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The real economic costs of COVID-19: Insights from electricity consumption data in Hunan Province, China
The COVID-19 pandemic has caused extreme economic fluctuations. However, the magnitude of the economic cost of this extreme event remains challenging to quantify. The impact of the COVID-19 pandemic on the economy is estimated through firm-level electricity consumption data from Hunan province, Chin...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8632360/ https://www.ncbi.nlm.nih.gov/pubmed/34866706 http://dx.doi.org/10.1016/j.eneco.2021.105747 |
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author | Ai, Hongshan Zhong, Tenglong Zhou, Zhengqing |
author_facet | Ai, Hongshan Zhong, Tenglong Zhou, Zhengqing |
author_sort | Ai, Hongshan |
collection | PubMed |
description | The COVID-19 pandemic has caused extreme economic fluctuations. However, the magnitude of the economic cost of this extreme event remains challenging to quantify. The impact of the COVID-19 pandemic on the economy is estimated through firm-level electricity consumption data from Hunan province, China. Specifically, a difference-in-differences (DID) model was employed to estimate the real economic costs. The results indicate that electricity consumption in Hunan Province dropped by 27.8% during the early stage of the COVID-19 pandemic. Manufacturing and the transportation industry suffered the most severe declines. Electricity consumption began to recover after the virus was controlled. We suggest that government departments should take full measures to prevent and control COVID-19 outbreaks and associated economic impacts, in conjunction with preparing for economic recovery, deploying targeted measures to support different industries in response to the heterogeneity COVID-19 pandemic impacts. The COVID-19 has changed people's living habits and brought a new direction, the Internet industry, of economic growth. Hunan Province needs to accelerate the digital empowerment of traditional industries, develop the Internet, 5G technology, and new digital infrastructure to offset the negative impact of the COVID-19 pandemic. Electricity consumption is an applicable index in estimate the real economic cost of extreme events. |
format | Online Article Text |
id | pubmed-8632360 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86323602021-12-01 The real economic costs of COVID-19: Insights from electricity consumption data in Hunan Province, China Ai, Hongshan Zhong, Tenglong Zhou, Zhengqing Energy Econ Article The COVID-19 pandemic has caused extreme economic fluctuations. However, the magnitude of the economic cost of this extreme event remains challenging to quantify. The impact of the COVID-19 pandemic on the economy is estimated through firm-level electricity consumption data from Hunan province, China. Specifically, a difference-in-differences (DID) model was employed to estimate the real economic costs. The results indicate that electricity consumption in Hunan Province dropped by 27.8% during the early stage of the COVID-19 pandemic. Manufacturing and the transportation industry suffered the most severe declines. Electricity consumption began to recover after the virus was controlled. We suggest that government departments should take full measures to prevent and control COVID-19 outbreaks and associated economic impacts, in conjunction with preparing for economic recovery, deploying targeted measures to support different industries in response to the heterogeneity COVID-19 pandemic impacts. The COVID-19 has changed people's living habits and brought a new direction, the Internet industry, of economic growth. Hunan Province needs to accelerate the digital empowerment of traditional industries, develop the Internet, 5G technology, and new digital infrastructure to offset the negative impact of the COVID-19 pandemic. Electricity consumption is an applicable index in estimate the real economic cost of extreme events. Elsevier B.V. 2022-01 2021-12-01 /pmc/articles/PMC8632360/ /pubmed/34866706 http://dx.doi.org/10.1016/j.eneco.2021.105747 Text en © 2021 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Ai, Hongshan Zhong, Tenglong Zhou, Zhengqing The real economic costs of COVID-19: Insights from electricity consumption data in Hunan Province, China |
title | The real economic costs of COVID-19: Insights from electricity consumption data in Hunan Province, China |
title_full | The real economic costs of COVID-19: Insights from electricity consumption data in Hunan Province, China |
title_fullStr | The real economic costs of COVID-19: Insights from electricity consumption data in Hunan Province, China |
title_full_unstemmed | The real economic costs of COVID-19: Insights from electricity consumption data in Hunan Province, China |
title_short | The real economic costs of COVID-19: Insights from electricity consumption data in Hunan Province, China |
title_sort | real economic costs of covid-19: insights from electricity consumption data in hunan province, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8632360/ https://www.ncbi.nlm.nih.gov/pubmed/34866706 http://dx.doi.org/10.1016/j.eneco.2021.105747 |
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