Conditional Independance in Sample Selection Models

Joshua Angrist

Working papers from Massachusetts Institute of Technology (MIT), Department of Economics

Abstract: In this note, I describe the conditional independence properties that make it possible to use the selection propensity score to control selection bias in a general sample selection model. The resulting characterization does not rely on a latent index selection mechanism and imposes no structure other than an assumption of independance between the regression error term and the regressors in random samples. This approach leads to a simple rule that can be used to determine if conditioning on the selection propensity score is sufficient to control selection bias.

Keywords: ECONOMETRIC; MODELS (search for similar items in EconPapers)
JEL-codes: C5 C52 (search for similar items in EconPapers)
Pages: 14 pages
Date: 1996
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Journal Article: Conditional independence in sample selection models (1997)
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