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Bootstrap-based Selection for Instrumental Variables Model

Author

Listed:
  • Wenjie Wang

    (Kyoto University)

  • Qingfeng Liu

    (Otaru University of Commerce)

Abstract

This paper develops bootstrap-based method for addressing the “many instruments†problem in the context of instrumental variable estimation. We propose a plug-in restricted-efficient-residual-based (plug-in RE) bootstrap for choosing optimal number of instruments used for two-stage least squares (TSLS) and limited information maximum likelihood (LIML) estimator. In Monte Carlo experiments, we find that the instrument choice based on our plug-in RE bootstrap generally yields an improvement in finite sample performance.

Suggested Citation

  • Wenjie Wang & Qingfeng Liu, 2015. "Bootstrap-based Selection for Instrumental Variables Model," Economics Bulletin, AccessEcon, vol. 35(3), pages 1886-1896.
    • Handle: RePEc:ebl:ecbull:eb-15-00384
    as

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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Instrument selection; Many instruments; Bootstrap; TSLS; LIML;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

    Statistics

    Access and download statistics

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