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Baysesian inference and model comparison for ramdom choice structures

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  • McCAUSLAND, William
  • MARLEY, A. A. J.

Abstract

We complete the development of a testing ground for axioms of discrete stochastic choice. Our contribution here is to develop new posterior simulation methods for Bayesian inference, suitable for a class of prior distributions introduced by McCausland and Marley (2013). These prior distributions are joint distributions over various choice distributions over choice sets of different sizes. Since choice distributions over different choice sets can be mutually dependent, previous methods relying on conjugate prior distributions do not apply. We demonstrate by analyzing data from a previously reported experiment and report evidence for and against various axioms.

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File URL: https://papyrus.bib.umontreal.ca/xmlui/handle/1866/9776
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Bibliographic Info

Paper provided by Universite de Montreal, Departement de sciences economiques in its series Cahiers de recherche with number 2013-06.

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Length: 27 pages
Date of creation: 2013
Date of revision:
Handle: RePEc:mtl:montde:2013-06

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Keywords: Random utility; discrete choice; Bayesian inference; MCMC;

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  1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-39, November.
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