Oleg Itskhoki (Harvard University, USA, Central Economics & Mathematics Institute, Russia)
Abstract
In this essay we postulate a number of theoretical hypotheses allowing one to resolve in some degree the following two prediction paradoxes: (1) why simple linear models often have an advantage in predictive power over more complex nonlinear models that lead to a better in-sample fit; (2) why combinations of forecasts often increase the predictive power of individual forecasts. We also give a numerical example illustrating our theoretical statements.
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Article provided by Quantile in its journal Quantile.
Volume (Year): (2006) Issue (Month): 1 (September) Pages: 43-51 Download reference. The following formats are available: HTML
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