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On the limitations of comparing mean square forecast errors: Comment

โœ Scribed by Richard A. Meese

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

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โœฆ Synopsis

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 these variables are indicated with an asterisk.

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On the limitations of comparing mean squ
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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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one-step forecasts is, of course, simply the analogy of many in-sample tests of model specification. In this context, it is amusing that much recent applied econometric work has, in effect, exploited fitted models to make inference about economic systems, as the forecast horizon approaches injinity!