Academia.eduAcademia.edu

Outline

Title
Abstract
Introduction
Concluding Discussion
References
All Topics
Computer Science

A Survey of Network Formation Models: Stability and Efficiency

Profile image of Myrna WoodersMyrna Wooders

Group Formation in Economics

https://doi.org/10.1017/CBO9780511614385.002
visibility

…

description

62 pages

link

1 file

Abstract

I survey the recent literature on the formation of networks. I provide definitions of network games, a number of examples of models from the literature, and discuss some of what is known about the (in)compatibility of overall societal welfare with individual incentives to form and sever links.

Related papers

Are Individuals Profit Maximising in Network Formation? Some Experimental Evidence
Emanuela Sciubba

2005

We run a computerised experiment of network formation, where all connections are beneficial and only direct links are costly. The game% theoretic basis for the experiment is the model of Goyal and Joshi (2004) where players simultaneously submit link proposals and ...

View PDFchevron_right
Incentives to Cooperate in Network Formation
Haydée Lugo

Computational Economics, 2006

We propose a simple mechanism based on taxes and subsidies to enhance high cooperation in evolutionary networks. The interactions among agents are based on the Spatial Prisoners' Dilemma game in which each agent interacts with the same strategy with its local neighbors, collects an aggregate payoff and imitates the strategy of its best neighbor. First we study the mechanism in a regular lattice where it is well-known that the asymptotic fraction of cooperators fluctuates around a constant value for almost all starting proportions and configurations of cooperators. We also explore the mechanism in random and adaptive networks, where adaptability refers to the ability of agents to change their local neighborhood. For theses networks it has been reported that the starting proportion of cooperation has to be sufficiently high in order to obtain highly cooperative levels in the long-run time. The implementation of our mechanism produces successful results in such evolutionary networks, higher levels of cooperation are reached for all initial fractions of cooperation, including the most adverse case of just one cooperator in the network. Additionally, we observe that the network reaches a spatial configuration such that the fraction of cooperators remains in high level even when the mechanism is switched off. As a result the mechanism can work as an ignition engine to achieve highly cooperative level since it can be implemented for a finite period of time.

View PDFchevron_right
Behavioral experiments on a network formation game
Yevgeniy Vorobeychik, Stephen Judd

Proceedings of the 13th ACM Conference on Electronic Commerce - EC '12, 2012

We report on an extensive series of behavioral experiments in which 36 human subjects collectively build a communication network over which they must solve a competitive coordination task for monetary compensation. There is a cost for creating network links, thus creating a tension between link expenditures and collective and individual incentives. Our most striking finding is the poor performance of the subjects, especially compared to our long series of prior experiments. We demonstrate that the subjects built difficult networks for the coordination task, and compare the structural properties of the built networks to standard generative models of social networks. We also provide extensive analysis of the individual and collective behavior of the subjects, including free riding and factors influencing edge purchasing decisions.

View PDFchevron_right
Essays on the formation of social and economic networks
liza charroin

2018

In a world where networks become a dominant form of organization, the structure of networks and the position of individuals in these networks affect individual behavior and aggregate economic outcomes. The analysis of network formation by a central planner or by individuals themselves is at the heart of this thesis on the economics of networks.Chapter 1 theoretically studies the optimal formation and protection of networks by a central planner knowing that an external agent can destroy k links. The protection of the network can be guaranteed either by densifying the links between nodes, or by protecting the links. When the cost of protection is relatively small, a minimally connected network composed of protected links guarantees the communication flow; if this cost is high, the optimal solution is to form a symmetric network where each node has at least k+1 non-protected links.Chapter 2 explores the decentralized formation of networks in the laboratory by analyzing individual linki...

View PDFchevron_right
Network Structure in a Link Formation Game: An Experimental Study
Roberto Muñoz

Economic Inquiry, 2014

Network formation is frequently modeled using link-formation games and typically present a multiplicity of Nash equilibria. Cooperative re…nements-such as strong or coalitional proof Nash equilibria-have been the standard tool used for equilibrium selection in these games. Non-cooperative re…nements derived from the theory of global games have shown also that, for a class of payo¤ functions, multiplicity of equilibria disappears when the game is perturbed by introducing small amounts of incomplete information. We conducted a laboratory study evaluating the predictive power of each of these re…nements in an illustrative link-formation game. Compared with cooperative game solutions, the global game approach did signi…cantly better at predicting the strategies played by individuals in the experiment.

View PDFchevron_right
Games of Dynamic Network Formation
Claudio J Tessone

2009

We combine a network game introduced in Ballester et al. (2006), where the Nash equilibrium action of each agent is proportional to her Bonacich centrality (Bonacich, 1987), with an endogenous network formation process. Links are formed on the basis of centrality while the network is exposed to a volatile environment introducing interruptions in the connections between agents. Taking into account bounded rational decision making, new links are formed to the neighbors' neighbors with the highest centrality. The volatile environment causes existing links to decay to the neighbor with the lowest centrality. We show analytically that there exist stationary networks and that their topological properties completely match with features exhibited by social and economic networks. Moreover, we find that there exists a sharp transition in efficiency and network density from highly centralized to decentralized networks.

