Henrik Kleven
Kristian Jakobsen
Katrine Marie Jakobsen
Alessandro Guarnieri
Tanguy van Ypersele
Fabien Petit
Cecilia García-Peñalosa
Yonatan Berman
Nina Weber
Julian Limberg
David Hope
Pedro Tremacoldi-Rossi
Tatiana Mocanu
Marco Ranaldi
Silvia Vannutelli
Raymond Fisman
John Voorheis
Reed Walker
Janet Currie
Roel Dom
Marcos Vera-Hernández
Emla Fitzsimons
José V. Rodríguez Mora
Tomasa Rodrigo
Álvaro Ortiz
Stephen Hansen
Vasco Carvalho
Gergely Buda
Gabriel Zucman
Anders Jensen
Matthew Fisher-Post
José-Alberto Guerra
Myra Mohnen
Christopher Timmins
Ignacio Sarmiento-Barbieri
Peter Christensen
Linda Wu
Gaurav Khatri
Julián Costas-Fernández
Eleonora Patacchini
Jorgen Harris
Marco Battaglini
Ricardo Fernholz
Alberto Bisin
Jess Benhabib
Cian Ruane
Pete Klenow
Mark Bils
Peter Hull
Will Dobbie
David Arnold
Eric Zwick
Owen Zidar
Matt Smith
Ansgar Walther
Tarun Ramadorai
Paul Goldsmith-Pinkham
Andreas Fuster
Ellora Derenoncourt
Golvine de Rochambeau
Vinayak Iyer
Jonas Hjort
Elena Simintzi
Paige Ouimet
Holger Mueller
Pablo Garriga
Gabriel Ulyssea
Costas Meghir
Pinelopi Koujianou Goldberg
Rafael Dix-Carneiro
Alessandro Toppeta
Áureo de Paula
Orazio Attanasio
Seth Zimmerman
Joseph Price
Valerie Michelman
Camille Semelet
Anne Brockmeyer
Pierre Bachas
Santiago Pérez
Elisa Jácome
Leah Boustan
Ran Abramitzky
Jesse Rothstein
Jeffrey T. Denning
Sandra Black
Wei Cui
Mathieu Leduc
Philippe Jehiel
Shivam Gujral
Suraj Sridhar
Attila Lindner
Arindrajit Dube
Pascual Restrepo
Łukasz Rachel
Benjamin Moll
Kirill Borusyak
Michael McMahon
Frederic Malherbe
Gabor Pinter

Inequality and network structure

What is this research about and why did you do it?

Studies of wealth inequality (and other forms of economic disparity) are sometimes based on bargaining models among classes or other groups of individuals and in other cases as the outcome of interactions among individuals without regard for their connections to each other. We wanted to consider cases in which people are connected via social and economic networks (some more connected than others) and then explore how the structure of these network connections affects the equilibrium degree of inequality among the network participants. 

How did you answer this question?

The conventional answer to this question is based on the idea that the well connected and particularly those who have intermediate positions between many others in the network will be advantaged because they are able to extract rents similar to charging tolls on a busy road. We proposed, instead, that the advantaged positions in the network would be those who are connected to many others who are themselves not very well connected. The logic is that  the unconnected will have few outside options should they decide to reject a highly unequal offer from a more central individual. 

What did you find?

In our model: (i) any distribution of value across the network must be stable with respect to coalitional deviations (severing links), and (ii) the network structure itself determines the coalitions that may form. We show that if players can jointly deviate from a proposed distribution only if they form a clique in the network, then the degree of inequality that can be sustained depends on how unconnected the members of the network are (technically on the size of the maximum independent set.) Nodes in an independent set could be employees not belonging to a trade union, or sharecroppers not part of a village community. 

What implications does this have for the research on wealth concentration or economic inequality?

Our research provides an alternative to the standard view of the wealthy as a toll collector, holding up trading partners so as to capture some of the rents associated with the gains from trade. In our model the wealthy exercise power over their employees, share-croppers or others whose reservation options  and opportunities for collective action to resist unequal offers are limited due to their being unconnected to others. Both forms of power are important for understanding wealth inequality. 

What are the next steps in your agenda?

The Project on the Dynamics of Wealth Inequality at the Santa Fe Institute and the University of Cincinnati is collecting a panel data set on network structures and wealth inequality in over 40 small scale societies around the world to explore both the rent seeking toll collector and the collective action view of the relationship between network structure and wealth inequality. 

Citation and related literature

This paper can be cited as follows: Kets, W., Iyengar, G., Sethi, R.and Bowles, S. (2011) 'Inequality and Network Structure.' Games and Economic Behavior, 73, pp. 215-26.

Related literature:

About the authors