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Corruption Information and Vote Share: A Meta-Analysis and Lessons for Experimental Design

American Political Science Review(2020)SCI 1区

Yale Univ

Cited 60|Views4
Abstract
Debate persists on whether voters hold politicians accountable for corruption. Numerous experiments have examined whether informing voters about corrupt acts of politicians decreases their vote share. Meta-analysis demonstrates that corrupt candidates are punished by zero percentage points across field experiments, but approximately 32 points in survey experiments. I argue this discrepancy arises due to methodological differences. Small effects in field experiments may stem partially from weak treatments and noncompliance, and large effects in survey experiments are likely from social desirability bias and the lower and hypothetical nature of costs. Conjoint experiments introduce hypothetical costly trade-offs, but it may be best to interpret results in terms of realistic sets of characteristics rather than marginal effects of particular characteristics. These results suggest that survey experiments may provide point estimates that are not representative of real-world voting behavior. However, field experimental estimates may also not recover the “true” effects due to design decisions and limitations.
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要点】:本文通过元分析探讨了告知选民政治家腐败行为是否会减少他们的得票率,认为实验方法论差异导致现场实验中腐败候选人的惩罚效应不明显,而调查实验中则较为显著,指出调查实验可能高估了腐败对选票的影响。

方法】:采用元分析方法,对比了现场实验和调查实验中腐败信息对政治家得票率的影响。

实验】:现场实验中,腐败候选人在实验中受到的惩罚效应不明显,可能由于治疗效果较弱和非遵从性问题;调查实验中,腐败候选人受到的惩罚效应较大,可能源于社会期望偏差和成本的低假设性质。联合实验引入了假设性的成本权衡,但最好将结果解释为现实特征的集合,而不是特定特征的边际效应。这些结果表明,调查实验可能不反映现实世界中投票行为的确切估计值,而现场实验的估计值也可能由于设计决策和限制而无法恢复“真实”效应。