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Covid-19 Policy Convergence in Response to Knightian Uncertainty
Domestic policy responses to COVID-19 were remarkably consistent during the early days of the pandemic. What explains this policy convergence? Our formal model suggests that the novel character of COVID-19 produced a period of maximum policy uncertainty, incentivizing political actors to converge on...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331119/ https://www.ncbi.nlm.nih.gov/pubmed/37431520 http://dx.doi.org/10.1177/14789299221109081 |
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author | Sayers, Anthony M. Scholtz, Christa Armstrong, Dave Kam, Christopher Alcantara, Christopher |
author_facet | Sayers, Anthony M. Scholtz, Christa Armstrong, Dave Kam, Christopher Alcantara, Christopher |
author_sort | Sayers, Anthony M. |
collection | PubMed |
description | Domestic policy responses to COVID-19 were remarkably consistent during the early days of the pandemic. What explains this policy convergence? Our formal model suggests that the novel character of COVID-19 produced a period of maximum policy uncertainty, incentivizing political actors to converge on a common set of policies to minimize their exposure to electoral punishment. This convergence is likely to break down as policy feedback produces opinion divergence among experts and the public and as politicians recalculate the costs and benefits of various policy responses and under some conditions facing incentives to adopt extreme policies. |
format | Online Article Text |
id | pubmed-10331119 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-103311192023-07-10 Covid-19 Policy Convergence in Response to Knightian Uncertainty Sayers, Anthony M. Scholtz, Christa Armstrong, Dave Kam, Christopher Alcantara, Christopher Polit Stud Rev Early Results Domestic policy responses to COVID-19 were remarkably consistent during the early days of the pandemic. What explains this policy convergence? Our formal model suggests that the novel character of COVID-19 produced a period of maximum policy uncertainty, incentivizing political actors to converge on a common set of policies to minimize their exposure to electoral punishment. This convergence is likely to break down as policy feedback produces opinion divergence among experts and the public and as politicians recalculate the costs and benefits of various policy responses and under some conditions facing incentives to adopt extreme policies. SAGE Publications 2022-07-21 2023-08 /pmc/articles/PMC10331119/ /pubmed/37431520 http://dx.doi.org/10.1177/14789299221109081 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Early Results Sayers, Anthony M. Scholtz, Christa Armstrong, Dave Kam, Christopher Alcantara, Christopher Covid-19 Policy Convergence in Response to Knightian Uncertainty |
title | Covid-19 Policy Convergence in Response to Knightian Uncertainty |
title_full | Covid-19 Policy Convergence in Response to Knightian Uncertainty |
title_fullStr | Covid-19 Policy Convergence in Response to Knightian Uncertainty |
title_full_unstemmed | Covid-19 Policy Convergence in Response to Knightian Uncertainty |
title_short | Covid-19 Policy Convergence in Response to Knightian Uncertainty |
title_sort | covid-19 policy convergence in response to knightian uncertainty |
topic | Early Results |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331119/ https://www.ncbi.nlm.nih.gov/pubmed/37431520 http://dx.doi.org/10.1177/14789299221109081 |
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