View PDFchevron_right
The impact of negotiable cost-paying on basic models of network formation VERY PRELIMINARY DRAFT
Federico Valenciano

2015

This paper studies the impact of “liberalizing” the cost-paying of links on some basic models of network formation. JEL Classi cation Numbers: A14, C72, D20, J00 Key words: Network formation, Unilateral link-formation, Bilateral linkformation, E¢ ciency, Stability. This research is supported by the Spanish Ministerio de Economía y Competitividad under projects ECO2012-31626 and ECO2012-31346. Both authors also bene t from the Basque Government Departamento de Educación, Política Lingüística y Cultura funding for Grupos Consolidados IT869-13 and IT568-13. yBRiDGE group (http://www.bridgebilbao.es), Departamento de Fundamentos del Análisis Económico I, Universidad del País Vasco, Avenida Lehendakari Aguirre 83, 48015 Bilbao, Spain; norma.olaizola@ehu.es. zBRiDGE group (http://www.bridgebilbao.es), Departamento de Economía Aplicada IV, Universidad del País Vasco, Avenida Lehendakari Aguirre 83, 48015 Bilbao, Spain; federico.valenciano@ehu.es.

View PDFchevron_right
It's all about connections: Evidence on network formation
Armin Falk

We present an economic experiment on network formation, in which subjects can decide to form links to one another. Direct links are costly but being connected is valuable. The gametheoretic basis for our experiment is the model of Bala and Goyal (2000). They distinguish between two scenarios regarding the flow of benefits through a network, the so-called 1-way and 2-way flow model. Our main results show that the prediction based on Nash and strict Nash equilibrium works well in the 1-way flow model but fails largely in the 2-way flow model. We observe a strong learning dynamic in the 1-way flow model but less so in the 2-way flow model. Finally, costs of a direct link have a positive impact on the occurrence of (strict) Nash networks in the 1-way flow model but a negative impact in the 2-way flow model. In our discussion on possible explanations for these results we focus on strategic asymmetry and asymmetry with respect to payoffs. We find that the latter asymmetry, i.e., payoff inequity, plays an important role in the network formation process.

View PDFchevron_right
Econometric Models of Network Formation
Aureo de Paula

2020

This article provides a selective review on the recent literature on econometric models of network formation. The survey starts with a brief exposition on basic concepts and tools for the statistical description of networks. I then offer a review of dyadic models, focussing on statistical models on pairs of nodes and describe several developments of interest to the econometrics literature. The article also presents a discussion of nondyadic models where link formation might be influenced by the presence or absence of additional links, which themselves are subject to similar influences. This is related to the statistical literature on conditionally specified models and the econometrics of game theoretical models. I close with a (non-exhaustive) discussion of potential areas for further development.

View PDFchevron_right
Network Structure in a Link Formation Game: An Experimental Study WORK IN PROGRESS
Alexander Elbittar

Network formation is frequently modeled using link-formation games and typically present a multiplicity of Nash equilibria. Cooperative re…nements -such as strong or coalitional proof Nash equilibria -have been the standard tool used for equilibrium selection in these games. Non-cooperative re…nements derived from the theory of global games have shown also that, for a class of payo¤ functions, multiplicity of equilibria disappears when the game is perturbed by introducing small amounts of incomplete information. We conducted a laboratory study evaluating the predictive power of each of these re…nements in an illustrative link-formation game. Compared with cooperative game solutions, the global game approach did signi…cantly better at predicting the strategies played by individuals in the experiment.

View PDFchevron_right

References (139)

