Price dispersion in stationary networked markets
Section snippets
The market
There is a finite set B of types of buyers and a finite set S of types of sellers of a homogenous good. The type i of a buyer is determined by her value for the good and the set of sellers that she can trade with. Similarly, the type j of a seller is determined by her cost of producing the good and the set of buyers that she can trade with. I let N denote the set of all types of agents—that is, the union of the set B and the set S—and I let n denote the cardinality of the set N.10
Equilibrium: arbitrary bargaining frictions
In this section, I investigate the subgame-perfect equilibrium of the game for an arbitrary discount factor δ.15 After describing the sense in which this game admits an essentially unique equilibrium, I investigate what determines the equilibrium terms of trade in
Equilibrium: arbitrarily-small bargaining frictions
In this section, I characterize the equilibrium prices in the game in the limit as the discount factor δ goes to 1. The only trading frictions that remain in this limit are those generated by the underlying trading network g. Hence, this characterization isolates the effect of the trading network g on the equilibrium terms of trade. After showing that the limit in question is well defined, I leverage the results of the previous section to (i) provide a necessary and sufficient joint
Related literature
This article contributes to the emerging literature on strategic bargaining in networked markets.29 An important part of this literature studies the conditions under which decentralized bargaining in markets without inflows of traders can be efficient and/or feature the law of one price.30
Conclusion
The widespread phenomenon of price dispersion is the result of different frictions that prevent the traders who buy at high prices from reaching out to the traders that sell at low prices. In this paper, I take these frictions as given—in the form of a buyer–seller network that determines which agents can trade with each other—and I show how they shape the prices that emerge when buyers and sellers engage in decentralized strategic bargaining in a stationary market.
The main distinction between
References (30)
- et al.
Bargaining and efficiency in networks
J. Econ. Theory
(2012) - et al.
Markov equilibria in a model of bargaining in networks
Games Econ. Behav.
(2012) Bargaining power in communication networks
Math. Soc. Sci.
(2001)Bargaining in a network of buyers and sellers
J. Econ. Theory
(2004)Limit theorems for markets with sequential bargaining
J. Econ. Theory
(1987)Bargaining in dynamic markets
Games Econ. Behav.
(2017)Steady states in matching and bargaining
J. Econ. Theory
(2017)Bilateral bargaining in networks
J. Econ. Theory
(2007)- Agranov, M., Elliott, M., 2017. Commitment and (in) efficiency: a bargaining experiment....
- et al.
The Nash bargaining solution in economic modelling
Rand J. Econ.
(1986)
An outside option experiment
Q. J. Econ.
The Economics of Bargaining
Matching and bargaining in dynamic markets
Rev. Econ. Stud.
Walras retrouvé: decentralized trading mechanisms and the competitive price
J. Polit. Econ.
Cited by (6)
Bargaining in small dynamic markets
2023, Journal of Economic TheoryCitation Excerpt :In these papers, either there is no arrival, or traders are immediately replaced by copies of themselves upon transaction; furthermore, traders are heterogeneous because of their different valuations and/or different positions in the network. Both Talamàs and Elliott and Nava show that the network incompleteness and trader heterogeneity generate inefficiency, price dispersion, and delay. Here, we instead study an endogenously evolving unstructured market (i.e., with a complete network) with homogeneous traders and ask how the endogenous arrival determines—and is determined by—the bargaining outcome.
Bargaining and Exclusion With Multiple Buyers
2024, EconometricaTwo-Player Location-Price Game in a Spoke Market with Linear Transportation Cost
2021, Discrete Dynamics in Nature and SocietyLocation-price game in a dual-circle market with different demand levels
2021, Mathematical Problems in Engineering
- 1
The guidance of Benjamin Golub throughout the process of conducting and presenting this research has been essential. I thank Eduardo Azevedo, Matthew Elliott, Edward Glaeser, Sanjeev Goyal, Jerry Green, Mihai Manea, Eric Maskin, Pau Milán and Rakesh Vohra, as well as several audiences and anonymous referees, for useful feedback. This work was supported by the Warren Center for Network & Data Sciences, and the Rockefeller Foundation (#2017PRE301). All errors are my own.