This paper presents economic models of child development that capture the essence of recent findings from the empirical literature on skill formation. The goal of this essay is to provide a theoretical framework for interpreting the evidence from a vast empirical literature, for guiding the next...

This paper uses the marginal treatment effect (MTE) to unify the nonparametric literature on treatment effects with the econometric literature on structural estimation using a nonparametric analog of a policy invariant parameter; to generate a variety of treatment effects from a common...

This paper uses the marginal treatment effect (MTE) to unify the nonparametric literature on treatment effects with the econometric literature on structural estimation using a nonparametric analog of a policy invariant parameter; to generate a variety of treatment effects from a common...

This paper argues that skill formation is a life-cycle process and develops the implications of this insight for Scottish social policy. Families are major producers of skills, and a successful policy needs to promote effective families and to supplement failing ones. We present evidence that...

This paper develops and applies a method for decomposing cross section variability of earnings into components that are forecastable at the time students decide to go to college (heterogeneity) and components that are unforecastable. About 60% of variability in returns to schooling is...

This paper examines minority-white wage gaps. Neal and Johnson (1996) show that controlling for ability measured in the teenage years eliminates young adult wage gaps for all groups except for black males, for whom they eliminate 70% of the gap. Their study has been faulted because minority...

This paper considers the identification and estimation of hedonic models. We establish that in an additive version of the hedonic model, technology and preferences are generically identified up to affine transformations from data on demand and supply in a single hedonic market. For a very...