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Incorporating prior information when true priors are unknown: An Information-Theoretic approach for increasing efficiency in estimation

Author

Listed:
  • Henderson, Heath
  • Golan, Amos
  • Seabold, Skipper

Abstract

We develop a new way to incorporate prior information within an Information-Theoretic (IT) estimation framework. The estimator considers many potential priors and uses a simple statistic to choose the optimal solution. Our method outperforms its competitors for all finite data.

Suggested Citation

  • Henderson, Heath & Golan, Amos & Seabold, Skipper, 2015. "Incorporating prior information when true priors are unknown: An Information-Theoretic approach for increasing efficiency in estimation," Economics Letters, Elsevier, vol. 127(C), pages 1-5.
  • Handle: RePEc:eee:ecolet:v:127:y:2015:i:c:p:1-5
    DOI: 10.1016/j.econlet.2014.12.014
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    References listed on IDEAS

    as
    1. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    2. Golan, Amos, 2008. "Information and Entropy Econometrics — A Review and Synthesis," Foundations and Trends(R) in Econometrics, now publishers, vol. 2(1–2), pages 1-145, February.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Hyeok Lee & Yong Kyun Kim, 2018. "The effects of external shocks on the Korean economy: CGE model-based analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-14, December.

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    More about this item

    Keywords

    Generalized Cross Entropy; Generalized Maximum Entropy; Information; Maximum Entropy; Priors;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

    Statistics

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