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Strategic Interaction and Networks

  • Yann Bramoullé
  • Rachel Kranton
  • Martin D'Amours

This paper brings a general network analysis to a wide class of economic games. A network, or interaction matrix, tells who directly interacts with whom. A major challenge is determining how network structure shapes overall outcomes. We have a striking result. Equilibrium conditions depend on a single number: the lowest eigenvalue of a network matrix. Combining tools from potential games, optimization, and spectral graph theory, we study games with linear best replies and characterize the Nash and stable equilibria for any graph and for any impact of players’ actions. When the graph is sufficiently absorptive (as measured by this eigenvalue), there is a unique equilibrium. When it is less absorptive, stable equilibria always involve extreme play where some agents take no actions at all. This paper is the first to show the importance of this measure to social and economic outcomes, and we relate it to different network link patterns.

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Paper provided by CIRPEE in its series Cahiers de recherche with number 1018.

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Date of creation: 2010
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Handle: RePEc:lvl:lacicr:1018
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  1. Nicholas Bloom & Mark Schankerman & John Van Reenen, 2013. "Identifying Technology Spillovers and Product Market Rivalry," Econometrica, Econometric Society, vol. 81(4), pages 1347-1393, 07.
  2. Timothy G. Conley & Christopher R. Udry, 2005. "Learning about a new technology: pineapple in Ghana," Proceedings, Federal Reserve Bank of San Francisco.
  3. Yann Bramoull? & Rachel Kranton & Martin D'Amours, 2014. "Strategic Interaction and Networks," American Economic Review, American Economic Association, vol. 104(3), pages 898-930, March.
  4. Francis Bloch & Unal Zenginobuz, 2007. "The effect of spillovers on the provision of local public goods," Review of Economic Design, Springer, vol. 11(3), pages 199-216, November.
  5. David Card & Laura Giuliano, 2013. "Peer Effects and Multiple Equilibria in the Risky Behavior of Friends," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1130-1149, October.
  6. Esther Duflo & Emmanuel Saez, 2000. "Participation and Investment Decisions in a Retirement Plan: The Influence of Colleagues' Choices," NBER Working Papers 7735, National Bureau of Economic Research, Inc.
  7. Rauch, J E & Casella, Alessandra, 2001. "Overcoming Informational Barriers to International Resource Allocation: Prices and Ties," University of California at San Diego, Economics Working Paper Series qt2k8626fr, Department of Economics, UC San Diego.
  8. Manski, C.F., 1991. "Identification of Endogenous Social Effects: the Reflection Problem," Working papers 9127, Wisconsin Madison - Social Systems.
  9. Gary S. Becker, 1974. "Crime and Punishment: An Economic Approach," NBER Chapters, in: Essays in the Economics of Crime and Punishment, pages 1-54 National Bureau of Economic Research, Inc.
  10. Patrick Bayer & Randi Hjalmarsson & David Pozen, 2007. "Building Criminal Capital behind Bars: Peer Effects in Juvenile Corrections," NBER Working Papers 12932, National Bureau of Economic Research, Inc.
  11. Mohamed Belhaj & Yann Bramoullé & Frédéric Deroian, 2012. "Network Games under Strategic Complementarities," AMSE Working Papers 1225, Aix-Marseille School of Economics, Marseille, France.
  12. Daiji Kawaguchi, 2004. "Peer effects on substance use among American teenagers," Journal of Population Economics, Springer, vol. 17(2), pages 351-367, 06.
  13. Jaffe, A.B. & Trajtenberg, M., 1992. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," Papers 14-92, Tel Aviv.
  14. Trogdon, Justin G. & Nonnemaker, James & Pais, Joanne, 2008. "Peer effects in adolescent overweight," Journal of Health Economics, Elsevier, vol. 27(5), pages 1388-1399, September.
  15. James D. Adams, 2001. "Comparative Localization of Academic and Industrial Spillovers," NBER Working Papers 8292, National Bureau of Economic Research, Inc.
  16. Peter Kooreman & Adriaan R. Soetevent, 2007. "A discrete-choice model with social interactions: with an application to high school teen behavior," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 599-624.
  17. Alejandro Gaviria & Steven Raphael, 2001. "School-Based Peer Effects And Juvenile Behavior," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 257-268, May.
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