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Prospect Theory and Coercive Bargaining

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  • Christopher K. Butler

    (Department of Political Science, University of New Mexico, Albuquerque)

Abstract

Despite many applications of prospect theory's concepts to explain political and strategic phenomena, formal analyses of strategic problems using prospect theory are rare. Using Fearon's model of bargaining, Tversky and Kahneman's value function, and an existing probability weighting function, I construct a model that demonstrates the differences between expected value and prospect theory when applied to strategic interaction. Critically important to this demonstration is an examination of different types of reference points that make sense for bargaining problems. Four types of reference points are discussed and analyzed: power-based, equity, variants of the status quo, and extreme ``I-want-it-all'' reference points. Each of these types of reference points produce different bargaining behavior at the individual level and in combination with the type of reference point of the other actor. Additionally, I demonstrate that bargaining failure is possible for this model under complete and perfect information using prospect-theoretic logic.

Suggested Citation

  • Christopher K. Butler, 2007. "Prospect Theory and Coercive Bargaining," Journal of Conflict Resolution, Peace Science Society (International), vol. 51(2), pages 227-250, April.
    • Handle: RePEc:sae:jocore:v:51:y:2007:i:2:p:227-250
    DOI: 10.1177/0022002706297703
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    References listed on IDEAS

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    1. Slantchev, Branislav L., 2003. "The Power to Hurt: Costly Conflict with Completely Informed States," American Political Science Review, Cambridge University Press, vol. 97(1), pages 123-133, February.
    2. Fearon, James D., 1995. "Rationalist explanations for war," International Organization, Cambridge University Press, vol. 49(3), pages 379-414, July.
    3. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    4. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    5. Carlson Lisa J. & Dacey Raymond, 2004. "Sequential Decision Analysis of the Traditional Deterrence Game," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 10(3), pages 1-16, December.
    6. Jonathan Shalev, 2000. "Loss aversion equilibrium," International Journal of Game Theory, Springer;Game Theory Society, vol. 29(2), pages 269-287.
    7. Powell, Robert, 2004. "The Inefficient Use of Power: Costly Conflict with Complete Information," American Political Science Review, Cambridge University Press, vol. 98(2), pages 231-241, May.
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    Cited by:

    1. Bram Driesen & Andrés Perea & Hans Peters, 2010. "On Loss Aversion in Bimatrix Games," Theory and Decision, Springer, vol. 68(4), pages 367-391, April.
    2. Hota, Ashish R. & Garg, Siddharth & Sundaram, Shreyas, 2016. "Fragility of the commons under prospect-theoretic risk attitudes," Games and Economic Behavior, Elsevier, vol. 98(C), pages 135-164.
    3. Carlson Lisa J & Dacey Raymond, 2008. "The Sensitivity of Critical Risk Values to Small Changes in the Value of the Status Quo," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 13(2), pages 89-110, January.
    4. Peter J. Phillips & Gabriela Pohl, 2017. "Terrorist choice: a stochastic dominance and prospect theory analysis," Defence and Peace Economics, Taylor & Francis Journals, vol. 28(2), pages 150-164, March.
    5. Christopher K. Butler & Scott Gates, 2010. "The Technology of Terror: Accounting for the Strategic Use of Terrorism," Economics of Security Working Paper Series 30, DIW Berlin, German Institute for Economic Research.

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