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A solution to the weak instrument bias in 2SLS estimation: Indirect inference with stochastic approximation

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  • Arel-Bundock, Vincent

Abstract

This paper frames indirect inference bias correction as a stochastic root-finding problem and proposes a computationally efficient method to solve it. The technique is applied to the many/weak instrument bias in two-stage least squares estimation. Monte Carlo experiments suggest that the bias-corrected estimator outperforms more common alternatives.

Suggested Citation

  • Arel-Bundock, Vincent, 2013. "A solution to the weak instrument bias in 2SLS estimation: Indirect inference with stochastic approximation," Economics Letters, Elsevier, vol. 120(3), pages 495-498.
    • Handle: RePEc:eee:ecolet:v:120:y:2013:i:3:p:495-498
    DOI: 10.1016/j.econlet.2013.06.004
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    References listed on IDEAS

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    Cited by:

    1. Chau, Tak Wai, 2014. "On the equivalence of indirect inference and bootstrap bias correction for linear IV estimators," Economics Letters, Elsevier, vol. 123(3), pages 333-335.
    2. Nam-Hyun Kim & Winfried Pohlmeier, 2015. "A Regularization Approach to Biased Two-Stage Least Squares Estimation," Working Paper series 15-22, Rimini Centre for Economic Analysis.
    3. Namhyun Kim & Winfried Pohlmeier, 2016. "A Note on the Regularized Approach to Biased 2SLS Estimation with Weak Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(6), pages 915-924, December.

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