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The robust F-statistic as a test for weak instruments

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  • Windmeijer, Frank

Abstract

For the linear model with a single endogenous variable, (Montiel Olea and Pflueger 2013) proposed the effective F-statistic as a test for weak instruments in terms of the Nagar bias of the two-stage least squares (2SLS) or limited information maximum likelihood (LIML) estimator relative to a benchmark worst-case bias. We show that their methodology for the 2SLS estimator applies to a class of linear generalized method of moments (GMM) estimators with an associated class of generalized effective F-statistics. The standard robust F-statistic is a member of this class. The associated GMMf estimator, with the extension “f” for first-stage, has the weight matrix based on the first-stage residuals. In the grouped-data IV designs of Andrews (2018) with moderate and high levels of endogeneity and where the robust F-statistic is large but the effective F-statistic is small, the GMMf estimator is shown to behave much better in terms of bias than the 2SLS estimator.

Suggested Citation

  • Windmeijer, Frank, 2025. "The robust F-statistic as a test for weak instruments," Journal of Econometrics, Elsevier, vol. 247(C).
  • Handle: RePEc:eee:econom:v:247:y:2025:i:c:s0304407625000053
    DOI: 10.1016/j.jeconom.2025.105951
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    1. Paul A. Bekker & Jan van der Ploeg, 2005. "Instrumental variable estimation based on grouped data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(3), pages 239-267, August.
    2. Keith Finlay & Leandro M. Magnusson, 2009. "Implementing weak-instrument robust tests for a general class of instrumental-variables models," Stata Journal, StataCorp LLC, vol. 9(3), pages 398-421, September.
    3. Melvin Stephens Jr. & Dou-Yan Yang, 2014. "Compulsory Education and the Benefits of Schooling," American Economic Review, American Economic Association, vol. 104(6), pages 1777-1792, June.
    4. Marcelo J. Moreira, 2003. "A Conditional Likelihood Ratio Test for Structural Models," Econometrica, Econometric Society, vol. 71(4), pages 1027-1048, July.
    5. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    6. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    7. José Luis Montiel Olea & Carolin Pflueger, 2013. "A Robust Test for Weak Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 358-369, July.
    8. Carolin E. Pflueger & Su Wang, 2015. "A robust test for weak instruments in Stata," Stata Journal, StataCorp LLC, vol. 15(1), pages 216-225, March.
    9. Frank Windmeijer, 2019. "Two-stage least squares as minimum distance," The Econometrics Journal, Royal Economic Society, vol. 22(1), pages 1-9.
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    More about this item

    Keywords

    Instrumental variables; Weak instruments; Heteroskedasticity; Robust F-statistic; GMM;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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