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A Dynamic Model of Presidential Nomination Campaigns

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  • Aldrich, John H.

Abstract

Recent campaigns have demonstrated the importance of dynamic elements in affecting the selection of presidential nominees. This paper develops a mathematical model to analyze these dynamics. The heart of the model is the assumed relationship between the ability to acquire resources and success in primaries and caucuses. The expenditure of resources leads to greater electoral success, while greater electoral success (in particular, exceeding expectations in a primary or caucus) leads to greater resource-gathering capabilities. A difference equation model of these relationships is proposed. I prove that any campaign of this form is necessarily unstable, which implies that most candidates will be “winnowed out” necessarily, while only a very few, but at least one candidate, will necessarily “have momentum.” This result is true whether there are two or many contenders. However, I also argue that the larger the number of candidates, the stronger the dynamic forces, and thus the more rapid the “winnowing out” process.

Suggested Citation

  • Aldrich, John H., 1980. "A Dynamic Model of Presidential Nomination Campaigns," American Political Science Review, Cambridge University Press, vol. 74(3), pages 651-669, September.
    • Handle: RePEc:cup:apsrev:v:74:y:1980:i:03:p:651-669_16
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    Cited by:

    1. Jay Goodliffe, 2005. "When Do War Chests Deter?," Journal of Theoretical Politics, , vol. 17(2), pages 249-277, April.
    2. Battaglini, Marco, 2005. "Sequential voting with abstention," Games and Economic Behavior, Elsevier, vol. 51(2), pages 445-463, May.
    3. Hummel, Patrick, 2012. "Sequential voting in large elections with multiple candidates," Journal of Public Economics, Elsevier, vol. 96(3), pages 341-348.
    4. Hummel, Patrick & Holden, Richard, 2014. "Optimal primaries," Journal of Public Economics, Elsevier, vol. 109(C), pages 64-75.
    5. Dan Kovenock & Brian Roberson, 2009. "Is the 50-State Strategy Optimal?," Journal of Theoretical Politics, , vol. 21(2), pages 213-236, April.
    6. Kovenock, Dan & Konrad, Kai A., 2006. "Multi-Stage Contests with Stochastic Ability," CEPR Discussion Papers 5844, C.E.P.R. Discussion Papers.
    7. Kai A. Konrad & Dan Kovenock, 2010. "Contests With Stochastic Abilities," Economic Inquiry, Western Economic Association International, vol. 48(1), pages 89-103, January.
    8. Meredith, Marc & Malhotra, Neil, 2008. "Can October Surprise? A Natural Experiment Assessing Late Campaign Effects," Research Papers 2002, Stanford University, Graduate School of Business.
    9. M. Roth, 2011. "Resource allocation and voter calculus in a multicandidate election," Public Choice, Springer, vol. 148(3), pages 337-351, September.
    10. Patrick Hummel & Brian Knight, 2015. "Sequential Or Simultaneous Elections? A Welfare Analysis," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(3), pages 851-887, August.
    11. Rainer Schwabe, 2015. "Super Tuesday: campaign finance and the dynamics of sequential elections," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 44(4), pages 927-951, April.
    12. Adam Meirowitz, 2005. "Informational Party Primaries and Strategic Ambiguity," Journal of Theoretical Politics, , vol. 17(1), pages 107-136, January.
    13. de Roos, Nicolas & Sarafidis, Yianis, 2018. "Momentum in dynamic contests," Economic Modelling, Elsevier, vol. 70(C), pages 401-416.
    14. Steger, Wayne P., 2008. "Forecasting the presidential primary vote: Viability, ideology and momentum," International Journal of Forecasting, Elsevier, vol. 24(2), pages 193-208.

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