Martin Nybom
Jan Stuhler
Mattia Fochesato
Sam Bowles
Linda Wu
Tzu-Ting Yang
Thomas Piketty
Malka Guillot
Jonathan Goupille-Lebret
Bertrand Garbinti
Antoine Bozio
Hakki Yazici
Slavík Ctirad
Kina Özlem
Tilman Graff
Tilman Graff
Yuri Ostrovsky
Martin Munk
Anton Heil
Maitreesh Ghatak
Robin Burgess
Oriana Bandiera
Claire Balboni
Jonna Olsson
Richard Foltyn
Minjie Deng
Iiyana Kuziemko
Elisa Jácome
Juan Pablo Rud
Bridget Hofmann
Sumaiya Rahman
Martin Nybom
Stephen Machin
Hans van Kippersluis
Anne C. Gielen
Espen Bratberg
Jo Blanden
Adrian Adermon
Maximilian Hell
Robert Manduca
Robert Manduca
Marta Morazzoni
Aadesh Gupta
David Wengrow
Damian Phelan
Amanda Dahlstrand
Andrea Guariso
Erika Deserranno
Lukas Hensel
Stefano Caria
Vrinda Mittal
Ararat Gocmen
Clara Martínez-Toledano
Yves Steinebach
Breno Sampaio
Joana Naritomi
Diogo Britto
François Gerard
Filippo Pallotti
Heather Sarsons
Kristóf Madarász
Anna Becker
Lucas Conwell
Michela Carlana
Katja Seim
Joao Granja
Jason Sockin
Todd Schoellman
Paolo Martellini
UCL Policy Lab
Natalia Ramondo
Javier Cravino
Vanessa Alviarez
Hugo Reis
Pedro Carneiro
Raul Santaeulalia-Llopis
Diego Restuccia
Chaoran Chen
Brad J. Hershbein
Claudia Macaluso
Chen Yeh
Xuan Tam
Xin Tang
Marina M. Tavares
Adrian Peralta-Alva
Carlos Carillo-Tudela
Felix Koenig
Joze Sambt
Ronald Lee
James Sefton
David McCarthy
Bledi Taska
Carter Braxton
Alp Simsek
Plamen T. Nenov
Gabriel Chodorow-Reich
Virgiliu Midrigan
Corina Boar
Sauro Mocetti
Guglielmo Barone
Martin Nybom
Jan Stuhler
Mattia Fochesato
Sam Bowles
Linda Wu
Tzu-Ting Yang
Thomas Piketty
Malka Guillot
Jonathan Goupille-Lebret
Bertrand Garbinti
Antoine Bozio
Hakki Yazici
Slavík Ctirad
Kina Özlem
Tilman Graff
Tilman Graff
Yuri Ostrovsky
Martin Munk
Anton Heil
Maitreesh Ghatak
Robin Burgess
Oriana Bandiera
Claire Balboni
Jonna Olsson
Richard Foltyn
Minjie Deng
Iiyana Kuziemko
Elisa Jácome
Juan Pablo Rud
Bridget Hofmann
Sumaiya Rahman
Martin Nybom
Stephen Machin
Hans van Kippersluis
Anne C. Gielen
Espen Bratberg
Jo Blanden
Adrian Adermon
Maximilian Hell
Robert Manduca
Robert Manduca
Marta Morazzoni
Aadesh Gupta
David Wengrow
Damian Phelan
Amanda Dahlstrand
Andrea Guariso
Erika Deserranno
Lukas Hensel
Stefano Caria
Vrinda Mittal
Ararat Gocmen
Clara Martínez-Toledano
Yves Steinebach
Breno Sampaio
Joana Naritomi
Diogo Britto
François Gerard
Filippo Pallotti
Heather Sarsons
Kristóf Madarász
Anna Becker
Lucas Conwell
Michela Carlana
Katja Seim
Joao Granja
Jason Sockin
Todd Schoellman
Paolo Martellini
UCL Policy Lab
Natalia Ramondo
Javier Cravino
Vanessa Alviarez
Hugo Reis
Pedro Carneiro
Raul Santaeulalia-Llopis
Diego Restuccia
Chaoran Chen
Brad J. Hershbein
Claudia Macaluso
Chen Yeh
Xuan Tam
Xin Tang
Marina M. Tavares
Adrian Peralta-Alva
Carlos Carillo-Tudela
Felix Koenig
Joze Sambt
Ronald Lee
James Sefton
David McCarthy
Bledi Taska
Carter Braxton
Alp Simsek
Plamen T. Nenov
Gabriel Chodorow-Reich
Virgiliu Midrigan
Corina Boar
Sauro Mocetti
Guglielmo Barone

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