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A decision making model: Its structure and form

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  • Bruce Bueno de Mesquita

Abstract

I explain the logic and real‐time track record of the expected utility model used for forecasting the outcome and dynamics of political choices. The model represents an example of applied modeling. It is a tool designed for practical application. As such, some sacrifices in theoretical or analytic purity are made to gain empirical leverage. At the same time, the model remains faithful to the rational choice perspective that suggests that decision makers do what they believe is in their best interest. Decision makers are modeled as individuals with bounded rationality, who are not able to look ahead over an unbounded time horizon, but instead see only one move ahead of their current choice. Furthermore, while they update information, they do so crudely. I also attempt to explain limitations of the model and areas for further improvement.

Suggested Citation

  • Bruce Bueno de Mesquita, 1997. "A decision making model: Its structure and form," International Interactions, Taylor & Francis Journals, vol. 23(3-4), pages 235-266, May.
    • Handle: RePEc:taf:ginixx:v:23:y:1997:i:3-4:p:235-266
    DOI: 10.1080/03050629708434909
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    References listed on IDEAS

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    1. de Mesquita, Bruce Bueno, 1990. "Multilateral negotiations: a spatial analysis of the Arab–Israeli dispute," International Organization, Cambridge University Press, vol. 44(3), pages 317-340, July.
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    Cited by:

    1. Brian Efird & Ambassador Peter Galbraith & Jacek Kugler & Mark Abdollahian, 2000. "Negotiating peace in Kosovo," International Interactions, Taylor & Francis Journals, vol. 26(2), pages 153-178, March.
    2. Patrick T. Brandt & Michael Colaresi & John R. Freeman, 2008. "The Dynamics of Reciprocity, Accountability, and Credibility," Journal of Conflict Resolution, Peace Science Society (International), vol. 52(3), pages 343-374, June.
    3. Mark Abdollahian & Carole Alsharabati, 2003. "Modeling the Strategic Effects of Risk and Perceptions in Linkage Politics," Rationality and Society, , vol. 15(1), pages 113-135, February.
    4. Patrick T. Brandt & John R. Freeman & Philip A. Schrodt, 2011. "Real Time, Time Series Forecasting of Inter- and Intra-State Political Conflict," Conflict Management and Peace Science, Peace Science Society (International), vol. 28(1), pages 41-64, February.
    5. Ellen Lust-Okar & A.F.K. Organski, 2002. "Coalitions and Conflict: the Case of the Palestinian-Israeli Negotiations Over the West Bank," Conflict Management and Peace Science, Peace Science Society (International), vol. 19(2), pages 23-58, September.
    6. Michael Macgregor Perry & Hadi El-Amine, 2021. "Computational Efficiency in Multivariate Adversarial Risk Analysis Models," Papers 2110.12572, arXiv.org.
    7. Jacek Kugler & Yi Feng, 1999. "Explaining and Modeling Democratic Transitions," Journal of Conflict Resolution, Peace Science Society (International), vol. 43(2), pages 139-146, April.
    8. Michael Perry & Hadi El-Amine, 2019. "Computational Efficiency in Multivariate Adversarial Risk Analysis Models," Decision Analysis, INFORMS, vol. 16(4), pages 314-332, December.
    9. Bruce Bueno de Mesquita, 2011. "A New Model for Predicting Policy Choices," Conflict Management and Peace Science, Peace Science Society (International), vol. 28(1), pages 65-87, February.
    10. Jason B Scholz & Gregory J Calbert & Glen A Smith, 2011. "Unravelling Bueno De Mesquita’s group decision model," Journal of Theoretical Politics, , vol. 23(4), pages 510-531, October.
    11. Lewis W. Snider & Jason E. Strakes, 2006. "Modeling Middle East Security: A Formal Assessment of Regional Responses to the Iraq War," Conflict Management and Peace Science, Peace Science Society (International), vol. 23(3), pages 211-226, July.

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