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Variance Estimates and Model Selection

Author

Listed:
  • Sidika Basci
  • Asad Zaman

Abstract

The large majority of the criteria for model selection are functions of the usual variance estimate for a regression model. The validity of the usual variance estimate depends on some assumptions, most critically the validity of the model being estimated. This is often violated in model selection contexts, where model search takes place over invalid models. A cross validated variance estimate is more robust to specification errors (see, for example, Efron, 1983). We consider the effects of replacing the usual variance estimate by a cross validated variance estimate, namely, the Prediction Sum of Squares (PRESS) in the functions of several model selection criteria. Such replacements improve the probability of finding the true model, at least in large samples.
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Suggested Citation

  • Sidika Basci & Asad Zaman, 1998. "Variance Estimates and Model Selection," Working Papers 9814, Department of Economics, Bilkent University.
    • Handle: RePEc:bil:wpaper:9814
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    Cited by:

    1. is not listed on IDEAS
    2. Houcine Senoussi, 2021. "Inflation and Inflation Uncertainty in Growth Model of Barro: An Application of Random Forest Method," International Econometric Review (IER), Econometric Research Association, vol. 13(1), pages 4-23, March.
    3. Ozer Ozdemir & Memmedaga Memmedli & Akhlitdin Nizamitdinov, 2013. "ANN Models and Bayesian Spline Models for Analysis of Exchange Rates and Gold Price," International Econometric Review (IER), Econometric Research Association, vol. 5(2), pages 53-69, September.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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