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

Thomas Demuynck

Journal of Mathematical Economics, 2021, vol. 97, issue C

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: Revealed preference; Markov Chain Monte Carlo; Bronars power (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: 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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Persistent link: https://EconPapers.repec.org/RePEc:eee:mateco:v:97:y:2021:i:c:s0304406821000860

DOI: 10.1016/j.jmateco.2021.102523

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