  1. Aizer, A. and J. Currie (2002) "Networks, Neighborhoods, and the Utilization of Publicly-Funded Prenatal Care in California," mimeo UCLA.
  2. Arrow, K.J. and Borzekowski, R. (2000) "Limited Network Connections and the Distribution of Wages," mimeo: Stanford University.
  3. Aumann, R. and Myerson, R. (1988) "Endogenous Formation of Links Between Players and Coalitions: An Application of the Shapley Value," In: Roth, A. (ed.) The Shapley Value, Cambridge University Press, 175-191.
  4. Badasyan, N. and S. Chakrabarti (2003) "Private Peering among Internet Back- bone Providers," mimeo: Virginia Tech.
  5. Bala, V. and Goyal, S. (2000) "A Strategic Analysis of Network Reliability," Review of Economic Design, 5, 205-228.
  6. Bala, V. and Goyal, S. (2000a) "A non-cooperative model of network formation," Econometrica, 68, pp 1181-1230.
  7. Banerjee, S. (1999) "Efficiency and Stability in Economic Networks," mimeo: Boston University.
  8. Banerjee, S., Konishi, H. and Sönmez, T. (2001) "Core in a Simple Coalition Formation Game," Social Choice and Welfare, 18, 135-154.
  9. Belleflamme, P. and F. Bloch (2002) "Market Sharing Agreements and Stable Collusive Networks" mimeo: University of London and GREQAM.
  10. Bienenstock, E. and Bonacich, P. (1993) "Game Theory Models for Social Ex- change Networks: Experimental Results," Sociological Perspectives, 36, 117-136.
  11. Bienenstock, E. and Bonacich, P. (1997) "Network Exchange as a Cooperative Game," Rationality and Society, 9, 37-65.
  12. Billard, P. and Bravard, C. (2002) "Non-Cooperative Networks in Oligopolies," mimeo: University of Jean Monnet -Saint Etienne.
  13. Bloch, F. (2001) "Coalitions and Networks in Industrial Organization" mimeo: GREQAM.
  14. Boorman, S. (1975) "A Combinatorial Optimization Model for Transmission of Job Information through Contact Networks," Bell Journal of Economics, 6, 216- 249.
  15. Borm, P., Owen, G., and S. Tijs, S. (1992) "On the Position Value for Commu- nication Situations," SIAM Journal on Discrete Mathematics, 5, 305-320.
  16. Bramoullé, Y. (2000) "Congestion and Social Networks: an Evolutionary Analy- sis," mimeo: University of Maryland.
  17. Bramoullé, Y. (2001) "Complementarity and Social Networks," mimeo: THEMA, Université de Paris X-Nanterre.
  18. Bramoullé, Y. (2001a) "Interdependent Utilities, Preference Indeterminacy and Social Networks," mimeo: THEMA, Université de Paris X-Nanterre.
  19. Bramoullé, Y., D. Lopez-Pintado, S. Goyal, and F. Vega-Redondo (2002) "Net- work Formation and Anti-coordination games," mimeo: Universidad de Alicante.
  20. Bramoullé, Y. and R. Kranton (2003) "A Network Model of Public Goods: Exper- imentation and Social Learning," mimeo: University of Toulouse and University of Maryland.
  21. Brueckner, J.K. (2003) "Friendship Networks," mimeo: University of Illinois.
  22. Burt, R. (1992) Structural Holes: The Social Structure of Competition, Harvard University Press: Cambridge, MA.
  23. Cahuc, P. and F. Fontaine (2002) "On the Efficiency of Job Search with Social Networks," mimeo: University of Paris 1-EUREQua.
  24. Callander, S. and C. Plott (2001) " ," mimeo: Caltech.
  25. Calvo, E., J. Lasaga, and A. van den Nouweland (1999) "Values of Games with Probabilistic Graphs," Mathematical Social Sciences, 37, 79-95.
  26. Calvo-Armengol, A. (1999) "Stable and Efficient Bargaining Networks," mimeo. Calvo-Armengol, A. (2000) "Job Contact Networks," mimeo.
  27. Calvo-Armengol, A. (2001) "Bargaining Power in Communication Networks," Mathematical Social Sciences, 41, 69-88.
  28. Calvo-Armengol, A. and Jackson, M.O. (2001) "Social Networks in Determin- ing Employment: Patterns, Dynamics, and Inequality," forthcoming: American Economic Review, http://www.hss.caltech.edu/∼jacksonm/dynet.pdf
  29. Calvo-Armengol, A. and M.O. Jackson (2001b) "Networks in Labor Markets: Wage and Employment Dynamics and Inequality," mimeo: Caltech and Universi- tat Autònoma de Barcelona, http://www.hss.caltech.edu/∼jacksonm/dyngen.pdf , California Institute of Technology Working Paper # .
  30. Carayol, N. and P. Roux (2003) " 'Collective Innovation' in a Model of Network Formation with Preferential Meeting," mimeo: Université Louis Pasteur and Université de Toulouse I.
  31. Casella, A. and J. Rauch (2001) "Anonymous Market and Group Ties in Interna- tional Trade," mimeo: Columbia University and University of California at San Diego. Charness, G. and M. Corominas-Bosch, and G.R. Frechette (2001) "Bargaining on Networks: An Experiment," mimeo: University of California Santa Barbara.
  32. Chatterjee, K., B. Dutta, D. Ray, and S. Sengupta (1993) "A Noncooperative Theory of Coalitional Bargaining," Review of Economic Studies, 60, 463-477.
  33. Chwe, M. S.-Y. (1994) "Farsighted Coalitional Stability," Journal of Economic Theory, 63, pp 299-325.
