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Randomization Tests in Econometrics

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  • Kennedy, Peter E

Abstract

Numerous shuffling of data produce a distribution of test statistic values that can be used to assess the degree to which the test statistic value produced by the actual data is unusual. Because this controversial randomization testing methodology, made practical by the computer revolution, has begun to appear in applied econometric studies, econometricians should become familiar with its mechanics, rationale, and interpretation, all of which are quite different from the status quo. This paper exposits randomization tests in an econometric context, discusses their advantages, and alerts practitioners to pitfalls.

Suggested Citation

  • Kennedy, Peter E, 1995. "Randomization Tests in Econometrics," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 85-94, January.
    • Handle: RePEc:bes:jnlbes:v:13:y:1995:i:1:p:85-94
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    Cited by:

    1. Adam M. Kleinbaum, 2018. "Reorganization and Tie Decay Choices," Management Science, INFORMS, vol. 64(5), pages 2219-2237, May.
    2. Kopczuk, Wojciech & Pop-Eleches, Cristian, 2007. "Electronic filing, tax preparers and participation in the Earned Income Tax Credit," Journal of Public Economics, Elsevier, vol. 91(7-8), pages 1351-1367, August.
    3. Florian Buhlmann & Benjamin Elsner & Andreas Peichl, 2018. "Tax refunds and income manipulation: evidence from the EITC," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 25(6), pages 1490-1518, December.
    4. Donohue III, John J. & Wolfers, Justin, 2006. "Uses and Abuses of Empirical Evidence in the Death Penalty Debate," IZA Discussion Papers 1949, Institute of Labor Economics (IZA).
    5. Luger, Richard, 2006. "Exact permutation tests for non-nested non-linear regression models," Journal of Econometrics, Elsevier, vol. 133(2), pages 513-529, August.
    6. Rui Albuquerque & Luis Brandão-Marques & Miguel A Ferreira & Pedro Matos, 2019. "International Corporate Governance Spillovers: Evidence from Cross-Border Mergers and Acquisitions," Review of Financial Studies, Society for Financial Studies, vol. 32(2), pages 738-770.
    7. Taylor, Benjamin & Li, Jing, 2015. "Do fewer guns lead to less crime? Evidence from Australia," International Review of Law and Economics, Elsevier, vol. 42(C), pages 72-78.
    8. Sooncheol Sohn & Byoung Jung & Myoungshic Jhun, 2012. "Permutation tests using least distance estimator in the multivariate regression model," Computational Statistics, Springer, vol. 27(2), pages 191-201, June.
    9. Stefano Bonnini & Michela Borghesi, 2022. "Relationship between Mental Health and Socio-Economic, Demographic and Environmental Factors in the COVID-19 Lockdown Period—A Multivariate Regression Analysis," Mathematics, MDPI, vol. 10(18), pages 1-15, September.
    10. Harsha Konara Mudiyanselage & Shawn Xiaoguang Chen, 2022. "What impairs the ‘money machine’ of VAT in developing countries?," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 29(5), pages 1128-1159, October.
    11. Mittelhammer, Ron C. & Judge, George G., 2005. "Combining estimators to improve structural model estimation and inference under quadratic loss," Journal of Econometrics, Elsevier, vol. 128(1), pages 1-29, September.
    12. Ronit Nirel & Malka Gorfine, 2003. "Nonparametric Analysis of Longitudinal Binary Data: An Application to the Intergroup Prisoner's Dilemma Game," Experimental Economics, Springer;Economic Science Association, vol. 6(3), pages 327-341, November.
    13. Zhao, Anqi & Ding, Peng, 2021. "Covariate-adjusted Fisher randomization tests for the average treatment effect," Journal of Econometrics, Elsevier, vol. 225(2), pages 278-294.
    14. Christopher W. Anderson & Eli Beracha, 2008. "Robustness Of The Headquarters‐City Effect On Stock Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 31(3), pages 271-300, September.
    15. Ker, Alan P. & McGowan, Pat, 2000. "Weather-Based Adverse Selection And The U.S. Crop Insurance Program: The Private Insurance Company Perspective," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-25, December.
    16. Leonhard Schilbach & Veronika I Müller & Felix Hoffstaedter & Mareike Clos & Roberto Goya-Maldonado & Oliver Gruber & Simon B Eickhoff, 2014. "Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-9, April.
    17. Charles A. Holt & Sean P. Sullivan, 2023. "Permutation tests for experimental data," Experimental Economics, Springer;Economic Science Association, vol. 26(4), pages 775-812, September.
    18. Achim Zeileis & Torsten Hothorn, 2013. "A toolbox of permutation tests for structural change," Statistical Papers, Springer, vol. 54(4), pages 931-954, November.
    19. Harden Jeffrey J., 2012. "Improving Statistical Inference with Clustered Data," Statistics, Politics and Policy, De Gruyter, vol. 3(1), pages 1-30, January.
    20. Jeong-Joon Lee, 2005. "Persistent wage differential and its implications on the Balassa-Samuelson hypothesis," Applied Economics Letters, Taylor & Francis Journals, vol. 12(10), pages 643-648.
    21. Robert Moir, 1998. "A Monte Carlo Analysis of the Fisher Randomization Technique: Reviving Randomization for Experimental Economists," Experimental Economics, Springer;Economic Science Association, vol. 1(1), pages 87-100, June.
    22. Byoung Jung & Myoungshic Jhun & Seuck Song, 2007. "A new random permutation test in ANOVA models," Statistical Papers, Springer, vol. 48(1), pages 47-62, January.

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