A Markov Chain Monte Carlo procedure to generate revealed preference consistent datasets

Thomas Demuynck

ULB Institutional Repository from ULB -- Universite Libre de Bruxelles

Abstract: This paper presents Markov-Chain-Monte-Carlo (MCMC) procedures to sample uniformly from the collection of datasets that satisfy some revealed preference test. The MCMC for the GARP test combines a Gibbs-sampler with a simple hit and run step. It is shown that the MCMC has the uniform distribution as its unique invariant distribution and that it converges to this distribution at an exponential rate.

Keywords: Bronars power; Markov Chain Monte Carlo; Revealed preference (search for similar items in EconPapers)
Date: 2021-08-01
New Economics Papers: this item is included in nep-dcm
Note: SCOPUS: ar.j
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Citations: View citations in EconPapers (2)

Published in: Journal of mathematical economics (2021)

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Related works:
Journal Article: A Markov Chain Monte Carlo procedure to generate revealed preference consistent datasets (2021)
Working Paper: Markov Chain Monte Carlo Procedure to Generate Revealed Preference Consistent Datasets (2020)
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