Bayesian inference and model comparison for ramdom choice structures

William McCausland () and A. A. J. Marley

Cahiers de recherche from Universite de Montreal, Departement de sciences economiques

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.

Keywords: Random utility; discrete choice; Bayesian inference; MCMC (search for similar items in EconPapers)
JEL-codes: C11 C35 C53 D01 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2013
New Economics Papers: this item is included in nep-dcm, nep-ecm, nep-ore and nep-upt
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Downloads: (external link)
http://hdl.handle.net/1866/9776 (application/pdf)

Related works:
Working Paper: Bayesian Inference and Model Comparison for Random Choice Structures (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:mtl:montde:2013-06

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