Dynamic Directed Random Matching

Darrell Duffie, Lei Qiao and Yeneng Sun
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Lei Qiao: Shanghai University of Finance and Economics
Yeneng Sun: National University of Singapore

Research Papers from Stanford University, Graduate School of Business

Abstract: We develop a general and unified model in which a continuum of agents conduct directed random searches for counterparties. Our results provide the first probabilistic foundation for static and dynamic models of directed search (including the matching-function approach) that are common in search-based models of financial markets, monetary theory, and labor economics. The agents' types are shown to be independent discrete-time Markov processes that incorporate the effects of random mutation, random matching with match-induced type changes, and with the potential for enduring partnerships that may have randomly timed break-ups. The multi-period cross-sectional distribution of types is shown to be deterministic and is calculated using the exact law of large numbers.

JEL-codes: C02 D83 E00 G10 J64 (search for similar items in EconPapers)
Date: 2017-12
New Economics Papers: this item is included in nep-dge, nep-mac, nep-mic and nep-sea
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Related works:
Journal Article: Dynamic directed random matching (2018)
Working Paper: Dynamic Directed Random Matching (2015)
Working Paper: Dynamic Directed Random Matching (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:ecl:stabus:repec:ecl:stabus:3359

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