  34. Corbae, D. and Duffy, J. (2000) "Experiments with Network Economies," mimeo: University of Pittsburgh.
  35. Corominas-Bosch, M. (1999) "On Two-Sided Network Markets," Ph.D. disserta- tion: Universitat Pompeu Fabra.
  36. Currarini, S. (2002) "Stable Organizations with Externalities," mimeo: Univer- sitá di Venezia.
  37. Currarini, S. and Morelli, M. (2000) "Network Formation with Sequential De- mands," Review of Economic Design, 5, 229-250.
  38. Conley, T.G., and G. Topa (2001) "Socio-Economic Distance and Spatial Patterns in Unemployment," mimeo: NYU.
  39. De Weerdt, J. (2002) "Risk-Sharing and Endogenous Network Formation," mimeo: K.U.Leuven.
  40. Demange, G. (2002) "On group stability in hierarchies and networks" mimeo: DELTA. Dero ïan, F. (2003) "Farsighted Strategies in the Formation of a Communication Network," Economics Letters, 80, 343-349.
  41. Droste, E., Gilles, R.P. and Johnson, C. (2000) "Evolution of Conventions in Endogenous Social Networks," mimeo: Virginia Tech.
  42. Dutta, B., S. Ghosal, and D. Ray (2003) "Farsighted Network Formation," mimeo: University of Warwick and NYU.
  43. Dutta, B., and Jackson, M.O. (2000) "The Stability and Efficiency of Directed Communication Networks," Review of Economic Design, 5, 251-272.
  44. Dutta, B., and Jackson, M.O. (2003) "On the Formation of Networks and Groups," in Networks and Groups: Models of Strategic Formation, edited by B. Dutta and M.O. Jackson, Springer-Verlag: Heidelberg.
  45. Dutta, B., and Jackson, M.O. (2003b) editors: Networks and Groups: Models of Strategic Formation, Springer-Verlag: Heidelberg.
  46. Dutta, B., and Mutuswami, S. (1997) "Stable Networks," Journal of Economic Theory, 76, 322-344.
  47. Dutta, B., van den Nouweland, A. and S. Tijs (1998) "Link Formation in Coop- erative Situations," International Journal of Game Theory, 27, 245-256.
  48. Ellison, G. (1993) "Learning, Local Interaction, and Coordination," Economet- rica, 61, 1047-1071.
  49. Ellison, G. and Fudenberg, D. (1995) "Word-of-Mouth Communication and Social Learning," The Quarterly Journal of Economics, 110, 93-126.
  50. Fafchamps, M. and Lund, S. (2000) "Risk-Sharing Networks in Rural Philip- pines," mimeo: Stanford University.
  51. Falk, A. and M. Kosfeld (2003) "It's All About Connections: Evidence on Net- work Formation," mimeo: University of Zurich.
  52. Feri, F. (2003) "Network Formation with Decay," Università Ca Foscari, Venezia.
  53. Freidlin, M. and A. Wentzell (1984) Random Perturbations of Dynamical Sys- tems, New York: Springer-Verlag, 161-211.
  54. Furusawa, T. and H. Konishi (2002) "Free Trade Networks," mimeo: Yokohama National University and Boston College.
  55. Galeotti, A. and S. Goyal (2002) "Network Formation with Heterogeneous Play- ers," mimeo: Erasmus University Rotterdam and University of London.
  56. Galeotti, A. and M.A. Meléndez-Jiménez (2003) "Strategic Multidimensionality and Social Interaction," mimeo: Erasmus University Rotterdam and University of Alicante.
  57. Gilles, R.P. and S. Sarangi (2003) "The Role of Trust in Costly Network Forma- tion," mimeo: Virginia Tech and Louisiana State University.
  58. Gilles, R.P. and S. Sarangi (2003b) "Rationalizing Trust in Network Formation," mimeo: Virginia Tech and Louisiana State University.
  59. Goyal, S. (1993) "Sustainable Communication Networks," Discussion Paper TI 93-250, Tinbergen Institute, Amsterdam-Rotterdam.
  60. Goyal, S. (2003) "Learning in Networks," forthcoming in Group Formation in Economics: Networks, Clubs, and Coalitions , edited by G. Demange and M. Wooders, Cambridge University Press: Cambridge.
  61. Goyal, S. and Joshi, S. (1999) "Bilateralism and Free Trade," mimeo: Tinbergen Econometric Institute report 176.
  62. Goyal, S. and Joshi, S. (2000) "Networks of Collaboration in Oligopoly," forth- coming: Games and Economic Behavior.
  63. Goyal, S. and Joshi, S. (2003) "Unequal Connections," mimeo: University of London and George Washington University.
  64. Goyal, S., Konovalov, A. and J.-L. Moraga (2003) "Hybrid R and D" mimeo. Goyal, S. and J.-L. Moraga (2001) "R and D Networks," Rand Journal of Eco- nomics, 32, 686-707.
  65. Goyal, S. and Vega-Redondo, F. (1999) "Learning, Network Formation and Co- ordination," mimeo: Erasmus University.
  66. Glaeser, E., Sacerdote, B. and Scheinkman, J. (1996) "Crime and Social Interac- tions," Quarterly Journal of Economics, 111, 507-548.
  67. Granovetter, M. (1973) "The Strength of Weak Ties," American Journal of So- ciology, 78, 1360-1380.
  68. Granovetter, M. [1974](1995) Getting a Job: A Study of Contacts and Careers, 2 nd edition, University of Chicago Press, Chicago.
  69. Haller, H. and Sarangi, S. (2001) "Nash Networks with Heterogeneous Agents," mimeo: Virginia Tech and LSU.
  70. Harrison, R. and R. Munoz (2002) "Stability and Equilibrium Selection in a Link Formation Game," mimeo: Georgetown University and the University of Maryland.
