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
Angus Foulis
Saleem Bahaj
Stone Centre
Phil Thornton
James Baggaley
Xavier Jaravel
Richard Blundell
Parama Chaudhury
Dani Rodrik
Alan Olivi
Vincent Sterk
Davide Melcangi
Enrico Miglino
Fabian Kosse
Daniel Wilhelm
Azeem M. Shaikh
Joseph Romano
Magne Mogstad
Suresh Naidu
Ilyana Kuziemko
Daniel Herbst
Henry Farber
Lisa Windsteiger
Ruben Durante
Mathias Dolls
Cevat Giray Aksoy
Angel Sánchez
Penélope Hernández
Antonio Cabrales
Wendy Carlin
Suphanit Piyapromdee
Garud Iyengar
Willemien Kets
Rajiv Sethi
Ralph Luetticke
Benjamin Born
Amy Bogaard
Mattia Fochesato
Samuel Bowles
Guanyi Wang
CORE
David Cai
Toru Kitagawa
Michela Tincani
Christian Bayer
Arun Advani
Elliott Ash
Imran Rasul

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

Size:
0
Mb