Model selection and paradoxes of prediction (in Russian)

Oleg Itskhoki

Quantile, 2006, issue 1, 43-51

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.

Date: 2006
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:qnt:quantl:y:2006:i:1:p:43-51

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