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Model selection and paradoxes of prediction (in Russian)

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  • 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.

Suggested Citation

  • Oleg Itskhoki, 2006. "Model selection and paradoxes of prediction (in Russian)," Quantile, Quantile, issue 1, pages 43-51, September.
  • Handle: RePEc:qnt:quantl:y:2006:i:1:p:43-51
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    Cited by:

    1. Taganov, B. & Idrisov, G., 2016. "Investment Effects of Preferential Trade Agreements: Quality Matters," Journal of the New Economic Association, New Economic Association, vol. 31(3), pages 40-65.

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