How Trump triumphed: Multi-candidate primaries with buffoons

التفاصيل البيبلوغرافية
العنوان: How Trump triumphed: Multi-candidate primaries with buffoons
المؤلفون: Castanheira, Micael, Huck, Steffen, Leutgeb, Johannes, Schotter, Andrew
المساهمون: Wissenschaftszentrum Berlin für Sozialforschung gGmbH
المصدر: SP II 2020-307r, Discussion Papers / Wissenschaftszentrum Berlin für Sozialforschung, Forschungsschwerpunkt Markt und Entscheidung, Abteilung Ökonomik des Wandels, 56
بيانات النشر: DEU, Berlin, 2022.
سنة النشر: 2022
مصطلحات موضوعية: Politikwissenschaft, Political science, Trump, Donald, political primaries, truel, politische Willensbildung, politische Soziologie, politische Kultur, Political Process, Elections, Political Sociology, Political Culture, USA, Präsidentschaftswahl, Kandidatur, Die Republikaner, Wahlkampf, United States of America, presidential election, candidacy, The Republicans (Germany), election campaign
الوصف: While people on all sides of the political spectrum were amazed that Donald Trump won the Republican nomination this paper demonstrates that Trump's victory was not a crazy event but rather the equilibrium outcome of a multi-candidate race where one candidate, the buffoon, is viewed as likely to self-destruct and hence unworthy of attack. We model such primaries as a truel (a three-way duel), solve for its equilibrium, and test its implications in a laboratory experiment. We find that people recognize a buffoon when they see one and aim their attacks elsewhere with the unfortunate consequence that the buffoon has an enhanced probability of winning. This result is strongest amongst those subjects who demonstrate an ability to best respond suggesting that our results would only be stronger when the game is played by experts and for higher stakes.
نوع الوثيقة: Arbeitspapier
working paper
URL الوصول: https://www.ssoar.info/ssoar/handle/document/81465
حقوق: Deposit Licence - Keine Weiterverbreitung, keine Bearbeitung
Deposit Licence - No Redistribution, No Modifications
رقم الأكسشن: edsgso.81465
قاعدة البيانات: SSOAR – Social Science Open Access Repository