When an econometric model coincides with the mechanism generating the data in an unchanging world, the theory of economic forecasting is reasonably well developed. However, less is known about forecasting when model and mechanism differ in a nonstationary and changing world. This paper addresses the basic concepts; the invariance of forecast accuracy measures to isopmorphic model representations; the roles of causal information, parsimony, and collinearity; a reformulated taxonomy of forecast errors; differencing and intercept corrections to robustify forecasts against biases due to shifts in deterministic factors; the removal of structural breaks by cobreaking; and forecasting using leading indicators. Copyright 1997 by Royal Economic Society.
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Volume (Year): 107 (1997) Issue (Month): 444 (September) Pages: 1330-57 Download reference. The following formats are available: HTML
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