  71. Hendricks, K., Piccione, M. and Tan, G. (1995) "The Economics of Hubs: The Case of Monopoly," Review of Economic Studies, 62, 83-100.
  72. Holland, P.W. and S. Leinhardt (1977) "A Dynamic Model for Social Networks," Journal of Mathematical Sociology, 5, 5-20.
  73. Ioannides, Y.M. and L. Datcher Loury (2002) "Job Information Networks, Neigh- borhood Effects and Inequality," mimeo: Tufts University.
  74. Jackson, M.O. (2003). "The Stability and Efficiency of Economic and Social Networks," in Advances in Economic Design, edited by S. Koray and M. Sertel, Springer-Verlag: Heidelberg, and reprinted in Networks and Groups: Models of Strategic Formation, edited by B. Dutta and M.O. Jackson, Springer-Verlag: Heidelberg.
  75. Jackson, M.O. (2003b) "Allocation Rules for Network Games," mimeo: Caltech, http://www.hss.caltech.edu/∼jacksonm/allonet.pdf California Institute of Tech- nology Working Paper # .
  76. Jackson, M.O. and van den Nouweland, A. (2000) "Strongly Stable Networks," forthcoming: Games and Economic Behavior, http://www.hss.caltech.edu/∼jacksonm/coopnet.pd
  77. Jackson, M.O. and Watts, A. (2001) "The Existence of Pairwise Stable Net- works," Seoul Journal of Economics, vol. 14, no. 3, pp 299-321.
  78. Jackson, M.O. and Watts, A. (2002a) "The Evolution of Social and Economic Networks," Journal of Economic Theory, vol. 106, no. 2, pp 265-295.
  79. Jackson, M.O. and Watts, A. (2002b) "On the Formation of Interaction Networks in Social Coordination Games," Games and Economic Behavior, vol. 41, no. 2, pp 265-291.
  80. Jackson, M.O. and Wolinsky, A. (1996) "A Strategic Model of Social and Eco- nomic Networks," Journal of Economic Theory, 71, 44-74.
  81. Johnson, C. and Gilles, R.P. (2000) "Spatial Social Networks," Review of Eco- nomic Design, 5, 273-300.
  82. Kandori, M., G. Mailath, and R. Rob (1993) "Learning, Mutation, and Long Run Equilibria in Games, Econometrica, 61, 29-56.
  83. Katz, M. and Shapiro, C. (1994) "Systems Competition and Networks Effects," Journal of Economic Perspectives, 8, 93-115.
  84. Kirman, A. (1997) "The Economy as an Evolving Network," Journal of Evolu- tionary Economics, 7, 339-353.
  85. Kirman, A., Oddou, C. and Weber, S. (1986) "Stochastic Communication and Coalition Formation," Econometrica, 54, 129-138.
  86. Konishi, H. and M. Utku Ünver (2003) "Credible Group-Stability in General Multi-Partner Matching Problems," mimeo: Boston College and Koc University.
  87. Kosfeld, M. (2003) "Network Experiments," mimeo: University of Zurich.
  88. Kranton, R. and Minehart, D. (2002) "A Theory of Buyer-Seller Networks," American Economic Review, , .
  89. Kranton, R. and Minehart, D. (1996) "Link Patterns in Buyer-Seller Networks: Incentives and Allocations in Graphs," mimeo: University of Maryland and Boston University.
  90. Kranton, R. and Minehart, D. (2000) "Competition for Goods in Buyer-Seller Networks," Review of Economic Design, 5, 301-332.
  91. Lahari, S. (2003) "Stable Allocation Rules for Generalized Matching Problems," mimeo. Liebowitz, S. and Margolis, S. (1994) "Network Externality: An Uncommon Tragedy," Journal of Economic Perspectives, 8, 133-150.
  92. Lippert, S. and G. Spagnolo (2003) "Networks of Relations," mimeo: University of Mannheim.
  93. Marsali, M., F. Vega-Redondo, and F. Slanina (2003) "The Rise and Fall of a Networked Society," mimeo.
  94. Mairesse, J. and L. Turner (2001) "Measurement and Explanation of the Intensity of Co-publication in Scientific Research: An Analysis at the Laboratory Level," EUREQua working paper 2001.53.
  95. McBride, M. (2002) "Position-Specific Information in Social Networks," mimeo: University of California at Irvine.
  96. Meessen, R. (1988) "Communication games," Master's thesis, Department of Mathematics, University of Nijmegen.
  97. Monsuur, H. (2002) "Centrality and Network Dynamics," mimeo: Royal Nether- lands Naval Academy.
  98. Moreno-Ternero, J.D. (2000) "Notes About a Strategic Model of Social and Eco- nomic Networks," Universidad de Alicante.
  99. Montgomery, J. (1991) "Social Networks and Labor Market Outcomes," The American Economic Review, 81, 1408-1418.
  100. Montgomery, J. (1992) "Job Search and Network Composition: Implications of the Strength-of-Weak-Ties Hypothesis," American Sociological Review, 57, 586- 596. Montgomery, J. (1994) "Weak Ties, Employment, and Inequality: An Equilib- rium Analysis," American Journal of Sociology, 99, 1212-1236.
  101. Mutuswami, S. and Winter, E. (2002) "Subscription Mechanisms for Network Formation," Journal of Economic Theory, 106, 242-264.
  102. Myerson, R (1977) "Graphs and Cooperation in Games," Math. Operations Research, 2, 225-229.
  103. Myerson, R. (1991) Game Theory: Analysis of Conflict, Harvard University Press: Cambridge, MA.
  104. Navarro, N. (2002) "Fair Allocation in Evolving Networks," mimeo: Universidad Carlos III de Madrid.
