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The Power And Size Of Nonparametric Tests For Common Distributional Characteristics

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Author Info
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.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal Econometric Reviews.

Volume (Year): 20 (2001)
Issue (Month): 1 ()
Pages: 1-30
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Handle: RePEc:taf:emetrv:v:20:y:2001:i:1:p:1-30

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

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Levy, Frank & Murnane, Richard J, 1992. "U.S. Earnings Levels and Earnings Inequality: A Review of Recent Trends and Proposed Explanations," Journal of Economic Literature, American Economic Association, vol. 30(3), pages 1333-81, September. [Downloadable!] (restricted)
  2. Esfandiar Maasoumi, 1993. "A compendium to information theory in economics and econometrics," Econometric Reviews, Taylor and Francis Journals, vol. 12(2), pages 137-181. [Downloadable!] (restricted)
  3. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-65, May. [Downloadable!] (restricted)
  4. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976 Elsevier. [Downloadable!] (restricted)
  5. Fortin, N.M. & Lemieux, T., 1996. "Rank Regressions, Wage Distributions and the Gender Gap," Cahiers de recherche 9607, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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  6. Stephen Donald & David Green & Harry Paarsch, . "Differences in Earnings and Wage Distributions between Canada and the United States: An Application of a Semi-Parametric Estimator of Distribution Functions with Covariates," Working Papers _003, University of California at Berkeley, Econometrics Laboratory Software Archive. [Downloadable!]
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  7. Anderson, Gordon, 1994. "Simple tests of distributional form," Journal of Econometrics, Elsevier, vol. 62(2), pages 265-276, June. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Gianna Boero & J. Smith & KF. Wallis, 2002. "The properties of some goodness-of-fit tests," Working Paper CRENoS 200209, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia. [Downloadable!]
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  2. 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," Journal of Economic Inequality, Springer, vol. 6(1), pages 73-87, March. [Downloadable!] (restricted)
  3. Qi Li & Esfandiar Maasoumi & Jeffrey S. Racine, 2008. "A Nonparametric Test For Equality Of Distributions With Mixed Categorical And Continuous Data," Emory Economics 0805, Department of Economics, Emory University (Atlanta). [Downloadable!]
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