We apply Haider and Solon’s generalized errors‐in‐variables model to Swedish income tax data to produce estimates of the association between current and lifetime income. Our estimates demonstrate strong life‐cycle patterns. This implies that the widespread use of current income as a proxy for lifetime income leads to inconsistent parameter estimates (i.e., life‐cycle bias) even when the proxy is used as the dependent variable. Estimates for comparable cohorts of Swedish and American men demonstrate surprising similarities. There are, however, significant gender and cohort differences in this association that lead to statistically significant and quantitatively meaningful differences in life‐cycle biases.

Introduced in 1993, Georgia’s HOPE Program sponsors a merit‐based scholarship for students attending in‐state colleges and a grant for those entering technical schools. There are no income restrictions. Comparing Georgia with other southeastern states over the 1988–97 period, HOPE increased freshmen enrollment by 5.9%, or 2,889 students per year, which amounts to only 15% of freshmen scholarship recipients. Four‐year colleges account for most of the gain; a reduction in students leaving the state explains two‐thirds of the 4‐year‐school effect attributable to freshmen who have recently graduated from high school. White and black enrollments increased because of HOPE.

Using three sources of data, this article examines the direct economic return to General Educational Development (GED) certification for both native and immigrant high school dropouts. One data source—the Current Population Survey (CPS)—is plagued by nonresponse and allocation bias from the hot deck procedure that biases the estimated return to the GED upward. Correcting for allocation bias and ability bias, there is no direct economic return to GED certification. An apparent return to GED certification with age found in the raw CPS data is due to dropouts becoming more skilled over time. These results apply to both native‐born and immigrant populations.

This paper established that a low dimensional vector of cognitive and noncognitive skills explains a variety of labor market and behavioral outcomes. For many dimensions of social performance cognitive and noncognitive skills are equally important. Our analysis addresses the problems of measurement error, imperfect proxies, and reverse causality that plague conventional studies of cognitive and noncognitive skills that regress earnings (and other outcomes) on proxies for skills. Noncognitive skills strongly influence schooling decisions, and also affect wages given schooling decisions. Schooling, employment, work experience and choice of occupation are affected by latent noncognitive and cognitive skills. We study a variety of correlated risky behaviors such as teenage pregnancy and marriage, smoking, marijuana use, and participation in illegal activities. The same low dimensional vector of abilities that explains schooling choices, wages, employment, work experience and choice of occupation explains these behavioral outcomes.

Studies examining welfare‐to‐work program effectiveness present mixed and sometimes discrepant findings, partly due to research design, data, and methodological limitations. Using administrative data on Missouri and North Carolina welfare recipients, we substantially improve on past estimation approaches to identify the distinct effects of each state’s welfare‐to‐work subprograms—assessment, job search assistance and job readiness training, and more intensive programs designed to augment human capital. More intensive training is associated with greater initial earnings losses but also greater long‐run earnings gains. The negative program impacts we observe in quarters immediately following participation turn positive by the second year after participation.