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On the limitations of comparing mean square forecast errors: Clarifications and extensions

โœ Scribed by Neil R. Ericsson

Publisher
John Wiley and Sons
Year
1993
Tongue
English
Weight
323 KB
Volume
12
Category
Article
ISSN
0277-6693

No coin nor oath required. For personal study only.

โœฆ Synopsis

method is essentially no improvement over an unrestricted VAR, but an exact MLE is superior to both. The puzzle is solved when it is realized that asymptotically the GFSEM is a monotonic function of the one-step-ahead forecast errors regardless of the horizon. The EG estimator is inferior to the UVAR method for one-step-ahead estimation which in turn is inferior to the MLE which optimally imposes the true cointegrating restrictions. Thus the GFSEM criterion is not really a multi-step criterion. The problem of comparing long-horizon forecasts has been solved by outlawing it.

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Meese, R. A. and Rogoff, K., 'Empirical exchange rate models of the seventies: do they fit out of sample?' Journal of International Economics, 14 (1983a). 1, 3-24. Meese, R. A. and Rogoff, K. 'The out-of-sample failure of empirical exchange rate models: sampling error or misspecification?', Chapter

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An algebraic relationship between mean square error comparisons and encompassing tests is provided by a contrast of two of the earliest regression equations for comparing forecasting formulas. Hoel (1947) proposed a regression equation of precisely the form given by CH (equation (44)), namely, wher

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See Chinn and Meese (1992) for evidence and justification of constrained parameter values. They use x(r) = [ s ( t )log(rn(r)/rn\*(r)) + 0.75 log(y(f)/y\*(t)) -4.5(i(f) -i\*(r))l, where rn, y , and i are domestic money supply, real income, and interest rate proxies, respectively. Foreign values of t