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Fast Double Bootstrap Tests Of Nonnested Linear Regression Models

Author

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  • Russell Davidson
  • James MacKinnon

Abstract

It has been shown in previous work that bootstrapping the J test for nonnested linear regression models dramatically improves its finite-sample performance. We provide evidence that a more sophisticated bootstrap procedure, which we call the fast double bootstrap, produces a very substantial further improvement in cases where the ordinary bootstrap does not work as well as it might. This FDB procedure is only about twice as expensive as the usual single bootstrap.

Suggested Citation

  • Russell Davidson & James MacKinnon, 2002. "Fast Double Bootstrap Tests Of Nonnested Linear Regression Models," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 419-429.
  • Handle: RePEc:taf:emetrv:v:21:y:2002:i:4:p:419-429
    DOI: 10.1081/ETC-120015384
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    References listed on IDEAS

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    1. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-793, May.
    2. Russell Davidson & James MacKinnon, 2000. "Bootstrap tests: how many bootstraps?," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 55-68.
    3. McAleer, Michael, 1995. "The significance of testing empirical non-nested models," Journal of Econometrics, Elsevier, vol. 67(1), pages 149-171, May.
    4. Davidson, Russell & MacKinnon, James G., 1999. "The Size Distortion Of Bootstrap Tests," Econometric Theory, Cambridge University Press, vol. 15(03), pages 361-376, June.
    5. Yanqin Fan & Qi Li, 1995. "Bootstrapping J-type tests for non-nested regression models," Economics Letters, Elsevier, vol. 48(2), pages 107-112, May.
    6. Davidson, Russell & MacKinnon, James G., 2002. "Bootstrap J tests of nonnested linear regression models," Journal of Econometrics, Elsevier, vol. 109(1), pages 167-193, July.
    7. Godfrey, L. G., 1998. "Tests of non-nested regression models some results on small sample behaviour and the bootstrap," Journal of Econometrics, Elsevier, vol. 84(1), pages 59-74, May.
    8. MacKinnon, James & Davidson, Russel, 2000. "Improving the Reliability of Bootstrap Tests," Queen's Economics Department Working Papers 273421, Queen's University - Department of Economics.
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    Citations

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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. Bernard Fingleton & Simonetta Longhi, 2013. "The Effects Of Agglomeration On Wages: Evidence From The Micro-Level," Journal of Regional Science, Wiley Blackwell, vol. 53(3), pages 443-463, August.
    3. Qian, Hang, 2012. "Essays on statistical inference with imperfectly observed data," ISU General Staff Papers 201201010800003618, Iowa State University, Department of Economics.
    4. Davidson, Russell & MacKinnon, James G., 2007. "Improving the reliability of bootstrap tests with the fast double bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3259-3281, April.
    5. Yazid Dissou & Reza Ghazal, 2010. "Energy Substitutability in Canadian Manufacturing Econometric Estimation with Bootstrap Confidence Intervals," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 121-148.
    6. Patrick Richard, 2014. "Bootstrap tests in linear models with many regressors," Cahiers de recherche 14-06, Departement d'Economique de l'École de gestion à l'Université de Sherbrooke.
    7. James G. MacKinnon, 1983. "Model Specification Tests Against Non-Nested Alternatives," Working Papers 573, Queen's University, Department of Economics.
    8. Sun, Yixiao & Kim, Min Seong, 2009. "k-step Bootstrap Bias Correction for Fixed Effects Estimators in Nonlinear Panel Models," University of California at San Diego, Economics Working Paper Series qt9gn6n5mr, Department of Economics, UC San Diego.
    9. Seojeong Lee, 2018. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Empirical Likelihood Estimators," Papers 1806.00953, arXiv.org, revised Jun 2018.
    10. Qian, Hang, 2011. "Sampling Variation, Monotone Instrumental Variables and the Bootstrap Bias Correction," MPRA Paper 32634, University Library of Munich, Germany.
    11. James G. MacKinnon, 2006. "Applications of the Fast Double Bootstrap," Working Papers 1023, Queen's University, Department of Economics.
    12. Bernard FINGLETON & Silvia PALOMBI, 2013. "The Wage Curve Reconsidered: Is It Truly An 'Empirical Law Of Economics'?," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 38, pages 49-92.
    13. Lenard Lieb & Stephan Smeekes, 2017. "Inference for Impulse Responses under Model Uncertainty," Papers 1709.09583, arXiv.org, revised May 2018.
    14. MacKinnon, James, 2007. "Bootstrap Hypothesis Testing," Queen's Economics Department Working Papers 273603, Queen's University - Department of Economics.
    15. Han, Xiaoyi & Lee, Lung-fei, 2013. "Model selection using J-test for the spatial autoregressive model vs. the matrix exponential spatial model," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 250-271.
    16. Burridge, Peter & Robert Taylor, A. M., 2004. "Bootstrapping the HEGY seasonal unit root tests," Journal of Econometrics, Elsevier, vol. 123(1), pages 67-87, November.

    More about this item

    Keywords

    Nonnested test; Bootstrap test; J test; JEL Classification: C12; C15; C20;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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