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Choice is suffering: A Focused Information Criterion for model selection

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  • Behl, Peter
  • Dette, Holger
  • Frondel, Manuel
  • Tauchmann, Harald

Abstract

In contrast to conventional measures, the Focused Information Criterion (FIC) allows the purpose-specific selection of models, thereby reflecting the idea that one kind of model might be appropriate for inferences on a parameter of interest, but not for another. Ever since its invention, the FIC has been increasingly applied in the realm of statistics, but this concept appears to be virtually unknown in the economic literature. Using a straightforward analytical example, this paper provides for a didactic illustration of the FIC and demonstrates its usefulness in economic applications.

Suggested Citation

  • Behl, Peter & Dette, Holger & Frondel, Manuel & Tauchmann, Harald, 2012. "Choice is suffering: A Focused Information Criterion for model selection," Economic Modelling, Elsevier, vol. 29(3), pages 817-822.
    • Handle: RePEc:eee:ecmode:v:29:y:2012:i:3:p:817-822
    DOI: 10.1016/j.econmod.2011.09.002
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    1. Manuel Frondel & Christoph M. Schmidt, 2006. "The Empirical Assessment of Technology Differences: Comparing the Comparable," The Review of Economics and Statistics, MIT Press, vol. 88(1), pages 186-192, February.
    2. Hjort, Nils Lid & Claeskens, Gerda, 2006. "Focused Information Criteria and Model Averaging for the Cox Hazard Regression Model," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1449-1464, December.
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    5. Christian T. Brownlees & Giampiero M. Gallo, 2008. "On Variable Selection for Volatility Forecasting: The Role of Focused Selection Criteria," Journal of Financial Econometrics, Oxford University Press, vol. 6(4), pages 513-539, Fall.
    6. Claeskens, Gerda & Hjort, Nils Lid, 2008. "Minimizing Average Risk In Regression Models," Econometric Theory, Cambridge University Press, vol. 24(2), pages 493-527, April.
    7. Holger Dette & Mark Podolskij & Mathias Vetter, 2006. "Estimation of Integrated Volatility in Continuous‐Time Financial Models with Applications to Goodness‐of‐Fit Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 259-278, June.
    8. Manuel Frondel & Christoph M. Schmidt, 2002. "The Capital-Energy Controversy: An Artifact of Cost Shares?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 53-79.
    9. Dette, Holger & Podolskij, Mark, 2008. "Testing the parametric form of the volatility in continuous time diffusion models--a stochastic process approach," Journal of Econometrics, Elsevier, vol. 143(1), pages 56-73, March.
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    Cited by:

    1. Behl, Peter & Dette, Holger & Frondel, Manuel & Vance, Colin, 2019. "A focused information criterion for quantile regression: Evidence for the rebound effect," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 223-227.
    2. Behl, Peter & Dette, Holger & Frondel, Manuel & Tauchmann, Harald, 2013. "Energy substitution: When model selection depends on the focus," Energy Economics, Elsevier, vol. 39(C), pages 233-238.
    3. Behl, Peter & Dette, Holger & Frondel, Manuel & Tauchmann, Harald, 2011. "Being Focused: When the Purpose of Inference Matters for Model Selection," Ruhr Economic Papers 264, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    4. Céline Cunen & Nils Lid Hjort, 2020. "Confidence Distributions for FIC Scores," Econometrics, MDPI, vol. 8(3), pages 1-28, July.

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    More about this item

    Keywords

    Akaike Information Criterion; Schwarz Information Criterion; Translog cost function;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • D2 - Microeconomics - - Production and Organizations

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