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Using Simulation Methods for Bayesian Econometric Models

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Author Info

  • John Geweke

    ()
    (University of Minnesota and FRB)

Abstract

This paper surveys the fundamental principles of subjective Bayesian inference in econometrics and their implementation using posterior simulation methods. The emphasis is on the combination of models and the development of predictive distributions. The paper shows how posterior simulators can facilitate communication between investigators (for example, econometricians) on the one hand and remote clients (for example, decision makers) on the other, enabling clients to vary the prior distributions and functions of interest employed by investigators.

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 832.

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Date of creation: 01 Mar 1999
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Handle: RePEc:sce:scecf9:832

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