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Why Are American Presidential Election Campaign Polls So Variable When Votes Are So Predictable?

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  1. Sergiu Gherghina & Elena Rusu, 2021. "Begin Again: Election Campaign and Own Opinions Among First‐Time Voters in Romania," Social Science Quarterly, Southwestern Social Science Association, vol. 102(4), pages 1311-1329, July.
  2. David A. M. Peterson, 2009. "Campaign Learning and Vote Determinants," American Journal of Political Science, John Wiley & Sons, vol. 53(2), pages 445-460, April.
  3. Leighton Vaughan Williams & J. James Reade, 2016. "Prediction Markets, Social Media and Information Efficiency," Kyklos, Wiley Blackwell, vol. 69(3), pages 518-556, August.
  4. Igor A. Mayburov & Anna P. Kireenko, 2018. "Tax reforms and elections in modern Russia," Journal of Tax Reform, Graduate School of Economics and Management, Ural Federal University, vol. 4(1), pages 73-94.
  5. Bernhardt, Dan & Duggan, John & Squintani, Francesco, 2009. "Private polling in elections and voter welfare," Journal of Economic Theory, Elsevier, vol. 144(5), pages 2021-2056, September.
  6. repec:cup:judgdm:v:14:y:2019:i:3:p:373-380 is not listed on IDEAS
  7. Katjana Gattermann & Claes De Vreese & Wouter van der Brug, 2016. "Evaluations of the Spitzenkandidaten: The Role of Information and News Exposure in Citizens’ Preference Formation," Politics and Governance, Cogitatio Press, vol. 4(1), pages 37-54.
  8. Bernardo S. Da Silveira & João M. P. De Mello, 2011. "Campaign Advertising and Election Outcomes: Quasi-natural Experiment Evidence from Gubernatorial Elections in Brazil," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(2), pages 590-612.
  9. Wang, Samuel S.-H., 2015. "Origins of Presidential poll aggregation: A perspective from 2004 to 2012," International Journal of Forecasting, Elsevier, vol. 31(3), pages 898-909.
  10. Wiśniowski, Arkadiusz & Bijak, Jakub & Forster, Jonathan J. & Smith, Peter W.F., 2019. "Hierarchical model for forecasting the outcomes of binary referenda," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 90-103.
  11. Abu, Christian Ukeame, 2022. "Political Campaign and Human Rights Violation in Rivers State, Nigeria, 2013-2021," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 6(12), pages 536-543, December.
  12. Khan, Urmee & Lieli, Robert P., 2018. "Information flow between prediction markets, polls and media: Evidence from the 2008 presidential primaries," International Journal of Forecasting, Elsevier, vol. 34(4), pages 696-710.
  13. repec:cup:judgdm:v:15:y:2020:i:5:p:863-880 is not listed on IDEAS
  14. Brett Gordon & Mitchell Lovett & Ron Shachar & Kevin Arceneaux & Sridhar Moorthy & Michael Peress & Akshay Rao & Subrata Sen & David Soberman & Oleg Urminsky, 2012. "Marketing and politics: Models, behavior, and policy implications," Marketing Letters, Springer, vol. 23(2), pages 391-403, June.
  15. Strömberg, David, 2002. "Optimal Campaigning in Presidential Elections: The Probability of Being Florida," Seminar Papers 706, Stockholm University, Institute for International Economic Studies.
  16. Donald Wittman, 2009. "How Pressure Groups Activate Voters and Move Candidates Closer to the Median," Economic Journal, Royal Economic Society, vol. 119(540), pages 1324-1343, October.
  17. Jones Jr., Randall J., 2008. "The state of presidential election forecasting: The 2004 experience," International Journal of Forecasting, Elsevier, vol. 24(2), pages 310-321.
  18. Banducci, Susan & Giebler, Heiko & Kritzinger, Sylvia, 2017. "Knowing more from less: how the information environment increases knowledge of party positions," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 47(3), pages 571-588.
