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Finite sample evidence of IV estimators under weak instruments

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  • Alfonso Flores-Lagunes

    (Department of Economics, Eller College of Management, University of Arizona, Tucson, AZ, USA)

Abstract

We present finite sample evidence on different IV estimators available for linear models under weak instruments; explore the application of the bootstrap as a bias reduction technique to attenuate their finite sample bias; and employ three empirical applications to illustrate and provide insights into the relative performance of the estimators in practice. Our evidence indicates that the random-effects quasi-maximum likelihood estimator outperforms alternative estimators in terms of median point estimates and coverage rates, followed by the bootstrap bias-corrected version of LIML and LIML. However, our results also confirm the difficulty of obtaining reliable point estimates in models with weak identification and moderate-size samples. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Alfonso Flores-Lagunes, 2007. "Finite sample evidence of IV estimators under weak instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 677-694.
  • Handle: RePEc:jae:japmet:v:22:y:2007:i:3:p:677-694
    DOI: 10.1002/jae.916
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    File URL: http://qed.econ.queensu.ca:80/jae/2007-v22.3/
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    References listed on IDEAS

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