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Small-sample bias in synthetic cohort models of labor supply

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  • Paul J. Devereux

    (School of Economics and Geary Institute, University College Dublin, Ireland)

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.

Suggested Citation

  • Paul J. Devereux, 2007. "Small-sample bias in synthetic cohort models of labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 839-848.
  • Handle: RePEc:jae:japmet:v:22:y:2007:i:4:p:839-848
    DOI: 10.1002/jae.938
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