  19. Ignacio Ortuño Ortín & Christian Schultz, 2012. "Public funding of political parties when campaigns are informative Abstract: The paper considers public funding of political parties when some voters are poorly informed about parties? candidates and ," EPRU Working Paper Series 2012-05, Economic Policy Research Unit (EPRU), University of Copenhagen. Department of Economics.
  20. Xefteris, Dimitrios, 2012. "Spatial electoral competition with a probabilistically favored candidate," Economics Letters, Elsevier, vol. 116(1), pages 96-98.
  21. James Adams & Simon Weschle & Christopher Wlezien, 2021. "Elite Interactions and Voters’ Perceptions of Parties’ Policy Positions," American Journal of Political Science, John Wiley & Sons, vol. 65(1), pages 101-114, January.
  22. Andrew Gelman & Jessica Hullman & Christopher Wlezien & George Elliott Morris, 2020. "Information, incentives, and goals in election forecasts," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(5), pages 863-880, September.
  23. Meredith, Marc & Malhotra, Neil, 2008. "Can October Surprise? A Natural Experiment Assessing Late Campaign Effects," Research Papers 2002, Stanford University, Graduate School of Business.
  24. Wang, Wei & Rothschild, David & Goel, Sharad & Gelman, Andrew, 2015. "Forecasting elections with non-representative polls," International Journal of Forecasting, Elsevier, vol. 31(3), pages 980-991.
  25. Caterina Gennaioli, 2010. "Go Divisive or Not? How Political Campaigns Affect Turnout," CESifo Working Paper Series 3298, CESifo.
  26. Munzert, Simon, 2017. "Forecasting elections at the constituency level: A correction–combination procedure," International Journal of Forecasting, Elsevier, vol. 33(2), pages 467-481.
  27. Marcelo Tyszler & Arthur Schram, 2016. "Information and strategic voting," Experimental Economics, Springer;Economic Science Association, vol. 19(2), pages 360-381, June.
  28. Manavopoulos Vasilis & Triga Vasiliki & Marschall Stefan & Wurthmann Lucas Constantin, 2018. "The Impact of VAAs on (non-Voting) Aspects of Political Participation: Insights from Panel Data Collected During the 2017 German Federal Elections Campaign," Statistics, Politics and Policy, De Gruyter, vol. 9(2), pages 105-134, December.
  29. Mongrain, Philippe & Nadeau, Richard & Jérôme, Bruno, 2021. "Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model," International Journal of Forecasting, Elsevier, vol. 37(1), pages 289-301.
  30. Jonathan R. Cervas & Bernard Grofman, 2017. "Why noncompetitive states are so important for understanding the outcomes of competitive elections: the Electoral College 1868–2016," Public Choice, Springer, vol. 173(3), pages 251-265, December.
  31. Yangguang Huang & Ming He, 2021. "Structural Analysis Of Tullock Contests With An Application To U.S. House Of Representatives Elections," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(3), pages 1011-1054, August.
  32. Brown, Lloyd B. & Chappell Jr., Henry W., 1999. "Forecasting presidential elections using history and polls," International Journal of Forecasting, Elsevier, vol. 15(2), pages 127-135, April.
  33. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzan, Alfred G., 2017. "Assessing the 2016 U.S. Presidential Election Popular Vote Forecasts," MPRA Paper 83282, University Library of Munich, Germany.
  34. Christine Fauvelle-Aymar & Abel François, 2003. "Campagne électorale, préférences politiques et participation. Une étude empirique sur les élections législatives françaises de 1997," Cahiers de la Maison des Sciences Economiques j04009, Université Panthéon-Sorbonne (Paris 1).
  35. Temporão, Mickael & Dufresne, Yannick & Savoie, Justin & Linden, Clifton van der, 2019. "Crowdsourcing the vote: New horizons in citizen forecasting," International Journal of Forecasting, Elsevier, vol. 35(1), pages 1-10.
