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Split-Sample Instrumental Variables Estimates of the Return to Schooling
Joshua D. Angrist and Alan B. Krueger
Journal of Business & Economic Statistics
Vol. 13, No. 2, JBES Symposium on Program and Policy Evaluation (Apr., 1995), pp. 225-235
Stable URL: http://www.jstor.org/stable/1392377
Page Count: 11
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This article reevaluates recent instrumental variables (IV) estimates of the returns to schooling in light of the fact that two-stage least squares is biased in the same direction as ordinary least squares (OLS) even in very large samples. We propose a split-sample instrumental variables (SSIV) estimator that is not biased toward OLS. SSIV uses one-half of a sample to estimate parameters of the first-stage equation. Estimated first-stage parameters are then used to construct fitted values and second-stage parameter estimates in the other half sample. SSIV is biased toward 0, but this bias can be corrected. The splt-sample estimators confirm and reinforce some previous findings on the returns to schooling but fail to confirm others.
Journal of Business & Economic Statistics © 1995 American Statistical Association