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Prior density ratio class robustness in econometrics

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  • John Geweke
  • Lea Petrella

Abstract

This paper provides a general and efficient method for computing density ratio class bounds on posterior moments, given the output of a posterior simulator. It shows how density ratio class bounds for posterior odds ratios may be formed in many situations, also on the basis of posterior simulator output. The computational method is used to provide density ratio class bounds in two econometric models. It is found that the exact bounds are approximated poorly by their asymptotic approximation, when the posterior distribution of the function of interest is skewed. It is also found that posterior odds ratios display substantial variation within the density ratio class, in ways that cannot be anticipated by the asymptotic approximation.

Suggested Citation

  • John Geweke & Lea Petrella, 1995. "Prior density ratio class robustness in econometrics," Working Papers 553, Federal Reserve Bank of Minneapolis.
    • Handle: RePEc:fip:fedmwp:553
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    Cited by:

    1. Kawther Alimi & Mohamed Chakroun & Grégory Levieuge, 2019. "Diagnosis of Monetary Policy in Tunisia During the Last Decade: a DSGE Model Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(1), pages 348-364, March.
    2. Brutscher, P., 2012. "Self-Disconnection Among Pre-Payment Customers - A Behavioural Analysis," Cambridge Working Papers in Economics 1214, Faculty of Economics, University of Cambridge.

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    Keywords

    Econometrics;

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