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Parameter constancy, mean square forecast errors, and measuring forecast performance: an exposition, extensions, and illustration

  • Neil R. Ericsson

Parameter constancy and a model's mean square forecast error are two commonly used measures of forecast performance. By explicit consideration of the information sets involved, this paper clarifies the roles that each plays in analyzing a model's forecast accuracy. Both criteria are necessary for "good" forecast performance, but neither (nor both) is sufficient. Further, these criteria fit into a general taxonomy of model evaluation statistics, and the information set corresponding to a model's mean square forecast error leads to a new test statistic, forecast-model encompassing. Two models of U.K. money demand illustrate the various measures of forecast accuracy.

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Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 412.

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Date of creation: 1991
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Handle: RePEc:fip:fedgif:412
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  1. Hali J. Edison & Jan Tore Klovland, 1983. "A quantitative reassessment of the purchasing power parity hypothesis : evidence from Norway and the United Kingdom," International Finance Discussion Papers 231, Board of Governors of the Federal Reserve System (U.S.).
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  3. Kiviet, Jan F, 1986. "On the Rigour of Some Misspecification Tests for Modelling Dynamic Relationships," Review of Economic Studies, Wiley Blackwell, vol. 53(2), pages 241-61, April.
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  5. Garry J. Schinasi & P.A.V.B. Swamy, 1987. "The out-of-sample forecasting performance of exchange rate models when coefficients are allowed to change," International Finance Discussion Papers 301, Board of Governors of the Federal Reserve System (U.S.).
  6. Hali J. Edison, 1983. "The rise and fall of sterling: testing alternative models of exchange rate determination," International Finance Discussion Papers 224, Board of Governors of the Federal Reserve System (U.S.).
  7. Fair, Ray C., 1986. "Evaluating the predictive accuracy of models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 3, chapter 33, pages 1979-1995 Elsevier.
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  11. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-93, May.
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  15. Neil R. Ericsson & Julia Campos & Hong-Anh Tran, 1991. "PC-give and David Hendry's econometric methodology," International Finance Discussion Papers 406, Board of Governors of the Federal Reserve System (U.S.).
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  20. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
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  24. Hendry, David F. & Richard, Jean-Francois, 1982. "On the formulation of empirical models in dynamic econometrics," Journal of Econometrics, Elsevier, vol. 20(1), pages 3-33, October.
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  28. repec:cup:cbooks:9780521269124 is not listed on IDEAS
  29. Sargan, J D, 1980. "Some Approximations to the Distribution of Econometric Criteria Which are Asymptotically Distributed as Chi-Squared," Econometrica, Econometric Society, vol. 48(5), pages 1107-38, July.
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  31. Hendry, David F. & Ericsson, Neil R., 1991. "Modeling the demand for narrow money in the United Kingdom and the United States," European Economic Review, Elsevier, vol. 35(4), pages 833-881, May.
  32. Godfrey, Leslie G, 1978. "Testing against General Autoregressive and Moving Average Error Models When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1293-1301, November.
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