  105. Navarro, N. and A. Perea (2001) "Bargaining in Networks and the Myerson Value," mimeo: Universidad Carlos III de Madrid.
  106. Nieva, R. (2002) "An Extension of the Aumann-Myerson Solution for Reasonable Empty-Core Games," mimeo: Rochester Institute of Technology.
  107. Qin, C.-Z. (1996) "Endogenous Formation of Cooperation Structures," Journal of Economic Theory, 69, 218-226.
  108. Page, F. (2003) "Farsighted Stability in Network formation," forthcoming in Group Formation in Economics: Networks, Clubs, and Coalitions, edited by G. Demange and M. Wooders, Cambridge University Press: Cambridge.
  109. Page, F. and M. Wooders, and S. Kamat (2001) "Networks and Farsighted Sta- bility" DP University of Warwick.
  110. Pantz, K. and A. Ziegelmeyer (2003) "An Experimental Study of Network For- mation," mimeo: Max Planck Institute.
  111. Polanski, A. (2003) "Bilateral Bargaining in Networks," mimeo: Universidad de Alicante.
  112. Rees, A. (1966) "Information Networks in Labor Markets," American Economic Review, 56, 559-566.
  113. Roth, A. and Sotomayor, M. (1989) Two Sided Matching, Econometric Society Monographs No. 18: Cambridge University Press.
  114. Santamaria-Garcia, J. (2003) "Gathering Information through Social Contacts: An Empirical Analysis of Labor Market Outcomes," mimeo: European University Institute.
  115. Sarangi, S., R. Kannan, and L. Ray (2003) "The Structure of Information Net- works," mimeo: Louisiana State University.
  116. Skyrms, B. and Pemantle, R. (2000) "A Dynamic Model of Social Network For- mation," Proceedings of the National Academy of Sciences, 97, 9340-9346.
  117. Slikker, M. (2000) Decision Making and Cooperation Structures CentER Disser- tation Series: Tilburg.
  118. Slikker, M., Gilles, R.P., Norde, H. and Tijs, S. (2001) "Directed Networks," Allocation Properties and Hierarchy Formation. mimeo.
  119. Slikker, M. and van den Nouweland, A. (2000) "Network Formation Models with Costs for Establishing Links," Review of Economic Design, 5, 333-362.
  120. Slikker, M. and van den Nouweland, A. (2001) Social and Economic Networks in Cooperative Game Theory, Kluwer.
  121. Slikker, M. and van den Nouweland, A. (2001b) "A One-Stage Model of Link Formation and Payoff Division," Games and Economic Behavior, 34, 153-175.
  122. Starr, R.M. and Stinchcombe, M.B. (1992) "Efficient Transportation Routing and Natural Monopoly in the Airline Industry: An Economic Analysis of Hub-Spoke and Related Systems," UCSD dp 92-25.
  123. Starr, R.M. and Stinchcombe, M.B. (1999) "Exchange in a Network of Trad- ing Posts," in Markets, Information and Uncertainty, edited by G. Chichilnisky, Cambridge University Press.
  124. Stole, L. and J. Zweibel (1996) "Intra-Firm Bargaining under Non-Binding Con- straints," Review of Economic Studies, 63, 375-410.
  125. Tassier, T. (2002) "A Markov Model of Referral Based Hiring and Workplace Segregation," mimeo: University of Iowa.
  126. Tassier, T. and F. Menczer (2002) "Social Network Structure, Equality and Seg- regation in a Labor Market with Referral Hiring," mimeo: University of Iowa.
  127. Tesfatsion, L. (1997) "A Trade Network Game with Endogenous Partner Selec- tion," in Computational Approaches to Economic Problems, H. Amman et al (eds.), Kluwer Academic Publishers, 249-269.
  128. Tesfatsion, L. (1998) "Gale-Shapley matching in an Evolutionary Trade Network Game," Iowa State University Economic Report no. 43.
  129. Topa, G. (2001) "Social Interactions, Local Spillovers and Unemployment," Re- view of Economic Studies, 68, 261-296.
  130. van den Nouweland, A. (2003) "Static Networks and Coalition Formation," . forthcoming in Group Formation in Economics: Networks, Clubs, and Coalitions, edited by G. Demange and M. Wooders, Cambridge University Press: Cambridge.
  131. Vega-Redondo, F. (2002) "Building Up Social Capital in a Changing World," mimeo: Universidad de Alicante.
  132. Wang, P. and A. Watts (2002) "Formation of Buyer-Seller Trade Networks in a Quality-Differentiated Product Market," mimeo: Penn State University and Southern Illinois University.
  133. Wang, P. and Wen, Q. (1998) "Network Bargaining," mimeo: Penn State Uni- versity.
  134. Wasserman, S. and Faust, K. (1994) Social Network Analysis: Methods and Applications, Cambridge University Press.
  135. Watts, A. (2002) "A Note on Non-Myopic Network Formation," Economics Let- ters.
  136. Watts, A. (2001) "A Dynamic Model of Network Formation," Games and Eco- nomic Behavior, 34, pp 331-341.
  137. Watts, D.J. (1999) Small Worlds: The Dynamics of Networks between Order and Randomness, Princeton University Press.
  138. Weisbuch, G., Kirman, A. and Herreiner, D. (2000) "Market Organization," Eco- nomica, 110, pp 411-436.
  139. Yoon, K. "Resale of Information and Stability of Networks," mimeo: Korea Uni- versity.

