We study the impact of artificial intelligence (AI) on labor markets using establishment-level data on the near universe of online vacancies in the United States from 2010 onward. There is rapid growth in AI-related vacancies over 2010–18 that is driven by establishments whose workers engage in tasks compatible with AI’s current capabilities. As these AI-exposed establishments adopt AI, they simultaneously reduce hiring in non-AI positions and change the skill requirements of remaining postings. While visible at the establishment level, the aggregate impacts of AI-labor substitution on employment and wage growth in more exposed occupations and industries is currently too small to be detectable.

In an ongoing evaluation of post-secondary financial aid, we use random assignment to assess the causal effects of large privately-funded aid awards. Here, we compare the unbiased causal effect estimates from our RCT with two types of non-experimental econometric estimates. The first applies a selection-on-observables assumption in data from an earlier, nonrandomized cohort; the second uses a regression discontinuity design. Selection-on-observables methods generate estimates well below the experimental benchmark. Regression discontinuity estimates are similar to experimental estimates for students near the cutoff, but sensitive to controlling for the running variable, which is unusually coarse.

Using Current Population Survey and US Army administrative data, we document that between 2000 and 2010, the employment rate of Vietnam era veterans fell markedly relative to non-veterans of the same cohorts while simultaneously their enrollment increased steeply in the Veterans Disability Compensation (DC) program, which provides healthcare and transfer payments to veterans with service-connected disabilities. Thirty percent of Vietnam era Army veterans enrolled in DC in 2006 received benefits for Post-Traumatic Stress Disorder, with median annual payments of $25,500. The declining employment and rising transfer payments to Vietnam era veterans underscore the long-term private and public costs of wartime service, potentially stemming from both adverse health consequences and policies that have expanded benefits eligibility.

Even before the Great Recession, US employment growth was unimpressive. Between 2000 and 2007, the economy gave back the considerable employment gains achieved during the 1990s, with a historic contraction in manufacturing employment being a prime contributor to the slump. We estimate that import competition from China, which surged after 2000, was a major force behind both recent reductions in US manufacturing employment and—through input-output linkages and other general equilibrium channels—weak overall US job growth. Our central estimates suggest job losses from rising Chinese import competition over 1999–2011 in the range of 2.0–2.4 million.

Abstract We analyze the effect of exposure to international trade on earnings and employment of U.S. workers from 1992 through 2007 by exploiting industry shocks to import competition stemming from China’s spectacular rise as a manufacturing exporter paired with longitudinal data on individual earnings by employer spanning close to two decades. Individuals who in 1991 worked in manufacturing industries that experienced high subsequent import growth garner lower cumulative earnings, face elevated risk of obtaining public disability benefits, and spend less time working for their initial employers, less time in their initial two-digit manufacturing industries, and more time working elsewhere in manufacturing and outside of manufacturing. Earnings losses are larger for individuals with low initial wages, low initial tenure, and low attachment to the labor force. Low-wage workers churn primarily among manufacturing sectors, where they are repeatedly exposed to subsequent trade shocks. High-wage workers are better able to move across employers with minimal earnings losses and are more likely to move out of manufacturing conditional on separation. These findings reveal that import shocks impose substantial labor adjustment costs that are highly unevenly distributed across workers according to their skill levels and conditions of employment in the pre-shock period.

There is no evaluation of the consequences of Disability Insurance (DI) receipt that captures the effects on households’ net income and consumption expenditure, family labor supply, or benefits from other programs. Combining detailed register data from Norway with an instrumental variables approach based on random assignment to appellant judges, we comprehensively assess how DI receipt affects these understudied outcomes. To consider the welfare implications of the findings from this instrumental variables approach, we estimate a dynamic model of household behavior that translates employment, reapplication, and savings decisions into revealed preferences for leisure and consumption. The model-based results suggest that on average, the willingness to pay for DI receipt is positive and sizable. Because spousal labor supply strongly buffers the household income and consumption effects of DI allowances, the estimated willingness to pay for DI receipt is smaller for married than single applicants. (JEL D12, D14, H55, I38, J14, J22)