This study measures the impact of rapidly placing single adults experiencing homelessness in housing programs on future homelessness, crime, and health. Using a caseworker placement tendencies design and a novel dataset constructed by linking administrative records from multiple public agencies in Los Angeles County, I estimate that rapidly placing individuals in housing programs significantly reduces the likelihood of future return to the homeless support system, crime, and reliance on emergency cash assistance, yet it does not have a detectable effect on health services utilization. These findings demonstrate that rapid housing placements can have both rehabilitative and potentially cost-saving impacts. 

In the 1920s, the United States substantially reduced immigration by imposing country-specific entry quotas. We compare local labor markets differentially exposed to the quotas due to variation in the national-origin mix of their immigrant population. US-born workers in areas losing immigrants did not benefit relative to workers in less exposed areas. Instead, in urban areas, European immigrants were replaced with internal migrants and immigrants from Mexico and Canada. By contrast, farmers shifted toward capital-intensive agriculture, and the immigrant-intensive mining industry contracted. These differences highlight the uneven effects of the quota system at the local level. 

This paper examines how the U.S. immigration restrictions of the 1920s affected the wages of low-skilled workers using newly digitized annual wage data from 1910 to 1930. Exploiting variation across local labor markets, we find that wages for low-skilled workers rose faster in areas more affected by the restrictions. These wage effects emerged early in the 1920s and persisted throughout the decade across manufacturing, construction, and agricultural sectors. Our findings help explain previously documented internal migration patterns and demonstrate how reduced immigration affected labor markets through both direct supply effects and subsequent adjustment mechanisms. 

We analyze the effects of legalizing marijuana for recreational use on state economic and social outcomes using difference-in-differences estimation robust to staggered timing and heterogeneity of treatment. We find moderate economic gains accompanied by some social costs. Post-legalization, average state income per capita grew by 3 percent, house prices by 6 percent, and population by 2 percent. However, substance use disorders, chronic homelessness, and arrests increased by 17, 35, and 13 percent, respectively. Early legalizing states experienced larger economic gains yet similar social costs, implying a potential first-mover advantage 

Understanding how occupations differ in their exposure to emissions-intensive activities is fundamental for analyzing labor market risks amid changes in the energy mix. We develop new, data-driven measures of occupational emissions intensity that capture heterogeneity across and within industries. Our baseline Occupational Emissions Score (OES), along with wage- and concentration-adjusted variations (WOES and COES), highlights substantial differences in emissions exposure across the U.S. workforce. Applying these measures, we document several new facts: emissions are highly concentrated in a small set of occupations; emissions intensity has declined over time; and even within industries, workers' exposure varies significantly by occupation. Higher-emission occupations are disproportionately held by older, male, native-born, and less-educated workers, and are concentrated in particular regions. While higher-emission occupations tend to experience lower employment growth, they show higher hourly wages and vacancy growth. An event study of coal mine closures further shows that high-emission occupations are more exposed to structural shocks. Together, our measures provide a comprehensive, granular framework for understanding occupational risk and adjustment during major economic shifts.