A Simple Non-Parametric Test Of Predictive Performance
AbstractThis paper derives a distribution free procedure for testing the accuracy of forecasts when the focus of the analysis is on the correct prediction of the direction of change in the variable under consideration. The test applies to a general m x n contingency table and it is shown that the standard null hypothesis of independence in a contingency table implies the null hypothesis of the proposed test of predictive failure but not vice versa. As a test of predictive performance the chi-squared test of independence will, in general, be more conservative than the suggested test of predictive failure. The paper also contains two applications: A dichotomous version of the test is applied to the CBI's Industrial Trends Surveys of actual and expected price changes in the manufacturing sector, and a trichotomous version of the test is applied to the demand data from business surveys of French manufacturing industry conducted by INSEE.
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Bibliographic InfoPaper provided by California Los Angeles - Applied Econometrics in its series Papers with number 29.
Length: 19 pages
Date of creation: 1990
Date of revision:
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Postal: UNIVERSITY OF CALIFORNIA AT LOS ANGELES, DEPARTMENT OF ECONOMICS, PROGRAM IN APPLIED ECONOMETRICS, LOS ANGELES CALIFORNIA 90024 U.S.A.
Phone: (310) 825 1011
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Web page: http://www.econ.ucla.edu/
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tests ; forecasting methods ; statistics;
Other versions of this item:
- Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-65, October.
- Pesaran, M.H. & Timmermann, A., 1990. "A Simple, Non-Parametric Test Of Predictive Performance," Cambridge Working Papers in Economics 9021, Faculty of Economics, University of Cambridge.
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