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Inference via kernel smoothing of bootstrap P values

Author

Listed:
  • Jeff Racine

    () (McMaster University)

  • James G. MacKinnon

    () (Queen's University)

Abstract

Resampling methods such as the bootstrap are routinely used to estimate the finite-sample null distributions of a range of test statistics. We present a simple and tractable way to perform classical hypothesis tests based upon a kernel estimate of the CDF of the bootstrap statistics. This approach has a number of appealing features: i) it can perform well when the number of bootstraps is extremely small, ii) it is approximately exact, and iii) it can yield substantial power gains relative to the conventional approach. The proposed approach is likely to be useful when the statistic being bootstrapped is computationally expensive.

Suggested Citation

  • Jeff Racine & James G. MacKinnon, 2006. "Inference via kernel smoothing of bootstrap P values," Working Papers 1054, Queen's University, Department of Economics.
  • Handle: RePEc:qed:wpaper:1054
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    File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_1054.pdf
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    References listed on IDEAS

    as
    1. Russell Davidson & James MacKinnon, 2000. "Bootstrap tests: how many bootstraps?," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 55-68.
    2. Racine, Jeff & MacKinnon, James, 2004. "Simulation-based Tests that can Use Any Number of Simulations," Queen's Economics Department Working Papers 273465, Queen's University - Department of Economics.
    3. Davidson, Russell & MacKinnon, James G., 1992. "Regression-based methods for using control variates in Monte Carlo experiments," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 203-222.
    4. Gourieroux, Christian & Monfort, Alain, 1997. "Simulation-based Econometric Methods," OUP Catalogue, Oxford University Press, number 9780198774754.
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    Cited by:

    1. Cabane, Charlotte & Hille, Adrian & Lechner, Michael, 2015. "Mozart or Pelé? The effects of teenagers’ participation in music and sports," CEPR Discussion Papers 10556, C.E.P.R. Discussion Papers.
    2. repec:tpr:restat:v:99:y:2017:i:1:p:180-183 is not listed on IDEAS
    3. Pawlowski, Tim & Schüttoff, Ute & Downward, Paul & Lechner, Michael, 2014. "Sport participation and Child Development in Less Developed Countries," Economics Working Paper Series 1433, University of St. Gallen, School of Economics and Political Science.
    4. Pawlowski, Tim & Schüttoff, Ute & Downward, Paul & Lechner, Michael, 2014. "Children’s skill formation in less developed countries – The impact of sports participation," Economics Working Paper Series 1412, University of St. Gallen, School of Economics and Political Science.
    5. James G. MacKinnon, 2007. "Bootstrap Hypothesis Testing," Working Papers 1127, Queen's University, Department of Economics.
    6. Michael Lechner & Paul Downward, 2017. "Heterogeneous sports participation and labour market outcomes in England," Applied Economics, Taylor & Francis Journals, vol. 49(4), pages 335-348, January.
    7. Martin Huber & Michael Lechner & Giovanni Mellace, 2017. "Why Do Tougher Caseworkers Increase Employment? The Role of Program Assignment as a Causal Mechanism," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 180-183, March.
    8. Bodory, Hugo & Camponovo, Lorenzo & Huber, Martin & Lechner, Michael, 2016. "The Finite Sample Performance of Inference Methods for Propensity Score Matching and Weighting Estimators," IZA Discussion Papers 9706, Institute for the Study of Labor (IZA).
    9. Patrick Richard, 2010. "Kernel smoothing end of sample instability tests P values," Cahiers de recherche 10-19, Departement d'Economique de l'École de gestion à l'Université de Sherbrooke.

    More about this item

    Keywords

    resampling; Monte Carlo test; bootstrap test; percentiles; kernel; smoothing;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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

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