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Bootstrap Hypothesis Testing

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  • MacKinnon, James

Abstract

This paper surveys bootstrap and Monte Carlo methods for testing hypotheses in econometrics. Several different ways of computing bootstrap P values are discussed, including the double bootstrap and the fast double bootstrap. It is emphasized that there are many different procedures for generating bootstrap samples for regression models and other types of model. As an illustration, a simulation experiment examines the performance of several methods of bootstrapping the supF test for structural change with an unknown break point.

Suggested Citation

  • MacKinnon, James, 2007. "Bootstrap Hypothesis Testing," Queen's Economics Department Working Papers 273603, Queen's University - Department of Economics.
    • Handle: RePEc:ags:quedwp:273603
    DOI: 10.22004/ag.econ.273603
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    Cited by:

    1. Alessandro Riboni & Francisco Ruge‐Murcia, 2023. "The Power Of The Federal Reserve Chair," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(2), pages 727-756, May.
    2. is not listed on IDEAS
    3. Johan Blomquist & Joakim Westerlund, 2016. "Panel bootstrap tests of slope homogeneity," Empirical Economics, Springer, vol. 50(4), pages 1359-1381, June.
    4. Gelman, Sergey & Wilfling, Bernd, 2009. "Markov-switching in target stocks during takeover bids," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 745-758, December.
    5. Christopher J. Bennett, 2009. "p-Value Adjustments for Asymptotic Control of the Generalized Familywise Error Rate," Vanderbilt University Department of Economics Working Papers 0905, Vanderbilt University Department of Economics.
    6. A. Yasemin Yalta, 2011. "New Evidence on FDI-Led Growth: The Case of China," Working Papers 1107, TOBB University of Economics and Technology, Department of Economics.
    7. Todd Prono, 2009. "Market proxies, correlation, and relative mean-variance efficiency: still living with the roll critique," Supervisory Research and Analysis Working Papers QAU09-3, Federal Reserve Bank of Boston.
    8. Martin Huber & Giovanni Mellace, 2015. "Testing Instrument Validity for LATE Identification Based on Inequality Moment Constraints," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 398-411, May.
    9. Stephanie Thomas, 2016. "A Standardized Method for the Evaluation of Adherence to Practice Guidelines," Department of Economics Working Papers 2016-14, McMaster University.
    10. Yalta, A. Talha, 2011. "Analyzing energy consumption and GDP nexus using maximum entropy bootstrap: The case of Turkey," Energy Economics, Elsevier, vol. 33(3), pages 453-460, May.
    11. Del Hoyo, Juan & Llorente, Guillermo & Rivero, Carlos, 2011. "Consumo de electricidad y producto interior bruto: Relación dinámica y estabilidad/Electricity Consumption and GDP: Dynamic Relationship and Stability," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 29, pages 473-492, Agosto.
    12. Janusz L. Wywiał, 2018. "Application of Two Gamma Distributions Mixture to Financial Auditing," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 1-18, May.
    13. Eva Boj & Teresa Costa & Josep Fortiana & Anna Esteve, 2015. "Assessing the Importance of Risk Factors in Distance-Based Generalized Linear Models," Methodology and Computing in Applied Probability, Springer, vol. 17(4), pages 951-962, December.
    14. Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2010. "Hypothesis Testing in Econometrics," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 75-104, September.
    15. Christopher J. Bennett, 2009. "Consistent and Asymptotically Unbiased MinP Tests of Multiple Inequality Moment Restrictions," Vanderbilt University Department of Economics Working Papers 0908, Vanderbilt University Department of Economics.
    16. Zsurkis, Gabriel & Nicolau, João & Rodrigues, Paulo M. M, 2021. "The expected time to cross a threshold and its determinants: a simple and flexible framework," Journal of Economic Dynamics and Control, Elsevier, vol. 122(C).
    17. Rakovská, Zuzana, 2021. "Composite survey sentiment as a predictor of future market returns: Evidence for German equity indices," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 473-495.

    More about this item

    Keywords

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    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

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