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Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Method of Moments Estimators

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  • Seojeong Lee

Abstract

I propose a nonparametric iid bootstrap that achieves asymptotic refinements for t tests and confidence intervals based on GMM estimators even when the model is misspecified. In addition, my bootstrap does not require recentering the moment function, which has been considered as critical for GMM. Regardless of model misspecification, the proposed bootstrap achieves the same sharp magnitude of refinements as the conventional bootstrap methods which establish asymptotic refinements by recentering in the absence of misspecification. The key idea is to link the misspecified bootstrap moment condition to the large sample theory of GMM under misspecification of Hall and Inoue (2003). Two examples are provided: Combining data sets and invalid instrumental variables.

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  • Seojeong Lee, 2018. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Method of Moments Estimators," Papers 1806.01450, arXiv.org.
  • Handle: RePEc:arx:papers:1806.01450
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    Cited by:

    1. Lee, Seojeong, 2016. "Asymptotic refinements of a misspecification-robust bootstrap for GEL estimators," Journal of Econometrics, Elsevier, vol. 192(1), pages 86-104.
    2. Hwang, Jungbin & Kang, Byunghoon & Lee, Seojeong, 2022. "A doubly corrected robust variance estimator for linear GMM," Journal of Econometrics, Elsevier, vol. 229(2), pages 276-298.
    3. Hansen, Bruce E. & Lee, Seojeong, 2019. "Asymptotic theory for clustered samples," Journal of Econometrics, Elsevier, vol. 210(2), pages 268-290.
    4. Seojeong Lee, 2018. "A Consistent Variance Estimator for 2SLS When Instruments Identify Different LATEs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(3), pages 400-410, July.
    5. Bruce E. Hansen & Seojeong Lee, 2021. "Inference for Iterated GMM Under Misspecification," Econometrica, Econometric Society, vol. 89(3), pages 1419-1447, May.
    6. Seojeong Lee, 2018. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Empirical Likelihood Estimators," Papers 1806.00953, arXiv.org, revised Jun 2018.
    7. Dovonon, Prosper & Gonçalves, Sílvia, 2017. "Bootstrapping the GMM overidentification test under first-order underidentification," Journal of Econometrics, Elsevier, vol. 201(1), pages 43-71.
    8. A. Felipe & N. Martín & P. Miranda & L. Pardo, 2018. "Testing with Exponentially Tilted Empirical Likelihood," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1319-1358, December.
    9. Mihai Giurcanu & Brett Presnell, 2018. "Bootstrap inference for misspecified moment condition models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(3), pages 605-630, June.
    10. Jungbin Hwang & Gonzalo Valdés, 2020. "Finite-sample Corrected Inference for Two-step GMM in Time Series," Working papers 2020-02, University of Connecticut, Department of Economics.
    11. Hwang, Jungbin & Valdés, Gonzalo, 2023. "Finite-sample corrected inference for two-step GMM in time series," Journal of Econometrics, Elsevier, vol. 234(1), pages 327-352.

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    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
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