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Optimal lockdowns
This paper provides a framework for understanding optimal lockdowns and makes three contributions. First, it theoretically analyzes lockdown policies and argues that policy makers systematically enact too strict lockdowns because their incentives are misaligned with achieving desired ends and they c...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9449920/ https://www.ncbi.nlm.nih.gov/pubmed/36091084 http://dx.doi.org/10.1007/s11127-022-00992-4 |
_version_ | 1784784407338418176 |
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author | Hebert, David J. Curry, Michael D. |
author_facet | Hebert, David J. Curry, Michael D. |
author_sort | Hebert, David J. |
collection | PubMed |
description | This paper provides a framework for understanding optimal lockdowns and makes three contributions. First, it theoretically analyzes lockdown policies and argues that policy makers systematically enact too strict lockdowns because their incentives are misaligned with achieving desired ends and they cannot adapt to changing circumstances. Second, it provides a benchmark to determine how strongly policy makers in different locations should respond to COVID-19. Finally, it provides a framework for understanding how, when, and why lockdown policy is expected to change. |
format | Online Article Text |
id | pubmed-9449920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-94499202022-09-07 Optimal lockdowns Hebert, David J. Curry, Michael D. Public Choice Article This paper provides a framework for understanding optimal lockdowns and makes three contributions. First, it theoretically analyzes lockdown policies and argues that policy makers systematically enact too strict lockdowns because their incentives are misaligned with achieving desired ends and they cannot adapt to changing circumstances. Second, it provides a benchmark to determine how strongly policy makers in different locations should respond to COVID-19. Finally, it provides a framework for understanding how, when, and why lockdown policy is expected to change. Springer US 2022-09-07 2022 /pmc/articles/PMC9449920/ /pubmed/36091084 http://dx.doi.org/10.1007/s11127-022-00992-4 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Hebert, David J. Curry, Michael D. Optimal lockdowns |
title | Optimal lockdowns |
title_full | Optimal lockdowns |
title_fullStr | Optimal lockdowns |
title_full_unstemmed | Optimal lockdowns |
title_short | Optimal lockdowns |
title_sort | optimal lockdowns |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9449920/ https://www.ncbi.nlm.nih.gov/pubmed/36091084 http://dx.doi.org/10.1007/s11127-022-00992-4 |
work_keys_str_mv | AT hebertdavidj optimallockdowns AT currymichaeld optimallockdowns |