The modern definition of unemployment emerged in the late 1930s from research conducted at the Works Progress Administration and the Census Bureau. According to this definition, people who are not working but actively searching for work are counted as unemployed. This concept was first used in the Enumerative Check Census, a follow-up sample for the 1937 Census of Unemployment, and continued with the Monthly Report on the Labor Force survey, begun in December 1939 by the Works Progress Administration. A similar definition is now used to measure unemployment around the world.

We report the impacts of a job training program operated in the Dominican Republic. A random sample of applicants was selected to undergo training, and information was gathered 10–14 months after graduation. Unfortunately, people originally assigned to treatment who failed to show up were not included in the follow-up survey, potentially compromising the evaluation design. We present estimates of the program effect, including comparisons that ignore the potential nonrandomness of “no-show” behavior, and estimates that model selectivity parametrically. We find little indication of a positive effect on employment outcomes but some evidence of a modest effect on earnings, conditional on working.

Defined contribution pensions in many postsecondary institutions are funded by a combination of an employer premium and a mandatory employee premium. Individuals can also contribute to a supplemental savings account. Holding constant total compensation, standard reasoning suggests that supplemental savings should depend negatively on the sum of the employer and employee pension contributions. Contrarily, we find that the supplementary savings of professors are significantly more sensitive to employee contributions than to employer contributions. This asymmetry is consistent with different marginal propensities to save out of the salary and pension components of compensation. Nevertheless, impacts on lifetime utility are relatively modest.

We study the link between family violence and the emotional cues associated with wins and losses by professional football teams. We hypothesize that the risk of violence is affected by the “gain-loss” utility of game outcomes around a rationally expected reference point. Our empirical analysis uses police reports of violent incidents on Sundays during the professional football season. Controlling for the pregame point spread and the size of the local viewing audience, we find that upset losses (defeats when the home team was predicted to win by four or more points) lead to a 10% increase in the rate of at-home violence by men against their wives and girlfriends. In contrast, losses when the game was expected to be close have small and insignificant effects. Upset wins (victories when the home team was predicted to lose) also have little impact on violence, consistent with asymmetry in the gain-loss utility function. The rise in violence after an upset loss is concentrated in a narrow time window near the end of the game and is larger for more important games. We find no evidence for reference point updating based on the halftime score.