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Bootstrap validity for the score test when instruments may be weak

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  • Moreira, Marcelo J.
  • Porter, Jack R.
  • Suarez, Gustavo A.

Abstract

It is well-known that size adjustments based on bootstrapping the t-statistic perform poorly when instruments are weakly correlated with the endogenous explanatory variable. In this paper, we provide a theoretical proof that guarantees the validity of the bootstrap for the score statistic. This theory does not follow from standard results, since the score statistic is not a smooth function of sample means and some parameters are not consistently estimable when the instruments are uncorrelated with the explanatory variable.

Suggested Citation

  • Moreira, Marcelo J. & Porter, Jack R. & Suarez, Gustavo A., 2009. "Bootstrap validity for the score test when instruments may be weak," Journal of Econometrics, Elsevier, vol. 149(1), pages 52-64, April.
    • Handle: RePEc:eee:econom:v:149:y:2009:i:1:p:52-64
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    References listed on IDEAS

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    1. Marcelo J. Moreira & Jack R. Porter & Gustavo A. Suarez, 2004. "Bootstrap and Higher-Order Expansion Validity When Instruments May Be Weak," Harvard Institute of Economic Research Working Papers 2048, Harvard - Institute of Economic Research.
    2. Otsu, Taisuke, 2006. "Generalized Empirical Likelihood Inference For Nonlinear And Time Series Models Under Weak Identification," Econometric Theory, Cambridge University Press, vol. 22(3), pages 513-527, June.
    3. Atsushi Inoue, 2006. "A bootstrap approach to moment selection," Econometrics Journal, Royal Economic Society, vol. 9(1), pages 48-75, March.
    4. Guggenberger, Patrik & Smith, Richard J., 2005. "Generalized Empirical Likelihood Estimators And Tests Under Partial, Weak, And Strong Identification," Econometric Theory, Cambridge University Press, vol. 21(4), pages 667-709, August.
    5. Donald W. K. Andrews, 2000. "Inconsistency of the Bootstrap when a Parameter Is on the Boundary of the Parameter Space," Econometrica, Econometric Society, vol. 68(2), pages 399-406, March.
    6. Nelson, Charles R & Startz, Richard, 1990. "Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator," Econometrica, Econometric Society, vol. 58(4), pages 967-976, July.
    7. Qumsiyeh, Maher B., 1990. "Edgeworth expansion in regression models," Journal of Multivariate Analysis, Elsevier, vol. 35(1), pages 86-101, October.
    8. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
    9. Rothenberg, Thomas J, 1988. "Approximate Power Functions for Some Robust Tests of Regression Coefficients," Econometrica, Econometric Society, vol. 56(5), pages 997-1019, September.
    10. Andrews, Donald W K, 1987. "Consistency in Nonlinear Econometric Models: A Generic Uniform Law of Large Numbers [On Unification of the Asymptotic Theory of Nonlinear Econometric Models]," Econometrica, Econometric Society, vol. 55(6), pages 1465-1471, November.
    11. Jiahui Wang & Eric Zivot, 1998. "Inference on Structural Parameters in Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 66(6), pages 1389-1404, November.
    12. Marcelo J. Moreira, 2003. "A Conditional Likelihood Ratio Test for Structural Models," Econometrica, Econometric Society, vol. 71(4), pages 1027-1048, July.
    13. Horowitz, Joel L., 2001. "The Bootstrap," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.),Handbook of Econometrics, edition 1, volume 5, chapter 52, pages 3159-3228, Elsevier.
    14. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    15. Frank Kleibergen, 2002. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Econometrica, Econometric Society, vol. 70(5), pages 1781-1803, September.
    16. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
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    Citations

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    Cited by:

    1. Andrews, Donald W.K. & Guggenberger, Patrik, 2010. "Applications of subsampling, hybrid, and size-correction methods," Journal of Econometrics, Elsevier, vol. 158(2), pages 285-305, October.
    2. Guggenberger, Patrik & Smith, Richard J., 2008. "Generalized empirical likelihood tests in time series models with potential identification failure," Journal of Econometrics, Elsevier, vol. 142(1), pages 134-161, January.
    3. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    4. Noud P.A. van Giersbergen, 2011. "Bootstrapping Subset Test Statistics in IV Regression," UvA-Econometrics Working Papers 11-08, Universiteit van Amsterdam, Dept. of Econometrics.
    5. Firmin Doko Tchatoka, 2015. "On bootstrap validity for specification tests with weak instruments," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 137-146, February.
    6. Guggenberger, Patrik & Ramalho, Joaquim J.S. & Smith, Richard J., 2012. "GEL statistics under weak identification," Journal of Econometrics, Elsevier, vol. 170(2), pages 331-349.
    7. Wenjie Wang, 2012. "Bootstrapping Anderson-Rubin Statistic and J Statistic in Linear IV Models with Many Instruments," KIER Working Papers 810, Kyoto University, Institute of Economic Research.
    8. Doko Tchatoka, Firmin & Wang, Wenjie, 2020. "Uniform Inference after Pretesting for Exogeneity," MPRA Paper 99243, University Library of Munich, Germany.
    9. Wang, Wenjie, 2020. "On the Inconsistency of Nonparametric Bootstraps for the Subvector Anderson-Rubin Test," MPRA Paper 99109, University Library of Munich, Germany.
    10. Wang, Wenjie & Doko Tchatoka, Firmin, 2018. "On Bootstrap inconsistency and Bonferroni-based size-correction for the subset Anderson–Rubin test under conditional homoskedasticity," Journal of Econometrics, Elsevier, vol. 207(1), pages 188-211.
    11. Wang, Wenjie, 2020. "On the inconsistency of nonparametric bootstraps for the subvector Anderson–Rubin test," Economics Letters, Elsevier, vol. 191(C).
    12. Firmin Doko Tchatoka & Wenjie Wang, 2015. "On Bootstrap Validity for Subset Anderson-Rubin Test in IV Regressions," School of Economics Working Papers 2015-01, University of Adelaide, School of Economics.
    13. Russell Davidson & James G. MacKinnon, 2014. "Bootstrap Confidence Sets with Weak Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 651-675, August.
    14. Rachida Ouysse, 2014. "On the performance of block-bootstrap continuously updated GMM for a class of non-linear conditional moment models," Computational Statistics, Springer, vol. 29(1), pages 233-261, February.
    15. Keith Finlay & Leandro M. Magnusson, 2014. "Bootstrap Methods for Inference with Cluster-Sample IV Models," Economics Discussion / Working Papers 14-12, The University of Western Australia, Department of Economics.

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