Dynamic Directed Random Matching

76 Pages Posted: 16 Nov 2015 Last revised: 19 May 2023

See all articles by Darrell Duffie

Darrell Duffie

Stanford University - Graduate School of Business; National Bureau of Economic Research (NBER); Canadian Derivatives Institute

Lei Qiao

National University of Singapore (NUS)

Yeneng Sun

National University of Singapore (NUS)

Date Written: November 2015

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.

Suggested Citation

Duffie, James Darrell and Qiao, Lei and Sun, Yeneng, Dynamic Directed Random Matching (November 2015). NBER Working Paper No. w21731, Available at SSRN: https://ssrn.com/abstract=2691249

James Darrell Duffie (Contact Author)

Stanford University - Graduate School of Business ( email )

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Canadian Derivatives Institute ( email )

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Lei Qiao

National University of Singapore (NUS) ( email )

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Singapore

Yeneng Sun

National University of Singapore (NUS) ( email )

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