Comprehensive Retrospective Voting in Mixed Electoral Systems: Evidence from the 2016 Korean Legislative Election

Author:

SHIN JUNGSUB

Abstract

AbstractPerformance-based retrospective voting is a fundamental mechanism of democracy. A good deal of scholarship has examined this electoral mechanism, but the extant studies have two omissions. First, there is little research that considers several retrospective evaluations together using an incumbent voting model. Second, there is little research that examines the difference in the effects of voters’ retrospective evaluations on two different ballots in mixed electoral systems. To fill these omissions, this article tests a comprehensive retrospective performance voting model in a mixed electoral system. Specifically, this article examines the effects of voters’ retrospective economic evaluations of economic performance at the national and personal levels, human rights, corruption, welfare protection, and foreign policy on vote choice for the incumbent party in the 2016 Korean legislative election in which voters had two ballots: one for the party list vote and one for the district vote. By using multinomial logistic regression models, this article finds that among the six retrospective evaluation categories, judgments of national economic performance at the national level, human rights, and foreign policy have a statistically significant impact on the likelihood of voting for the incumbent party in party list vote choice, whereas only voters’ evaluation of foreign policy matter in the district level vote decision. The results imply that Korean voters consider various aspects of government performance, such as the conditions of human rights and relationships with other countries, rather than just focusing on the economy. The retrospective voting behavior of Korean voters differs between party list and district level ballots.

Publisher

Cambridge University Press (CUP)

Subject

Political Science and International Relations,Sociology and Political Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3