Artikel

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

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.

Language
Englisch

Bibliographic citation
Journal: Political Analysis ; ISSN: 1476-4989 ; Year: 2023 ; Issue: First View ; Pages: 1-9 ; Cambridge: Cambridge University Press

Classification
Politik
Subject
survey experiments
utility theory
structural modeling
conjoint analysis
preferences

Event
Geistige Schöpfung
(who)
Hartmann, Felix
Humphreys, Macartan
Geissler, Ferdinand
Klüver, Heike
Giesecke, Johannes
Event
Veröffentlichung
(who)
Cambridge University Press
(where)
Cambridge
(when)
2023

DOI
doi:10.1017/pan.2023.25
Handle
Last update
10.03.2025, 11:46 AM CET

Data provider

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Object type

  • Artikel

Associated

  • Hartmann, Felix
  • Humphreys, Macartan
  • Geissler, Ferdinand
  • Klüver, Heike
  • Giesecke, Johannes
  • Cambridge University Press

Time of origin

  • 2023

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