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Bias‐Corrected Estimates of GED Returns

Journal of Labor Economics 2006 24(3), 661-700
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.

The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior

Journal of Labor Economics 2006 24(3), 411-482 open access
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.

Understanding Instrumental Variables in Models with Essential Heterogeneity

The Review of Economics and Statistics 2006 88(3), 389-432
This paper examines the properties of instrumental variables (IV) applied to models with essential heterogeneity, that is, models where responses to interventions are heterogeneous and agents adopt treatments (participate in programs) with at least partial knowledge of their idiosyncratic response. We analyze two-outcome and multiple-outcome models, including ordered and unordered choice models. We allow for transition-specific and general instruments. We generalize previous analyses by developing weights for treatment effects for general instruments. We develop a simple test for the presence of essential heterogeneity. We note the asymmetry of the model of essential heterogeneity: outcomes of choices are heterogeneous in a general way; choices are not. When both choices and outcomes are permitted to be symmetrically heterogeneous, the method of IV breaks down for estimating treatment parameters.