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Title: Split Sample Instrumental Variables
Authors: Krueger, Alan B.
Angrist, Joshua
Keywords: instrumental variables
split sample instrumental variables
compulsory schooling
Issue Date: 1-Oct-1993
Citation: Journal of Business and Economic Statistics, Vol. 13, No. 2, April, 1995
Series/Report no.: Working Papers (Princeton University. Industrial Relations Section) ; 320
Abstract: Instrumental Variables (IV) estimates tend to be biased in the same direction as Ordinary Least Squares (OLS) in finite samples if the instruments are weak. To address this problem we propose a new IV estimator which we call Split Sample Instrumental Variables (SSIV). SSIV works as follows: we randomly split the sample in half, and use one half of the sample to estimate parameters of the first-stage equation. We then use these estimated first-stage parameters to construct fitted values and second-stage parameter estimates using data from the other half sample. SSIV is biased toward zero, rather than toward the plim of the OLS estimate. However, an unbiased estimate of the attenuation bias of SSIV can be calculated. We use this estimate of the attenuation bias to derive an estimator that is asymptotically unbiased as the number of instruments tends to infinity, holding the number of observations per instrument fixed. We label this new estimator Unbiased Split Sample Instrumental Variables (USSIV). We apply SSIV and USSIV to the data used by Angrist and Krueger (1991) to estimate the payoff to education.
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