system of supports to students, including academic (e.g., tutoring), economic (e.g., access to food assistance, housing), and mentoring. In 2023, CIS worked with 1.8 million students in 3,750 schools. Using later-treated CIS schools as a control, we estimate that four years of exposure to CIS generates a $1,500 (6% of control mean) increase in earnings at age 30. Effects are larger for students from low-income families and are driven by a reduction in non-employment and an increase in the probability of having a low-paying job. Each child exposed to four years of CIS is expected to pay an additional $9,000 in taxes between ages 18-65, which compares favorably to the direct cost of the program. Our results are relevant for the growing community school movement and illuminate a possible path for improving economic mobility in low opportunity neighborhoods.Impact of CIS on Earnings in Adulthood
What Explains Temporal and Geographic Variation in the Early US Coronavirus Pandemic?
Conditionally accepted at Review of Economic Design
Abstract
We provide new evidence on the drivers of the early US coronavirus pandemic. We combine an epidemiological model of disease transmission with quasi-random variation arising from the timing of stay-at-home-orders to estimate the causal roles of policy interventions and voluntary social distancing. We then relate the residual variation in disease transmission rates to observable features of cities. We estimate significant impacts of policy and social distancing responses, but we show that the magnitude of policy effects is modest, and most social distancing is driven by voluntary responses. Moreover, we show that neither policy nor rates of voluntary social distancing explain a meaningful share of geographic variation. The most important predictors of which cities were hardest hit by the pandemic are exogenous characteristics such as population and density.Publications:
Within-Industry Agglomeration of Occupations: Evidence from Census Microdata
Journal of Regional Science 59.5 (2019): 910-930
Abstract
This study uses worker-level data on industry, occupation, and place of work to explore differences in the spatial properties of production, administrative, and R&D occupation groups within industries. To measure differences, we calculate location quotients at the local labor market level and the Duranton and Overman (2005) agglomeration index for each group. We find appreciable differences in the spatial distribution of occupation groups within most manufacturing industries, with R&D occupations consistently exhibiting the highest degree of spatial concentration. Our results are consistent with the core theoretical and empirical results in the agglomeration literature.Research in Progress:
Leveraging Mixed Methods to Understand Economic and Sociological Mechanisms Underlying Recent Changes in Intergenerational Mobility
The Effect of the Minimum Wage on Low-Wage Workers
The Effect of Low-level Arrests on the Early-life Trajectory of Urban Youth
Interracial Marriage and Racial Disparities
Any opinions and conclusions expressed herein are those of the author and do not represent the views of the U.S. Census Bureau. The Census Bureau has ensured appropriate access and use of confidential data and has reviewed these results for disclosure avoidance protection (Project 7519874: Segregation and Marriage CBDRB-FY23-0492, CBDRB-FY23-CES014-009, Student Supports CBDRB-FY23-CES014-028, Class and Race Gaps CBDRB-FY22-CES010-004, CBDRB-FY23-0375)