Bayesian Estimation of Linear Sum Assignment Problems

Yu-Wei Hsieh () and Matthew Shum

A chapter in Essays in Honor of Cheng Hsiao, 2020, vol. 41, pp 323-339 from Emerald Group Publishing Limited

Abstract: The authors propose an Markov Chain Monte Carlo (MCMC) method for estimating a class of linear sum assignment problems (LSAP; the discrete case of the optimal transport problems). Prominent examples include multi-item auctions and mergers in industrial organizations. This contribution is to decompose the joint likelihood of the allocation and prices by exploiting the primal and dual linear programming formulation of the underlying LSAP. Our decomposition, coupled with the data augmentation technique, leads to an MCMC sampler without a repeated model-solving phase.

Keywords: Linear sum assignment problems; two-sided matching; MCMC; position auction; optimal transport; sponsored-search auction; D44; D47; C11; C15 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-905320200000041011

DOI: 10.1108/S0731-905320200000041011

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