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The properties of some goodness-of-fit tests

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Boero, Gianna , Smith, Jeremy (Jeremy P.) and Wallis, Kenneth Frank (2002) The properties of some goodness-of-fit tests. Working Paper. University of Warwick, Department of Economics, Coventry.

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Abstract

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.

Item Type: Working or Discussion Paper (Working Paper)
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Social Sciences > Economics
Library of Congress Subject Headings (LCSH): Goodness-of-fit tests, Statistical hypothesis testing, Monte Carlo method, Distribution (Economic theory), Equilibrium (Economics)
Series Name: Warwick economic research papers
Publisher: University of Warwick, Department of Economics
Place of Publication: Coventry
Date: October 2002
Number: No.653
Number of Pages: 25
Status: Not Peer Reviewed
Access rights to Published version: Open Access
References: Anderson, G. (1994). Simple tests of distributional form. Journal of Econometrics, 62, 265-276. Anderson, G. (1996). Nonparametric tests of stochastic dominance in income distributions. Econometrica, 64, 1183-1193. Anderson, G. (2001). The power and size of nonparametric tests for common distributional characteristics. Econometric Reviews, 20, 1-30. Bera, A. K. and Jarque, C. M. (1981), “Efficient tests for normality, homoskedasticity and serial independence of regression residuals”, Economics Letters, 6, 255-259. Boero, G. and Marrocu, E. (2002). The performance of non-linear exchange rate models: a forecasting comparison. Journal of Forecasting, forthcoming. Diebold, F.X., Tay, A.S. and Wallis, K.F. (1999). Evaluating density forecasts of inflation: the Survey of Professional Forecasters. In Cointegration, Causality, and Forecasting: A Festschrift in Honour of Clive W. J. Granger (R.F. Engle and H. White, eds), pp.76-90. Oxford: Oxford University Press. Noceti, P, Smith, J. and Hodges, S. (2000). An evaluation of tests of distributional forecasts. Discussion Paper No.102, Financial Options Research Centre, University of Warwick. Pringle, R.M. and Rayner, A.A. (1971). Generalized Inverse Matrices with Applications to Statistics. London: Charles Griffin. Ramberg, J.S., Dudewicz, E.J., Tadikamalla, P.R. and Mykytka, E. (1979). A probability distribution and its uses in fitting data. Technometrics, 21, 201-214. Rao, C.R. and Rao, M.B. (1998). Matrix Algebra and its Applications to Statistics and Econometrics. Singapore: World Scientific Publishing Co. Stuart, A., Ord, J.K. and Arnold, S. (1999). Kendall’s Advanced Theory of Statistics, 6th ed., vol. 2A. London: Edward Arnold. Tanabe, K. and Sagae, M. (1992). An exact Cholesky decomposition and the generalized inverse of the variance-covariance matrix of the multinomial distribution, with applications. Journal of the Royal Statistical Society B, 54, 211-219. Wallis, K.F. (1999). Asymmetric density forecasts of inflation and the Bank of England’s fan chart. National Institute Economic Review, No. 167, 106-112. Wallis, K.F. (2002). Chi-squared tests of interval and density forecasts, and the Bank of England’s fan charts. International Journal of Forecasting, forthcoming
URI: http://wrap.warwick.ac.uk/id/eprint/1534

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