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On the limitations of comparing mean square forecast errors: Comment

✍ Scribed by Francis X. Diebold

Publisher: John Wiley and Sons
Year: 1993
Tongue: English
Weight: 130 KB
Volume: 12
Category: Article
ISSN: 0277-6693
DOI: 10.1002/for.3980120804

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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

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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!