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Sensitivity of the Chi-Squared Goodness-of-Fit Test to the Partitioning of Data

  • Boero, Gianna

    (Department of Economics, University of Warwick)

  • Smith, Jeremy

    (Department of Economics, University of Warwick)

  • Wallis, Kenneth F

    (Department of Economics, University of Warwick)

In this paper we conduct a Monte Carlo study to determine the power of Pearson’s overall goodness-of-fit test as well as the “Pearson analog” tests (see Anderson (1994)) to detect rejections due to shifts in variance, skewness and kurtosis, as we vary the number and location of the partition points. Simulations are conducted for small and moderate sample sizes. While it is generally recommended that to improve the power of the goodness-of-fit test the partition points are equiprobable, we find that power can be improved by the use of non-equiprobable partitions.

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File URL: http://www2.warwick.ac.uk/fac/soc/economics/research/workingpapers/2008/twerp694.pdf
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Paper provided by University of Warwick, Department of Economics in its series The Warwick Economics Research Paper Series (TWERPS) with number 694.

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Length: 34 pages
Date of creation: 2004
Date of revision:
Handle: RePEc:wrk:warwec:694
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  1. Marrocu, Emanuela & Gianna Boero, 2003. "The Performance of SETAR models by Regime: A Conditional Evaluation of Interval and Density Forecasts," Royal Economic Society Annual Conference 2003 147, Royal Economic Society.
  2. Anderson, Gordon, 1994. "Simple tests of distributional form," Journal of Econometrics, Elsevier, vol. 62(2), pages 265-276, June.
  3. repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
  4. Wallis, Kenneth F., 2002. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," Royal Economic Society Annual Conference 2002 181, Royal Economic Society.
  5. 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.
  6. Anderson, Gordon, 1996. "Nonparametric Tests of Stochastic Dominance in Income Distributions," Econometrica, Econometric Society, vol. 64(5), pages 1183-93, September.
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