Williams, S., Crookes, A., Glass, K. et al. (1 more author) (2021) COVID-19 mortalities in England and Wales and the Peltzman offsetting effect. Applied Economics, 53 (60). pp. 6982-6998. ISSN 0003-6846
Abstract
There are two approaches to measuring COVID-19 deaths–‘COVID associated deaths’ and ‘excess deaths’. An excess deaths framework is preferable, as there is measurement error in COVID associated deaths, due to issues relating to imperfect information about deaths that are directly attributable to COVID-19. The standard measure of excess deaths (comparison of deaths to a 5-year average) is subject to an omitted variables problem, as it attributes the entirety of the variation in mortality to COVID-19. We propose a method to estimate a refined measure of COVID-19 excess deaths in England and Wales that addresses the omitted impact of the first blanket lockdown. Using the counterfactual, we obtain a first stage estimate of excess deaths. In the second stage, this is decomposed into estimates of a refined measure of COVID-19 excess deaths and the excess mortality impact of lockdown. Our results suggest: (i) a refined estimate of mean weekly COVID-19 excess deaths that is 63% of standard excess deaths; and (ii) a positive net excess mortality impact of the lockdown. We make a case that (ii) is due to the Peltzman offsetting effect, i.e. the intended mortality impact of the lockdown was more than offset by the unintended impact.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-ncnd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
Keywords: | Excess deaths; counterfactual; lockdown; unintended consequences; demographics |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Sep 2021 07:49 |
Last Modified: | 10 Mar 2022 09:53 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.1080/00036846.2021.1955089 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177905 |
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