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Tools for Intuition about Sample Selection Bias and Its Correction

Ross M. Stolzenberg and Daniel A. Relles
American Sociological Review
Vol. 62, No. 3 (Jun., 1997), pp. 494-507
Stable URL: http://www.jstor.org/stable/2657318
Page Count: 14
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Tools for Intuition about Sample Selection Bias and Its Correction
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Abstract

We provide mathematical tools to assist intuition about selection bias in concrete empirical analyses. These new tools do not offer a general solution to the selection bias problem; no method now does that. Rather, the techniques we present offer a new decomposition of selection bias. This decomposition permits an analyst to develop intuition and make reasoned judgments about the sources, severity, and direction of sample selection bias in a particular analysis. When combined with simulation results, also presented in this paper, our decomposition of bias also permits a reasoned, empirically-informed judgment of when the well-known two-step estimator of Heckman (1976, 1979) is likely to increase or decrease the accuracy of regression coefficient estimates. We also use simulations to confirm mathematical derivations.

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