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A Monte Carlo Analysis of the Fisher Randomization Technique: Reviving Randomization for Experimental Economists

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  • Robert Moir

Abstract

Data created in a controlled laboratory setting are a relatively new phenomenon to economists. Traditional data analysis methods using either parametric or nonparametric tests are not necessarily the best option available to economists analyzing laboratory data. In 1935, Fisher proposed the randomization technique as an alternative data analysis method when examining treatment effects. The observed data are used to create a test statistic. Then treatment labels are shuffled across the data and the test statistic is recalculated. The original statistic can be ranked against all possible test statistics that can be generated by these data, and a p-value can be obtained. A Monte Carlo analysis of t-test, the Mann-Whitney U-test, and the exact randomization t-test is conducted. The exact randomization t-test compares favorably to the other two tests both in terms of size and power. Given the limited distributional assumptions necessary for implementation of the exact randomization test, these results suggest that experimental economists should consider using the exact randomization test more often. Copyright Economic Science Association 1998

Suggested Citation

  • 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.
  • Handle: RePEc:kap:expeco:v:1:y:1998:i:1:p:87-100
    DOI: 10.1023/A:1009961917752
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    References listed on IDEAS

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    1. Chan, Kenneth S. & Mestelman, Stuart & Muller, R. Andrew, 2008. "Voluntary Provision of Public Goods," Handbook of Experimental Economics Results, Elsevier.
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    3. Simon Gaechter & Daniele Nosenzo & Elke Renner & Martin Sefton, 2009. "Sequential versus Simultaneous Contributions to Public Goods: Experimental Evidence," CESifo Working Paper Series 2602, CESifo Group Munich.
    4. Buckley, Neil & Cuff, Katherine & Hurley, Jeremiah & Mestelman, Stuart & Thomas, Stephanie & Cameron, David, 2016. "Should I stay or should I go? Exit options within mixed systems of public and private health care finance," Journal of Economic Behavior & Organization, Elsevier, vol. 131(PB), pages 62-77.
    5. Kenneth Chan & Stuart Mestelman & Robert Moir & R. Muller, 1999. "Heterogeneity and the Voluntary Provision of Public Goods," Experimental Economics, Springer;Economic Science Association, vol. 2(1), pages 5-30, August.
    6. Klaus Abbink & Jordi Brandts, 2005. "Collusion in Growing and Shrinking Markets: Empirical Evidence from Experimental Duopolies," Working Papers 168, Barcelona Graduate School of Economics.
    7. Abbink, Klaus & Bolton, Gary E. & Sadrieh, Abdolkarim & Tang, Fang-Fang, 2001. "Adaptive Learning versus Punishment in Ultimatum Bargaining," Games and Economic Behavior, Elsevier, vol. 37(1), pages 1-25, October.
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    17. Rob Moir, 2004. "Lotteries as a funding tool for financing public goods," CEEL Working Papers 0401, Cognitive and Experimental Economics Laboratory, Department of Economics, University of Trento, Italia.
    18. Hanna Fromell & Daniele Nosenzo & Trudy Owens & Fabio Tufano, 2017. "Are Victims Truly Worse Off in the Presence of Bystanders? Revisiting the Bystander Effect," Discussion Papers 2017-15, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    19. Nathaniel T. Wilcox & Mark V. Van Boening, 2003. "Distribution and Dynamics in a Simple Tax Regime Transition," Working Papers 2003-02 Classification-C9, Department of Economics, University of Houston.
    20. Buckley, Neil & Cuff, Katherine & Hurley, Jeremiah & Mestelman, Stuart & Thomas, Stephanie & Cameron, David, 2015. "Support for public provision of a private good with top-up and opt-out: A controlled laboratory experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 111(C), pages 177-196.
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    Keywords

    Randomization test; Monte Carlo simulation;

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