Two-stage least squares is biased in the same direction as ordinary least squares even in very large samples. The authors propose a split-sample instrumental variables estimator that is not biased toward ordinary least squares. Split-sample instrumental variables 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. Split-sample instrumental variables is biased toward zero but this bias can be corrected. The authors use split-sample estimators to reexamine instrumental variables and two-stage least squares estimates of the returns to schooling.
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Volume (Year): 13 (1995) Issue (Month): 2 (April) Pages: 225-35 Download reference. The following formats are available: HTML
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