Related papers

``A Survey of Models of Network Formation: Stability and Efficiency,''
Matthew O. Jackson

I survey the recent literature on the formation of networks. I provide definitions of network games, a number of examples of models from the literature, and discuss some of what is known about the (in)compatibility of overall societal welfare with individual incentives to form and sever links. JEL Classification Numbers: A14, C71, C72

View PDFchevron_right
A Noncooperative Model of Network Formation
Venkatesh bala

Econometrica, 2000

We present an approach to network formation based on the notion that social networks are formed by individual decisions that trade off the costs of forming and maintaining links against the potential rewards from doing so. We suppose that a link with another agent allows access, in part and in due course, to the benefits available to the latter via his own links. Thus individual links generate externalities whose value depends on the level of decayrdelay associated with indirect links. A distinctive aspect of our approach is that the costs of link formation are incurred only by the person who initiates the link. This allows us to formulate the network formation process as a noncooperative game. We first provide a characterization of the architecture of equilibrium networks. We then study the dynamics of network formation. We find that individual efforts to access benefits offered by others lead, rapidly, to the emergence of an equilibrium social network, under a variety of circumstances. The limiting networks have simple architectures, e.g., the wheel, the star, or generalizations of these networks. In many cases, such networks are also socially efficient.

View PDFchevron_right
A game-theoretic network formation model
Omid Atabati

2014

We study the dynamics of a game-theoretic network formation model that yields large-scale small-world networks. So far, mostly stochastic frameworks have been utilized to explain the emergence of these networks. On the other hand, it is natural to seek for game-theoretic network formation models in which links are formed due to strategic behaviors of individuals, rather than based on probabilities. Inspired by Even-Dar and Kearns (2007), we consider a more realistic model in which the cost of establishing each link is dynamically determined during the course of the game. Moreover, players are allowed to put transfer payments on the formation of links. Also, they must pay a maintenance cost to sustain their direct links during the game. We show that there is a small diameter of at most 4 in the general set of equilibrium networks in our model. Unlike earlier model, not only the existence of equilibrium networks is guaranteed in our model, but also these networks coincide with the outcomes of pairwise Nash equilibrium in network formation. Furthermore, we provide a network formation simulation that generates small-world networks. We also analyze the impact of locating players in a hierarchical structure by constructing a strategic model, where a complete b-ary tree is the seed network.

View PDFchevron_right
A strategic model for network formation
Omid Atabati

Journal of Computational Social Networks, 2015

We study the dynamics of a game-theoretic network formation model that yields large-scale small-world networks. So far, mostly stochastic frameworks have been utilized to explain the emergence of these networks. On the other hand, it is natural to seek for game-theoretic network formation models in which links are formed due to strategic behaviors of individuals, rather than based on probabilities. Inspired by Even-Dar and Kearns’ model [8], we consider a more realistic framework in which the cost of establishing each link is dynamically determined during the course of the game. Moreover, players are allowed to put transfer payments on the formation and maintenance of links. Also, they must pay a maintenance cost to sustain their direct links during the game. We show that there is a small diameter of at most 4 in the general set of equilibrium networks in our model. We achieved an economic mechanism and its dynamic process for individuals which firstly; unlike the earlier model, the outcomes of players’ interactions or the equilibrium networks are guaranteed to exist. Furthermore, these networks coincide with the outcome of pairwise Nash equilibrium in network formation. Secondly; it generates large-scale networks that have a rational and strategic microfoundation and demonstrate the main characterization of small degree of separation in real-life social networks. Furthermore, we provide a network formation simulation that generates small-world networks.

