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Bayesian Elicitation Diagnostics

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  • Edward E. Leamer

    (UCLA)

Abstract

One elicitation diagnostic identifies a family of prior distributions that are so diffuse that they are practically equivalent to the "completely" diffuse prior. Another elicitation diagnostic identifies a family of prior distributions that concentrate enough mass in the neighborhood of zero that they are practically equivalent to the dogmatic prior that sets a parameter exactly equal to zero. If either question thus posed can be answered in the affirmative then there is no need to go to the expense of a more accurate elicitation of the prior distribution. Copyright 1992 by The Econometric Society.
(This abstract was borrowed from another version of this item.)

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  • Edward E. Leamer, 1989. "Bayesian Elicitation Diagnostics," UCLA Economics Working Papers 555, UCLA Department of Economics.
    • Handle: RePEc:cla:uclawp:555
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    File URL: http://www.econ.ucla.edu/workingpapers/wp555.pdf
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    Cited by:

    1. Vos, A.F., 1993. "A fair comparison between regression models of different dimension," Serie Research Memoranda 0078, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    2. Magnus, J.R. & Durbin, J., 1996. "A classical problem in linear regression or how to estimate the mean of a univariate normal distribution with known variance," Other publications TiSEM 325b330c-b816-4978-90c2-5, Tilburg University, School of Economics and Management.
    3. Iwata, Shigeru, 1996. "Bounding posterior means by model criticism," Journal of Econometrics, Elsevier, vol. 75(2), pages 239-261, December.

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