Abstract

http://ssrn.com/abstract=938735
 


 



Model Selection and Paradoxes of Prediction


Oleg Itskhoki


Princeton University - Department of Economics


Quantile Journal, Vol. 1, pp. 43-51, 2006

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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Date posted: October 20, 2006  

Suggested Citation

Itskhoki, Oleg, Model Selection and Paradoxes of Prediction. Quantile Journal, Vol. 1, pp. 43-51, 2006. Available at SSRN: http://ssrn.com/abstract=938735

Contact Information

Oleg Itskhoki (Contact Author)
Princeton University - Department of Economics ( email )
Fisher 306
Princeton, NJ 08544-1021
United States
+1 (609) 258-5493 (Phone)
HOME PAGE: http://www.princeton.edu/~itskhoki
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