View PDFchevron_right
Definitions of equilibrium in network formation games
Matthew O. Jackson

International Journal of Game Theory, 2006

We examine a variety of stability and equilibrium de…nitions that have been used to study the formation of social networks among a group of players. In particular we compare variations on three types of de…nitions: those based on a pairwise stability notion, those based on the Nash equilibria of a link formation game, and those based on equilibria of a link formation game where transfers are possible. JEL Classi…cation Numbers: A14, C71, C72

View PDFchevron_right

Related topics

  • Computer Science

    • Cited by

    Risk-sharing networks and farsighted stability
    Gilles Grandjean

    Review of Economic Design, 2013

    Evidence suggests that in developing countries, agents rely on mutual insurance agreements to deal with income or expenditure shocks. This paper analyzes which risk-sharing networks can be sustained in the long run when individuals are far-sighted, in the sense that they are able to forecast how other agents would react to their choice of insurance partners. In particular, we study whether the farsightedness of the agents leads to a reduction of the tension between stability and efficiency that arises when individuals are myopic. We find that for extreme values of the cost of establishing a mutual insurance agreement, myopic and farsighted agents form the same risk-sharing networks. For intermediate costs, farsighted agents form efficient networks while myopic agents don't.

    View PDFchevron_right
    Network Formation and Routing by Strategic Agents Using Local Contracts
    Elliot Anshelevich

    Lecture Notes in Computer Science, 2008

    In the Internet, Autonomous Systems (ASes) make contracts called Service Level Agreements (SLAs) between each other to transit one another's traffic. ASes also try to control the routing of traffic to and from their networks in order to achieve efficient use of their infrastructure and to attempt to meet some level of quality of service globally. We introduce a game theoretic model in order to gain understanding of this interplay between network formation and routing. Player strategies allow them to make contracts with one another to forward traffic, and to re-route traffic that is currently routed through them. This model extends earlier work of [3] that only considered the network formation aspect of the problem. We study the structure and quality of Nash equilibria and quantify the prices of anarchy and stability, that is, the relative quality of a centralized optimal solution versus that of the Nash equilibria.

    View PDFchevron_right
    A Game-Theoretical Network Formation Model for C. elegans Neural Network
    mohamad khajezade

    Frontiers in Computational Neuroscience

    Studying and understanding human brain structures and functions have become one of the most challenging issues in neuroscience today. However, the mammalian nervous system is made up of hundreds of millions of neurons and billions of synapses. This complexity made it impossible to reconstruct such a huge nervous system in the laboratory. So, most researchers focus on C. elegans neural network. The C. elegans neural network is the only biological neural network that is fully mapped. This nervous system is the simplest neural network that exists. However, many fundamental behaviors like movement emerge from this basic network. These features made C. elegans a convenient case to study the nervous systems. Many studies try to propose a network formation model for C. elegans neural network. However, these studies could not meet all characteristics of C. elegans neural network, such as significant factors that play a role in the formation of C. elegans neural network. Thus, new models are needed to be proposed in order to explain all aspects of C. elegans neural network. In this paper, a new model based on game theory is proposed in order to understand the factors affecting the formation of nervous systems, which meet the C. elegans frontal neural network characteristics. In this model, neurons are considered to be agents. The strategy for each neuron includes either making or removing links to other neurons. After choosing the basic network, the utility function is built using structural and functional factors. In order to find the coefficients for each of these factors, linear programming is used. Finally, the output network is compared with C. elegans frontal neural network and previous models. The results implicate that the game-theoretical model proposed in this paper can better predict the influencing factors in the formation of C. elegans neural network compared to previous models.

    View PDFchevron_right
    MSP-N: Multiple selection procedure with ‘N’ possible growth mechanisms
    Pradumn Pandey

    PLOS ONE

    Network modeling is a challenging task due to non-trivial evolution dynamics. We introduce multiple-selection-procedure with 'N' possible growth mechanisms (MSP-N). In MSP-N, an incoming node chooses a single option among N available options to link to pre-existing nodes. Some of the potential options, in case of social networks, can be standard preferential or random attachment and node aging or fitness. In this paper, we discuss a specific case, MSP-2, and shows its efficacy in reconstructing several non-trivial characteristic properties of social networks, including networks with power-law degree distribution, power-law with an exponential decay (exponential cutoff), and exponential degree distributions. We evaluate the proposed evolution mechanism over two real-world networks and observe that the generated networks highly resembles the degree distribution of the real-world networks. Besides, several other network properties such as high clustering and triangle count, low spectral radius, and community structure, of the generated networks are significantly closer to the real-world networks.

    View PDFchevron_right
    The Problem of Intransigently Biased Agents
    Justin Bruner

    Philosophy of Science, 2015

    View PDFchevron_right
    580 California St., Suite 400
    San Francisco, CA, 94104
    © 2025 Academia. All rights reserved