Trading Liberties: Estimating COVID-19 Policy Preferences from Conjoint Data

IF 4.7 2区 社会学 Q1 POLITICAL SCIENCE Political Analysis Pub Date : 2023-08-18 DOI:10.1017/pan.2023.25
Felix Hartmann, M. Humphreys, Ferdinand Geissler, H. Klüver, Johannes Giesecke
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Abstract

Survey experiments are an important tool to measure policy preferences. Researchers often rely on the random assignment of policy attribute levels to estimate different types of average marginal effects. Yet, researchers are often interested in how respondents trade-off different policy dimensions. We use a conjoint experiment administered to more than 10,000 respondents in Germany, to study preferences over personal freedoms and public welfare during the COVID-19 crisis. Using a pre-registered structural model, we estimate policy ideal points and indifference curves to assess the conditions under which citizens are willing to sacrifice freedoms in the interest of public well-being. We document broad willingness to accept restrictions on rights alongside sharp heterogeneity with respect to vaccination status. The majority of citizens are vaccinated and strongly support limitations on freedoms in response to extreme conditions—especially, when they vaccinated themselves are exempted from these limitations. The unvaccinated minority prefers no restrictions on freedoms regardless of the severity of the pandemic. These policy packages also matter for reported trust in government, in opposite ways for vaccinated and unvaccinated citizens.
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贸易自由度:从联合数据估计新冠肺炎政策偏好
调查实验是衡量政策偏好的重要工具。研究人员通常依靠政策属性水平的随机分配来估计不同类型的平均边际效应。然而,研究人员往往对受访者如何权衡不同的政策层面感兴趣。我们使用一项对德国10000多名受访者进行的联合实验,研究新冠肺炎危机期间对个人自由和公共福利的偏好。使用预先注册的结构模型,我们估计了政策理想点和无差别曲线,以评估公民愿意为公共福祉牺牲自由的条件。我们记录了接受权利限制的广泛意愿,以及疫苗接种状况的严重异质性。大多数公民都接种了疫苗,并强烈支持在极端条件下限制自由——尤其是当他们自己接种疫苗时,他们就不受这些限制。无论疫情的严重程度如何,未接种疫苗的少数人都不希望对自由施加限制。据报道,这些政策包对政府的信任也很重要,对接种疫苗和未接种疫苗的公民来说则相反。
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来源期刊
Political Analysis
Political Analysis POLITICAL SCIENCE-
CiteScore
8.80
自引率
3.70%
发文量
30
期刊介绍: Political Analysis chronicles these exciting developments by publishing the most sophisticated scholarship in the field. It is the place to learn new methods, to find some of the best empirical scholarship, and to publish your best research.
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