  36. José Garcia Montalvo & Omiros Papaspiliopoulos & Timothée Stumpf-Fétizon, 2018. "Bayesian forecasting of electoral outcomes with new parties' competition," Economics Working Papers 1624, Department of Economics and Business, Universitat Pompeu Fabra.
  37. Yarrow Dunham & Antonio A. Arechar & David G. Rand, 2019. "From foe to friend and back again: The temporal dynamics of intra-party bias in the 2016 U.S. Presidential Election," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(3), pages 373-380, May.
  38. Reade, J. James & Vaughan Williams, Leighton, 2019. "Polls to probabilities: Comparing prediction markets and opinion polls," International Journal of Forecasting, Elsevier, vol. 35(1), pages 336-350.
  39. Isakov, Michael & Kuriwaki, Shiro, 2020. "Towards Principled Unskewing: Viewing 2020 Election Polls Through a Corrective Lens from 2016," OSF Preprints 29pvm, Center for Open Science.
  40. Yanwen Wang & Michael Lewis & David A. Schweidel, 2018. "A Border Strategy Analysis of Ad Source and Message Tone in Senatorial Campaigns," Marketing Science, INFORMS, vol. 37(3), pages 333-355, May.
  41. A. Kamakura, Wagner & Afonso Mazzon, Jose & De Bruyn, Arnaud, 2006. "Modeling voter choice to predict the final outcome of two-stage elections," International Journal of Forecasting, Elsevier, vol. 22(4), pages 689-706.
  42. Campbell, James E., 2008. "Evaluating U.S. presidential election forecasts and forecasting equations," International Journal of Forecasting, Elsevier, vol. 24(2), pages 259-271.
  43. José García-Montalvo & Omiros Papaspiliopoulos & Timothée Stumpf-Fétizon, 2018. "Bayesian Forecasting of Electoral Outcomes with new Parties' Competition," Working Papers 1065, Barcelona School of Economics.
  44. Robert Liñeira, 2021. "Valence Secession? Voting Shocks and Independence Support in Scotland," Politics and Governance, Cogitatio Press, vol. 9(4), pages 399-411.
  45. Lee, Taeku & Schlesinger, Mark, 2001. "Signaling in Context: Elite Influence and the Dynamics of Public Support for Clinton's Health Security Act," Working Paper Series rwp01-029, Harvard University, John F. Kennedy School of Government.
  46. Caroline Le Pennec & Vincent Pons, 2019. "How Do Campaigns Shape Vote Choice? Multi-Country Evidence from 62 Elections and 56 TV Debates," NBER Working Papers 26572, National Bureau of Economic Research, Inc.
  47. Till Weber, 2007. "Campaign Effects and Second-Order Cycles," European Union Politics, , vol. 8(4), pages 509-536, December.
  48. Gabriel S. Lenz, 2009. "Learning and Opinion Change, Not Priming: Reconsidering the Priming Hypothesis," American Journal of Political Science, John Wiley & Sons, vol. 53(4), pages 821-837, October.
  49. Jerome, Bruno & Jerome, Veronique & Lewis-Beck, Michael S., 1999. "Polls fail in France: forecasts of the 1997 legislative election1," International Journal of Forecasting, Elsevier, vol. 15(2), pages 163-174, April.
  50. Adam Meirowitz, 2005. "Informational Party Primaries and Strategic Ambiguity," Journal of Theoretical Politics, , vol. 17(1), pages 107-136, January.
  51. Montalvo, José G. & Papaspiliopoulos, Omiros & Stumpf-Fétizon, Timothée, 2019. "Bayesian forecasting of electoral outcomes with new parties’ competition," European Journal of Political Economy, Elsevier, vol. 59(C), pages 52-70.
  52. Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
  53. Enrique García-Viñuela & Ignacio Jurado & Pedro Riera, 2018. "The effect of valence and ideology in campaign conversion: panel evidence from three Spanish general elections," Public Choice, Springer, vol. 175(1), pages 155-179, April.
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