The properties of some goodness-of-fit tests
The properties of Pearson’s goodness-of-fit test, as used in density forecast evaluation, income distribution analysis and elsewhere, are analysed. The components-of-chi-squared or “Pearson analog” tests of Anderson (1994) are shown to be less generally applicable than was originally claimed. For the case of equiprobable classes, where the general components tests remain valid, a Monte Carlo study shows that tests directed towards skewness and kurtosis may have low power, due to differences between the class boundaries and the intersection points of the distributions being compared. The power of individual component tests can be increased by the use of nonequiprobable classes.
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NBER Working Papers
6228, National Bureau of Economic Research, Inc.
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"Evaluating Density Forecasts,"
Center for Financial Institutions Working Papers
97-37, Wharton School Center for Financial Institutions, University of Pennsylvania.
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- repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
- 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.
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