Abstract
Abstract 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. KEY WORDS: Finite-sample biasHuman capital and wagesTwo-stage least squares
Keywords
Instrumental variableEconometricsEconomicsSample (material)MathematicsStatistics
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Publication Info
- Year
- 1995
- Type
- article
- Volume
- 13
- Issue
- 2
- Pages
- 225-235
- Citations
- 385
- Access
- Closed
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Cite This
Joshua D. Angrist,
Alan B. Krueger
(1995).
Split-Sample Instrumental Variables Estimates of the Return to Schooling.
Journal of Business and Economic Statistics
, 13
(2)
, 225-235.
https://doi.org/10.1080/07350015.1995.10524597
Identifiers
- DOI
- 10.1080/07350015.1995.10524597