Citizen forecasting in a mixed electoral system

IF 5.7 2区 经济学 Q1 ECONOMICS
Arndt Leininger , Andreas E. Murr , Lukas Stötzer , Mark A. Kayser
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引用次数: 0

Abstract

Existing studies show that aggregating citizens’ expectations about who will win can predict election outcomes in a majoritarian system. But can so-called citizen forecasting also successfully predict outcomes in mixed-member systems, where constituency results are less important? The existing evidence is mixed and limited in scope. We conducted, therefore, a citizen forecast of the 2021 German federal election by administering an original survey asking citizens who they thought would win in their constituency, what share of the vote each candidate would win in their constituency, and what share of the vote each party would win nationally. Citizens predicted constituency winners and vote shares more accurately than several benchmarks. However, our citizen forecast was based on a non-representative sample from an online-access panel. We conclude that citizen forecasting provides a simple and inexpensive way to predict the various relevant outcomes in mixed-member elections.
混合选举制度下的公民预测
现有的研究表明,汇总公民对谁将获胜的预期可以预测多数主义制度下的选举结果。但是,所谓的“公民预测”是否也能成功地预测选区结果不那么重要的混合成员制度的结果呢?现有的证据是混杂的,而且范围有限。因此,我们对2021年德国联邦选举进行了公民预测,通过管理一项原始调查,询问公民他们认为谁将在他们的选区获胜,每个候选人将在他们的选区赢得多少选票,以及每个政党将在全国赢得多少选票。公民预测选区获胜者和投票份额比几个基准更准确。然而,我们的公民预测是基于来自在线访问面板的非代表性样本。我们的结论是,公民预测提供了一种简单而廉价的方法来预测混合成员选举的各种相关结果。
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来源期刊
CiteScore
17.10
自引率
11.40%
发文量
189
审稿时长
77 days
期刊介绍: The International Journal of Forecasting is a leading journal in its field that publishes high quality refereed papers. It aims to bridge the gap between theory and practice, making forecasting useful and relevant for decision and policy makers. The journal places strong emphasis on empirical studies, evaluation activities, implementation research, and improving the practice of forecasting. It welcomes various points of view and encourages debate to find solutions to field-related problems. The journal is the official publication of the International Institute of Forecasters (IIF) and is indexed in Sociological Abstracts, Journal of Economic Literature, Statistical Theory and Method Abstracts, INSPEC, Current Contents, UMI Data Courier, RePEc, Academic Journal Guide, CIS, IAOR, and Social Sciences Citation Index.
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