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Structure and Uncertainty in Discrete Choice Models

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  • Signorino, Curtis S.

Abstract

Social scientists are often confronted with theories in which one or more actors make choices over a discrete set of options. In this article, I generalize a broad class of statistical discrete choice models, with both well-known and new nonstrategic and strategic special cases. I demonstrate how to derive statistical models from theoretical discrete choice models and, in doing so, I address the statistical implications of three sources of uncertainty: agent error, private information about payoffs, and regressor error. For strategic and some nonstrategic choice models, the three types of uncertainty produce different statistical models. In these cases, misspecifying the type of uncertainty leads to biased and inconsistent estimates, and to incorrect inferences based on estimated probabilities.

Suggested Citation

  • Signorino, Curtis S., 2003. "Structure and Uncertainty in Discrete Choice Models," Political Analysis, Cambridge University Press, vol. 11(4), pages 316-344.
    • Handle: RePEc:cup:polals:v:11:y:2003:i:04:p:316-344_01
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    Cited by:

    1. Taehee Whang & Hannah June Kim, 2015. "International Signaling and Economic Sanctions," International Interactions, Taylor & Francis Journals, vol. 41(3), pages 427-452, May.
    2. Thomas T. Holyoke, 2009. "Interest Group Competition and Coalition Formation," American Journal of Political Science, John Wiley & Sons, vol. 53(2), pages 360-375, April.
    3. Lindenschmidt, Karl-Erich & Fleischbein, Katrin & Baborowski, Martina, 2007. "Structural uncertainty in a river water quality modelling system," Ecological Modelling, Elsevier, vol. 204(3), pages 289-300.
    4. Golman, Russell, 2012. "Homogeneity bias in models of discrete choice with bounded rationality," Journal of Economic Behavior & Organization, Elsevier, vol. 82(1), pages 1-11.
    5. Enzo Lenine, 2020. "Modelling Coalitions: From Concept Formation to Tailoring Empirical Explanations," Games, MDPI, vol. 11(4), pages 1-12, November.
    6. Enzo Lenine, 2020. "The pulse-like nature of decisions in rational choice theory," Rationality and Society, , vol. 32(4), pages 485-508, November.
    7. Hou, Linke & Lv, Yuxia & Geng, Hao & Li, Feiyue, 2019. "To tell the truth or the perceived truth: Structural estimation of peer effects in China’s macroeconomic forecast," Economic Systems, Elsevier, vol. 43(2), pages 1-1.
    8. Kristian Skrede Gleditsch & Simon Hug & Livia Isabella Schubiger & Julian Wucherpfennig, 2011. "International Conventions and Non-State Actors: Selection, Signaling, and Reputation Effects," HiCN Working Papers 108, Households in Conflict Network.
    9. Muhammet A. Bas, 2012. "Measuring Uncertainty in International Relations: Heteroskedastic Strategic Models," Conflict Management and Peace Science, Peace Science Society (International), vol. 29(5), pages 490-520, November.
    10. B Glumac & Q Han & W Schaefer, 2018. "A negotiation decision model for public–private partnerships in brownfield redevelopment," Environment and Planning B, , vol. 45(1), pages 145-160, January.
    11. Shawna K. Metzger, 2017. "Time is on my side? The impact of timing and dispute type on militarized conflict duration," Conflict Management and Peace Science, Peace Science Society (International), vol. 34(3), pages 308-329, May.
    12. Michael Chwe, 2006. "Statistical Game Theory," Theory workshop papers 815595000000000004, UCLA Department of Economics.
    13. Kevin A. Clarke & Curtis S. Signorino, 2010. "Discriminating Methods: Tests for Non‐nested Discrete Choice Models," Political Studies, Political Studies Association, vol. 58(2), pages 368-388, March.

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