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Sample Selection Bias as a Specification Error
Sample selection bias as a specification error This paper discusses the bias that results from using non-randomly selected samples to estimate behavioral relationships as an ordinary specification error or «omitted variables» bias. A simple consistent two stage estimator is considered that enables analysts to utilize simple regression methods to estimate behavioral functions by least squares methods. The asymptotic distribution of the estimator is derived.
The Causal Effects of Youth Cigarette Addiction and Education
The Importance of Noncognitive Skills: Lessons from the GED Testing Program
The Importance of Noncognitive Skills: Lessons from the GED Testing Program by James J. Heckman and Yona Rubinstein. Published in volume 91, issue 2, pages 145-149 of American Economic Review, May 2001
The Empirical Content of the Roy Model
This paper explores the robustness of the essential economic conclusions of the Roy model of self-selection and income inequality to relaxation of its normality assumptions. A log concave version of the model reproduces most of the main results. Log convex cases offer counterexamples. The authors show that in a Roy economy, random assignment is inegalitarian and Pareto inefficient. They consider nonparametric identifiability of latent skill distributions with cross-section and panel data. The authors' analysis proves nonparametric identifiability for the closely related competing risks model.
The X^2 Goodness of Fit Test for Models with Parameters Estimated from Microdata
Shadow Prices, Market Wages, and Labor Supply
Causal Parameters and Policy Analysis in Economics: A Twentieth Century Retrospective*
The major contributions of twentieth century econometrics to knowledge were the definition of causal parameters within well-defined economic models in which agents are constrained by resources and markets and causes are interrelated, the analysis of what is required to recover causal parameters from data (the identification problem), and clarification of the role of causal parameters in policy evaluation and in forecasting the effects of policies never previously experienced. This paper summarizes the development ofthese ideas by the Cowles Commission, the response to their work by structural econometricians and VAR econometricians, and the response to structural and VAR econometrics by calibrators, advocates of natural and social experiments, and by nonparametric econometricians and statisticians.