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Bayesian Approach and Identification

Author

Listed:
  • Kociecki, Andrzej
Abstract
The paper aims at systematic placement of identification concept within Bayesian approach. Pointing to some deficiencies of the standard Bayesian language to describe identification problem we propose several useful characterizations that seem to be intuitively sound and attractive given their potential applications. We offer comprehensive interpretations for them. Moreover we introduce the concepts of uniform, marginal and faithful identification. We argue that all these concepts may have practical significance. Our theoretical development is illustrated with a number of simple examples and one real application i.e. Structural VAR model.

Suggested Citation

  • Kociecki, Andrzej, 2013. "Bayesian Approach and Identification," MPRA Paper 46538, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:46538
    as

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    File URL: https://mpra.ub.uni-muenchen.de/46538/1/MPRA_paper_46538.pdf
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    References listed on IDEAS

    as
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    13. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2007. "Assessing Structural VARs," NBER Chapters, in: NBER Macroeconomics Annual 2006, Volume 21, pages 1-106, National Bureau of Economic Research, Inc.
    14. Cooley, Thomas F. & Dwyer, Mark, 1998. "Business cycle analysis without much theory A look at structural VARs," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 57-88.
    15. Gustafson, Paul, 2009. "What Are the Limits of Posterior Distributions Arising From Nonidentified Models, and Why Should We Care?," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1682-1695.
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    Cited by:

    1. Michele Piffer, 2016. "Assessing Identifying Restrictions in SVAR Models," Discussion Papers of DIW Berlin 1563, DIW Berlin, German Institute for Economic Research.

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    More about this item

    Keywords

    Bayesian; Identification;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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