Conditioning on the Probability of Selection to Control Selection Bias

Joshua Angrist

No 181, NBER Technical Working Papers from National Bureau of Economic Research, Inc

Abstract: Problems of sample selection arise in the analysis of both experimental and non-experimental data. In clinical trials to evaluate the impact of an intervention on health and mortality, treatment assignment is typically nonrandom in a sample of survivors even if the original assignment is random. Similarly, randomized training interventions like National Supported Work (NSW) are not necessarily randomly assigned in the sample of working men. A non- experimental version of this problem involves the use of instrumental variables (IV) to estimate behavioral relationships. A sample selection rule that is related to the instruments can induce correlation between the instruments and unobserved outcomes, possibly invalidating the use of conventional IV techniques in the selected sample. This paper shows that conditioning on the probability of selection given the instruments can provide a solution to the selection problem as long as the relationship between instruments and selection status satisfies a simple monotonicity condition. A latent index structure is not required for this result, which is motivated as an extension of earlier work on the propensity score. The conditioning approach to selection problems is illustrated using instrumental variables techniques to estimate the returns to schooling in a sample with positive earnings.

JEL-codes: C24 J31 (search for similar items in EconPapers)
Date: 1995-06
New Economics Papers: this item is included in nep-dcm
Note: LS
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Citations: View citations in EconPapers (27)

Published as "Conditional independence in sample selection models" Economics Letters, Volume 54, Issue 2, February 1997, Pages 103-112

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