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A lockdown index to assess the economic impact of the coronavirus

Like most countries, the Swiss government adopted drastic measures to stop the spread of the coronavirus. These measures were aimed at avoiding close physical proximity between people. The adverse economic consequences of this lockdown policy became immediately apparent, with almost two million work...

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Autores principales: Faber, Marius, Ghisletta, Andrea, Schmidheiny, Kurt
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7453704/
https://www.ncbi.nlm.nih.gov/pubmed/32874959
http://dx.doi.org/10.1186/s41937-020-00056-8
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author Faber, Marius
Ghisletta, Andrea
Schmidheiny, Kurt
author_facet Faber, Marius
Ghisletta, Andrea
Schmidheiny, Kurt
author_sort Faber, Marius
collection PubMed
description Like most countries, the Swiss government adopted drastic measures to stop the spread of the coronavirus. These measures were aimed at avoiding close physical proximity between people. The adverse economic consequences of this lockdown policy became immediately apparent, with almost two million workers, or more than every third worker in Switzerland, being put on short-time work within only 6 weeks after the policy’s implementation. In an attempt to promptly assess the heterogeneous consequences of this lockdown policy, we computed a lockdown index. This index is based on an occupation’s dependence on physical proximity to other people and corrected for certain essential sectors being exempt from this policy. We find that on average, 31% of jobs in Switzerland have been potentially restricted by the lockdown policy. This average masks considerable heterogeneity along many dimensions, with the strongest effects for the large industries hospitality, construction, and arts and entertainment. With respect to the regional variation, we find the strongest effects for the cantons of Obwalden, Uri, Appenzell Innerrhoden, and Valais. Moreover, low- and middle-income individuals are considerably more restricted than high-income ones. We do not find meaningful differences between men and women or urban and rural areas. Finally, we test the explanatory power of the lockdown index for short-time work and unemployment increases by canton and industry until the end of April 2020 and find that it can explain up to 58% of these short-term employment outcomes.
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spelling pubmed-74537042020-08-28 A lockdown index to assess the economic impact of the coronavirus Faber, Marius Ghisletta, Andrea Schmidheiny, Kurt Swiss J Econ Stat Original Article Like most countries, the Swiss government adopted drastic measures to stop the spread of the coronavirus. These measures were aimed at avoiding close physical proximity between people. The adverse economic consequences of this lockdown policy became immediately apparent, with almost two million workers, or more than every third worker in Switzerland, being put on short-time work within only 6 weeks after the policy’s implementation. In an attempt to promptly assess the heterogeneous consequences of this lockdown policy, we computed a lockdown index. This index is based on an occupation’s dependence on physical proximity to other people and corrected for certain essential sectors being exempt from this policy. We find that on average, 31% of jobs in Switzerland have been potentially restricted by the lockdown policy. This average masks considerable heterogeneity along many dimensions, with the strongest effects for the large industries hospitality, construction, and arts and entertainment. With respect to the regional variation, we find the strongest effects for the cantons of Obwalden, Uri, Appenzell Innerrhoden, and Valais. Moreover, low- and middle-income individuals are considerably more restricted than high-income ones. We do not find meaningful differences between men and women or urban and rural areas. Finally, we test the explanatory power of the lockdown index for short-time work and unemployment increases by canton and industry until the end of April 2020 and find that it can explain up to 58% of these short-term employment outcomes. Springer International Publishing 2020-08-28 2020 /pmc/articles/PMC7453704/ /pubmed/32874959 http://dx.doi.org/10.1186/s41937-020-00056-8 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Original Article
Faber, Marius
Ghisletta, Andrea
Schmidheiny, Kurt
A lockdown index to assess the economic impact of the coronavirus
title A lockdown index to assess the economic impact of the coronavirus
title_full A lockdown index to assess the economic impact of the coronavirus
title_fullStr A lockdown index to assess the economic impact of the coronavirus
title_full_unstemmed A lockdown index to assess the economic impact of the coronavirus
title_short A lockdown index to assess the economic impact of the coronavirus
title_sort lockdown index to assess the economic impact of the coronavirus
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7453704/
https://www.ncbi.nlm.nih.gov/pubmed/32874959
http://dx.doi.org/10.1186/s41937-020-00056-8
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