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Momentum and Social Learning in Presidential Primaries

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  • Brian Knight
  • Nathan Schiff

Abstract

This paper provides an investigation of the role of momentum and social learning in sequential voting systems. In the econometric model, voters are uncertain over candidate quality, and voters in late states attempt to infer the information held by those in early states from voting returns. Candidates experience momentum effects when their performance in early states exceeds expectations. The empirical application focuses on the responses of daily polling data to the release of voting returns in the 2004 presidential primary. We find that Kerry benefited from surprising wins in early states and took votes away from Dean, who held a strong lead prior to the beginning of the primary season. The voting weights implied by the estimated model demonstrate that early voters have up to 20 times the influence of late voters in the selection of candidates, demonstrating a significant departure from the ideal of "one person, one vote." We then address several alternative, non-learning explanations for our results. Finally, we run simulations under different electoral structures and find that a simultaneous election would have been more competitive due to the absence of herding and that alternative sequential structures would have yielded different outcomes.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 13637.

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Date of creation: Nov 2007
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Publication status: published as Brian Knight & Nathan Schiff, 2010. "Momentum and Social Learning in Presidential Primaries," Journal of Political Economy, University of Chicago Press, vol. 118(6), pages 1110 - 1150.
Handle: RePEc:nbr:nberwo:13637

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  1. Steven Callander, 2007. "Bandwagons and Momentum in Sequential Voting," Review of Economic Studies, Oxford University Press, vol. 74(3), pages 653-684.
  2. Strumpf, Koleman S, 2002. " Strategic Competition in Sequential Election Contests," Public Choice, Springer, vol. 111(3-4), pages 377-97, June.
  3. Nageeb Ali & Navin Kartik, 2006. "A Theory of Momentum in Sequential Voting," NajEcon Working Paper Reviews 321307000000000016, www.najecon.org.
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  6. Mark Rosenzweig & Andrew D. Foster, . "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Home Pages _068, University of Pennsylvania.
  7. Banerjee, Abhijit V, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 107(3), pages 797-817, August.
  8. Wolfers, Justin & Zitzewitz, Eric, 2004. "Prediction Markets," Research Papers 1854, Stanford University, Graduate School of Business.
  9. Hongbin Cai & Yuyu Chen & Hanming Fang, 2007. "Observational Learning: Evidence from a Randomized Natural Field Experiment," NBER Working Papers 13516, National Bureau of Economic Research, Inc.
  10. Battaglini, Marco, 2004. "Sequential Voting with Abstention," Papers 05-19-2004, Princeton University, Research Program in Political Economy.
  11. Timothy Feddersen & Wolfgang Pesendorfer, 1997. "Voting Behavior and Information Aggregation in Elections with Private Information," Econometrica, Econometric Society, Econometric Society, vol. 65(5), pages 1029-1058, September.
  12. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 1998. "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, American Economic Association, vol. 12(3), pages 151-170, Summer.
  13. Eddie Dekel & Michele Piccione, 2000. "Sequential Voting Procedures in Symmetric Binary Elections," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 108(1), pages 34-55, February.
  14. Welch, Ivo, 2000. "Herding among security analysts," Journal of Financial Economics, Elsevier, Elsevier, vol. 58(3), pages 369-396, December.
  15. Eddie Dekel & Michele Piccione, 1997. "On the Equivalence of Simultaneous and Sequential Binary Elections," Discussion Papers, Northwestern University, Center for Mathematical Studies in Economics and Management Science 1206, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
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  18. Munshi, Kaivan, 2004. "Social learning in a heterogeneous population: technology diffusion in the Indian Green Revolution," Journal of Development Economics, Elsevier, vol. 73(1), pages 185-213, February.
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As found on the RePEc Biblio, the curated bibliography for Economics:
  1. > Political Economy > The Political Economy of the US
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Cited by:
  1. Enrico Moretti, 2011. "Social Learning and Peer Effects in Consumption: Evidence from Movie Sales," Review of Economic Studies, Oxford University Press, vol. 78(1), pages 356-393.
  2. S. Ali & Navin Kartik, 2012. "Herding with collective preferences," Economic Theory, Springer, Springer, vol. 51(3), pages 601-626, November.
  3. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
  4. Emilio Barucci & Marco Tolotti, 2012. "Identity, reputation and social interaction with an application to sequential voting," Journal of Economic Interaction and Coordination, Springer, vol. 7(1), pages 79-98, May.
  5. Nathan Yang, 2011. "An Empirical Model of Industry Dynamics with Common Uncertainty and Learning from the Actions of Competitors," Working Papers 11-16, NET Institute.
  6. Deniz Selman, 2011. "Optimal Sequencing of Presidential Primaries," Working Papers 2011/09, Bogazici University, Department of Economics.
  7. Robert Hodgson & John Maloney, 2013. "Bandwagon effects in British elections, 1885–1910," Public Choice, Springer, vol. 157(1), pages 73-90, October.
  8. Philipp Denter & Dana Sisak, 2013. "Do Polls create Momentum in Political Competition?," Tinbergen Institute Discussion Papers 13-169/VII, Tinbergen Institute.
  9. Denter, Philipp & Sisak, Dana, 2013. "Do Polls Create Momentum in Political Campaigns?," Economics Working Paper Series 1326, University of St. Gallen, School of Economics and Political Science.
  10. Meredith, Marc & Malhotra, Neil, 2008. "Can October Surprise? A Natural Experiment Assessing Late Campaign Effects," Research Papers 2002, Stanford University, Graduate School of Business.
  11. Patrick Hummel & Brian Knight, 2012. "Sequential or Simultaneous Elections? A Welfare Analysis," NBER Working Papers 18076, National Bureau of Economic Research, Inc.
  12. Hummel, Patrick, 2012. "Sequential voting in large elections with multiple candidates," Journal of Public Economics, Elsevier, vol. 96(3), pages 341-348.
  13. Hummel, Patrick & Holden, Richard, 2014. "Optimal primaries," Journal of Public Economics, Elsevier, vol. 109(C), pages 64-75.
  14. Ariel Guerreiro & Joao Amaro de Matos, 2013. "Referenda outcomes and the influence of polls: a social network feedback process," FEUNL Working Paper Series wp578, Universidade Nova de Lisboa, Faculdade de Economia.

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