About

Jeremy Fox is a Professor of Economics at Rice University, specializing in empirical industrial organization. His research also encompasses econometrics and labor economics. Fox has previously worked at the University of Chicago and the University of Michigan. His work has addressed industries such as mobile phones, automobile manufacturing, and venture capital, and includes studies on firm productivity and labor market issues. He is known for his work on estimating models of two-sided matching games and demand. Fox holds a Ph.D. and M.A. in Economics from Stanford University, obtained in 2003, and a B.A. in Economics, Political Science, and Statistics from Rice University, earned in 1998.

Research topics

• Econometrics
• Economics
• Mathematics
• Computer science
• Mathematical economics

Selected publications

• Repeated Matching Games An Empirical Framework

  National Bureau of Economic Research · 2025-10-01

  reportOpen access
  PublisherDOI

• Repeated Matching Games: An Empirical Framework

  ArXiv.org · 2025-10-03

  preprintOpen access

  We introduce a model of dynamic matching with transferable utility, extending the static model of Shapley and Shubik (1971). Forward-looking agents have individual states that evolve with current matches. Each period, a matching market with market-clearing prices takes place. We prove the existence of an equilibrium with time-varying distributions of agent types and show it is the solution to a social planner's problem. We also prove that a stationary equilibrium exists. We introduce econometric shocks to account for unobserved heterogeneity in match formation. We propose two algorithms to compute a stationary equilibrium. We adapt both algorithms for estimation. We estimate a model of accumulation of job-specific human capital using data on Swedish engineers.

  PublisherOA PDFDOI

• Repeated Matching Games An Empirical Framework

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Generative intelligence systems in the flow of group emotions

  2025-10-18

  articleOpen access

  Emotional cues frequently arise and shape group dynamics in interactive settings where multiple humans and artificial agents communicate through shared digital channels. While artificial agents lack intrinsic emotional states, they can simulate affective behavior using synthetic modalities such as text or speech. This work introduces a conceptual model for orchestrating emotion contagion, aiming to enable agents to detect emotional signals, infer group mood patterns, and generate targeted emotional responses. The system captures human emotional exchanges and uses this insight to produce adaptive, generative responses that influence group affect in real time. The model supports applications in collaborative, educational, and social environments by shifting affective computing from individual-level reactions to coordinated, group-level emotion modulation. We present the system architecture and provide experimental results that illustrate its effectiveness in sensing and steering group mood dynamics. While preliminary results illustrate feasibility, further empirical validation and large-scale testing are needed to assess robustness and generalizability.

  PublisherOA PDFDOI

• Estimating matching games with transfers

  Quantitative Economics · 2018-03-01 · 98 citations

  articleOpen access1st authorCorresponding

  I explore the estimation of transferable utility matching games, encompassing many-to-many matching, marriage, and matching with trading networks (trades). Computational issues are paramount. I introduce a matching maximum score estimator that does not suffer from a computational curse of dimensionality in the number of agents in a matching market. I apply the estimator to data on the car parts supplied by automotive suppliers to estimate the valuations from different portfolios of parts to suppliers and automotive assemblers.

  PublisherOA PDFDOI

• Matching Models: Empirics

  The New Palgrave Dictionary of Economics · 2018-01-01

  book-chapter1st authorCorresponding

  A matching model takes a set of payoffs or outputs for all possible matches and produces a set of matches where no couple would prefer to deviate and become matched, instead of their assigned matches. Matching models are increasingly being estimated in empirical work in industrial organization, labour economics, public economics, and other fields. This article surveys methods for and applications of structural estimation for two-sided matching games.

  PublisherDOI

• Unobserved Heterogeneity in Matching Games

  Journal of Political Economy · 2018-03-16 · 54 citations

  article1st authorCorresponding

  Agents in two-sided matching games vary in characteristics that are unobservable in typical data on matching markets. We investigate the identification of the distribution of unobserved characteristics using data on who matches with whom. In full generality, we consider many-to-many matching and matching with trades. The distribution of match-specific unobservables cannot be fully recovered without information on unmatched agents, but the distribution of a combination of unobservables, which we call unobserved complementarities, can be identified. Using data on unmatched agents restores identification.

  PublisherDOI

• A note on identification of discrete choice models for bundles and binary games

  Quantitative Economics · 2017-11-01 · 34 citations

  articleOpen access1st authorCorresponding

  We study nonparametric identification of single-agent discrete choice models for bundles (without requiring bundle-specific prices) and of binary games of complete information. We show that these two models are quite similar from an identification standpoint. Moreover, they are mathematically equivalent when we restrict attention to the class of potential games and impose a specific equilibrium selection mechanism in the data generating process. We provide new identification results for the two related models.

  PublisherOA PDFDOI

• Specifying a Structural Matching Game of Trading Networks with Transferable Utility

  American Economic Review · 2017-05-01 · 9 citations

  article1st authorCorresponding

  Structural estimation of matching games with transferable utility, including matching games of trading networks and many-to-many matching, is increasingly popular in empirical work. I explore several modeling decisions that need to be made when specifying a structural model for a matching game. One decision is the choice of a game theoretic solution concept to impose in the structural model. I discuss pairwise stability, competitive equilibrium, and noncooperative games such as auctions. Another decision is whether to work with a continuum of agents or a finite number of agents. I explore other issues as well.

  PublisherDOI

• A Note on Nonparametric Identification of Distributions of Random Coefficients in Multinomial Choice Models

  National Bureau of Economic Research · 2017-07-01 · 7 citations

  preprintOpen access1st authorCorresponding

  I prove that the joint distribution of random coefficients and additive errors is identified in a mulltinomial choice model. No restrictions are imposed on the support of the random coefficients and additive errors. The proof uses large support variation in choice-specific explanatory variables following Lewbel (2000) but does not rely on an identification at infinity technique where the payoffs of all but two choices are set to minus infinity.

  PublisherOA PDFDOI

Frequent coauthors

• Patrick Bajari

  24 shared

• Stephen Ryan

  Washington University in St. Louis

  13 shared

• Kyoo il Kim

  Abbott (Switzerland)

  11 shared

• Amit Gandhi

  8 shared

• Valérie Smeets

  6 shared

• Chenyu Yang

  Peking University

  5 shared

• Jacob K. Goeree

  UNSW Sydney

  5 shared

• Michelle S. Caird

  Orthopaedic Research Laboratories

  4 shared