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The Power And Size Of Nonparametric Tests For Common Distributional Characteristics

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  • Gordon Anderson

Abstract

This paper considers the power and size properties of some well known nonparametric linear rank tests for location and scale as well as the Kolmogorov-Smirnov omnibus test and proposed alternatives to it. Independence between some classes of linear rank tests is established facilitating their joint application. Monte Carlo study confirms the asymptotic power properties of the linear rank tests but raises concerns about their application in more general and practically relevant circumstances. It also indicates that the new omnibus tests constitute viable alternatives with superior properties to the Kolmogorov-Smirnov test in certain circumstances.

Suggested Citation

  • Gordon Anderson, 2001. "The Power And Size Of Nonparametric Tests For Common Distributional Characteristics," Econometric Reviews, Taylor & Francis Journals, vol. 20(1), pages 1-30.
  • Handle: RePEc:taf:emetrv:v:20:y:2001:i:1:p:1-30
    DOI: 10.1081/ETC-100104077
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    Citations

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    Cited by:

    1. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F, 2002. "The Properties Of Some Goodness-Of-Fit Tests," The Warwick Economics Research Paper Series (TWERPS) 653, University of Warwick, Department of Economics.
    2. Xiang, Chong, 2007. "Diversification cones, trade costs and factor market linkages," Journal of International Economics, Elsevier, vol. 71(2), pages 448-466, April.
    3. Gordon Anderson, 2008. "The empirical assessment of multidimensional welfare, inequality and poverty: Sample weighted multivariate generalizations of the Kolmogorov–Smirnov two sample tests for stochastic dominance," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(1), pages 73-87, March.
    4. Anderson, Gordon & Ge, Ying, 2005. "The size distribution of Chinese cities," Regional Science and Urban Economics, Elsevier, vol. 35(6), pages 756-776, November.
    5. Anderson, Gordon, 2004. "Toward an empirical analysis of polarization," Journal of Econometrics, Elsevier, vol. 122(1), pages 1-26, September.
    6. Li, Qi & Maasoumi, Esfandiar & Racine, Jeffrey S., 2009. "A nonparametric test for equality of distributions with mixed categorical and continuous data," Journal of Econometrics, Elsevier, vol. 148(2), pages 186-200, February.
    7. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2004. "Decompositions of Pearson's chi-squared test," Journal of Econometrics, Elsevier, vol. 123(1), pages 189-193, November.

    More about this item

    Keywords

    Two sample linear rank tests; Omnibus tests; JEL Classification: C12; C14;

    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

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