Replication Data for: Distributive Politics as Behavioral Localism: Evidence from a Vignette Experiment in Hungary
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https://doi.org/10.7910/DVN/RHAWSC
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Recent literature on friends-and-neighbors voting focused on explaining citizens’ motives behind supporting local candidates; the cue-based ac- count suggests that local ties signal accountability, constituency service orientation and policy representation. Localism was also posited to serve as a cue for distributive politics, but assumptions of voters making inferences about receiving tangible benefits once a politician from their own stock is elected were not corroborated empirically. Drawing on a survey experiment (N=2000) fielded in Hungary, the paper provides a test of pork barrel politics and clientelism serving as manifestations of behavioral localism; that is, if voters formulate expectations of politicians engaging in aforementioned practices based on their local roots. Respondents in treatment and control group were shown the same candidate profile, fictive politicians differing only in their local roots. Results demonstrate that respondents who were told that the candidate was born and living in their hometown were more likely to believe that the politician will ‘bring home the bacon’ as opposed to those confronted with a randomly selected Hungarian settlement as the candidate’s birthplace and residence. Findings refine our understanding of friends-and-neighbors voting, as well as voters’ expectations about likely non-programmatic behavior of elected candidates.
现有关于邻里投票(friends-and-neighbors voting)的研究文献,多聚焦于阐释公民支持本土候选人的动机;线索导向理论(cue-based account)提出,本土关联能够传递出候选人的问责意识、选区服务取向与政策代表立场。另有研究指出,本土主义(localism)亦可作为分配性政治的线索,但“选民会推断,一旦同出身背景的政客当选,自身便可获得切实收益”这一假设并未得到实证支持。本文依托在匈牙利开展的一项样本量为2000的调查实验,对作为行为型本土主义(behavioral localism)表现形式的政治分肥(pork barrel politics)与庇护主义(clientelism)进行了检验,即探究选民是否会依据候选人的本土出身,对其参与前述行为形成预期。实验组与对照组的受访者均被展示了完全一致的候选人简历,虚构候选人仅在本土出身背景上存在差异。研究结果表明,当被告知候选人出生并居住在本乡时,受访者相较于那些得知候选人出生与居住在随机选取的匈牙利定居点的受访者,更倾向于认为该政客会为本乡谋取切实利益。本研究结果深化了学界对邻里投票以及选民对当选政客非纲领性行为预期的认知。
创建时间:
2022-10-19



