Facing an unfortunate trade-off: policy responses, lessons and spill-overs during the COVID-19 pandemic.
COVID-19
GVAR
policy stringency
sign and magnitude restrictions
Journal
Economics and human biology
ISSN: 1873-6130
Titre abrégé: Econ Hum Biol
Pays: Netherlands
ID NLM: 101166135
Informations de publication
Date de publication:
12 2021
12 2021
Historique:
received:
16
04
2021
revised:
09
07
2021
accepted:
24
07
2021
pubmed:
2
8
2021
medline:
15
12
2021
entrez:
1
8
2021
Statut:
ppublish
Résumé
Although COVID-19 emerged as a global shock, governments adopted non-pharmaceutical policy responses that were rather heterogeneous, depending on cultural and institutional characteristics. At the country level, the stringency of 'lockdown'-type policies should be set to achieve the best possible trade-off between economic and fatality dynamics, obviously accounting for possible cross-border influences. To allow for policy learning, I assume that the first country implementing a policy initiative that is worth emulating must either get the best possible health or the best possible economic outcome. I propose a combination of sign and magnitude restrictions, embedded in a global VAR model, to identify idiosyncratic policy shocks that spill over and influence policy responses abroad. Once policy shocks are identified, I run a comparison exercise between two model specifications, i.e. with and without policy emulation. Within a given a sample, this methodology can be used to find when and where policy lessons can be identified. I find that, among 17 developed and developing countries, few can offer lessons based on their policy initiatives, but several others might get better trade-offs through policy emulation, although in reality this outcome is not guaranteed to have occurred.
Identifiants
pubmed: 34333351
pii: S1570-677X(21)00076-9
doi: 10.1016/j.ehb.2021.101052
pmc: PMC8525467
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
101052Informations de copyright
Copyright © 2021 Elsevier B.V. All rights reserved.
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