Small-sample bias in synthetic cohort models of labor supply

Paul Devereux

Journal of Applied Econometrics, 2007, vol. 22, issue 4, 839-848

Abstract: This paper investigates small-sample biases in synthetic cohort models (repeated cross-sectional data grouped at the cohort and year level) in the context of a female labor supply model. I use the Current Population Survey to compare estimates when group sizes are extremely large to those that arise from randomly drawing subsamples of observations from the large groups. I augment this approach with Monte Carlo analysis so as to precisely quantify biases and coverage rates. In this particular application, thousands of observations per group are required before small-sample issues can be ignored in estimation and sampling error leads to large downward biases in the estimated income elasticity. Copyright © 2007 John Wiley & Sons, Ltd.

Date: 2007
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Working Paper: Small sample bias in synthetic cohort models of labor supply (2006)
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DOI: 10.1002/jae.938

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