Knowledge that Transforms

Private equity firms are often criticized for laying off workers, but the evidence on who loses their jobs and why is scarce. This paper argues that explanations for job polarization also explain layoffs after private equity buyouts. Buyouts reduce agency problems, which triggers automation and offshoring. Using rich employer-employee data, we show that buyouts generally do not affect unemployment incidence. However, unemployment incidence doubles for workers in less productive firms who perform routine or offshorable job tasks. Job polarization is also much more marked among workers affected by buyouts than for the economy at large.

Leisure externalities across households have important implications for labor market regulations but have proven very difficult to identify. This paper exploits the unique features of school holidays and paid leave regulations in France to show that exogenous increases in the amount of leisure time enjoyed by workers living with children induce very significant increases in the demand for leisure of workers living in other households. We also provide evidence that these cross effects are driven by complementarities in nonmarket time rather than workplace norms or workplace externalities.

We estimate the effect of endogenous training participation on transitions in and out of employment for disadvantaged women in the Job Training Partnership Act (JTPA) study. Decomposing the effect of training on employment into its effects on transitions in and out of employment has the potential to develop more effective programs. We also consider a potentially serious identification problem that arises when individuals do not undertake training immediately, and we propose a test to shed light on this problem. We find that this problem is not important in our context. JTPA classroom training substantially reduced unemployment durations, and thus it complements programs that increase employment durations.

This paper uses experimental data from the Head Start Impact Study (HSIS) combined with nonexperimental data from the Early Childhood Longitudinal Study–Birth Cohort (ECLS-B) to study the performance of nonexperimental estimators for evaluating Head Start program impacts. The estimators studied include parametric cross-section and difference-in-differences regression estimators and nonparametric cross-section and difference-in-differences matching estimators. The estimators are used to generate program impacts on cognitive achievement test scores, child health measures, parenting behaviors, and parent labor market outcomes. Some of the estimators closely reproduce the experimental results, but a priori it would be difficult to know whether the estimator works well for any particular outcome. Pre-program exogeneity tests eliminate some outcomes and estimators with the worst biases, but estimators/outcomes with substantial biases pass the tests. The difference-in-differences matching estimator exhibits the best performance in terms of low bias values and capturing the pattern of statistically significant treatment effects. However, the variation in bias is greater across outcomes examined than across methods.

We investigate the impact of local social pressure on firms’ firing decisions. Using linked employer-employee data, we show that secondary establishments located further away from headquarters have higher dismissal rates than those located closer. The effect of distance on dismissals is stronger, the greater the visibility of the firm in the local community of its headquarters and the larger the degree of selfishness of that community. We show that these findings can be explained by the social pressure exerted by the communities where firms’ headquarters are located, which induces CEOs to refrain from dismissing at short distance from their headquarters.

This paper re-creates three of the samples from LaLonde’s famous 1986 paper that began the literature on “within-study designs” that uses experiments as benchmarks against which to assess the performance of nonexperimental identification strategies. In particular, we recreate the experimental data for the target group of women on welfare from the National Supported Work (NSW) Demonstration and two of the corresponding comparison groups drawn from the Panel Study of Income Dynamics (PSID). The loss of these data resulted in the (sizable) subsequent literature devoting its attention solely to the NSW men. In addition to repeating LaLonde’s analyses on our recreations of his files for the AFDC women, we apply (many of) the estimators from later papers by Dehejia and Wahba and by Smith and Todd to these data. Our findings support the general view in the literature that women on welfare pose a less difficult selection problem when evaluating employment and training programs. They also call into question the generalizability of some of the broad conclusions that Dehejia and Wahba and Smith and Todd draw from their analyses of the NSW men.

Government employment programs for low-skilled workers typically emphasize rapid placement of participants into jobs, of which many are temporary-help jobs. Using data from Detroit’s welfare-to-work program and the Chernozhukov-Hansen instrumental variables quantile regression method, we find that neither direct-hire nor temporary-help job placements significantly affect the lower tail of the earnings distribution. In the upper tail, direct-hire placements yield sizable earnings increases for over half of participants, while temporary-help placements yield significant earnings losses at higher quantiles. Our results cast doubt on the efficacy of employment programs’ exclusive focus on rapid job placement and their widespread reliance on temporary-help placements.

We evaluate the educational returns to General Educational Development (GED) certification using state administrative data. We use fuzzy regression discontinuity (FRD) methods to account for the fact that GED test-takers can repeatedly retake the test until they pass it and the fact that test-takers have to pass all five subtests before receiving the GED. We find that the GED increases the likelihood of postsecondary attendance and course completion substantially but that the GED impact on overall credits completed is modest; the GED causes an average increment of only two credits for men and six credits for women.

This paper investigates the role of mechanical ability as a determinant of schooling decisions and labor market outcomes. Using a Roy model with multiple unobserved abilities and longitudinal data from NLSY79, we find that this ability has a positive effect on overall earnings. However, in contrast to cognitive and socioemotional abilities, mechanical ability reduces the likelihood of 4-year college attendance. The rationale for this asymmetry comes from its large estimated impact on earnings conditional on not attending a 4-year college. Our findings highlight the importance of moving beyond the one-size-fits-all discourse to offer individuals alternative educational pathways to successful careers.

We propose a general framework for determining the extent of measurement error bias in ordinary least squares and instrumental variable (IV) estimators of linear models while allowing for measurement error in the validation source. We apply this method by validating Survey of Health, Ageing and Retirement in Europe data with Danish administrative registers. Contrary to most validation studies, we find that measurement error in income is classical once we account for imperfect validation data. We find nonclassical measurement error in schooling, causing a 38% amplification bias in IV estimators of the returns, with important implications for the program evaluation literature.