Cargando…
Electricity-consumption data reveals the economic impact and industry recovery during the pandemic
Coping with the outbreak of Coronavirus disease 2019 (COVID-19), many countries have implemented public-health measures and movement restrictions to prevent the spread of the virus. However, the strict mobility control also brought about production stagnation and market disruption, resulting in a se...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8497577/ https://www.ncbi.nlm.nih.gov/pubmed/34620905 http://dx.doi.org/10.1038/s41598-021-98259-3 |
_version_ | 1784579985859674112 |
---|---|
author | Wang, Xinlei Si, Caomingzhe Gu, Jinjin Liu, Guolong Liu, Wenxuan Qiu, Jing Zhao, Junhua |
author_facet | Wang, Xinlei Si, Caomingzhe Gu, Jinjin Liu, Guolong Liu, Wenxuan Qiu, Jing Zhao, Junhua |
author_sort | Wang, Xinlei |
collection | PubMed |
description | Coping with the outbreak of Coronavirus disease 2019 (COVID-19), many countries have implemented public-health measures and movement restrictions to prevent the spread of the virus. However, the strict mobility control also brought about production stagnation and market disruption, resulting in a severe worldwide economic crisis. Quantifying the economic stagnation and predicting post-pandemic recovery are imperative issues. Besides, it is significant to examine how the impact of COVID-19 on economic activities varied with industries. As a reflection of enterprises’ production output, high-frequency electricity-consumption data is an intuitive and effective tool for evaluating the economic impact of COVID-19 on different industries. In this paper, we quantify and compare economic impacts on the electricity consumption of different industries in eastern China. In order to address this problem, we conduct causal analysis using a difference-in-difference (DID) estimation model to analyze the effects of multi-phase public-health measures. Our model employs the electricity-consumption data ranging from 2019 to 2020 of 96 counties in the Eastern China region, which covers three main economic sectors and their 53 sub-sectors. The results indicate that electricity demand of all industries (other than information transfer industry) rebounded after the initial shock, and is back to pre-pandemic trends after easing the control measures at the end of May 2020. Emergency response, the combination of all countermeasures to COVID-19 in a certain period, affected all industries, and the higher level of emergency response with stricter movement control resulted in a greater decrease in electricity consumption and production. The pandemic outbreak has a negative-lag effect on industries, and there is greater resilience in industries that are less dependent on human mobility for economic production and activities. |
format | Online Article Text |
id | pubmed-8497577 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-84975772021-10-12 Electricity-consumption data reveals the economic impact and industry recovery during the pandemic Wang, Xinlei Si, Caomingzhe Gu, Jinjin Liu, Guolong Liu, Wenxuan Qiu, Jing Zhao, Junhua Sci Rep Article Coping with the outbreak of Coronavirus disease 2019 (COVID-19), many countries have implemented public-health measures and movement restrictions to prevent the spread of the virus. However, the strict mobility control also brought about production stagnation and market disruption, resulting in a severe worldwide economic crisis. Quantifying the economic stagnation and predicting post-pandemic recovery are imperative issues. Besides, it is significant to examine how the impact of COVID-19 on economic activities varied with industries. As a reflection of enterprises’ production output, high-frequency electricity-consumption data is an intuitive and effective tool for evaluating the economic impact of COVID-19 on different industries. In this paper, we quantify and compare economic impacts on the electricity consumption of different industries in eastern China. In order to address this problem, we conduct causal analysis using a difference-in-difference (DID) estimation model to analyze the effects of multi-phase public-health measures. Our model employs the electricity-consumption data ranging from 2019 to 2020 of 96 counties in the Eastern China region, which covers three main economic sectors and their 53 sub-sectors. The results indicate that electricity demand of all industries (other than information transfer industry) rebounded after the initial shock, and is back to pre-pandemic trends after easing the control measures at the end of May 2020. Emergency response, the combination of all countermeasures to COVID-19 in a certain period, affected all industries, and the higher level of emergency response with stricter movement control resulted in a greater decrease in electricity consumption and production. The pandemic outbreak has a negative-lag effect on industries, and there is greater resilience in industries that are less dependent on human mobility for economic production and activities. Nature Publishing Group UK 2021-10-07 /pmc/articles/PMC8497577/ /pubmed/34620905 http://dx.doi.org/10.1038/s41598-021-98259-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Xinlei Si, Caomingzhe Gu, Jinjin Liu, Guolong Liu, Wenxuan Qiu, Jing Zhao, Junhua Electricity-consumption data reveals the economic impact and industry recovery during the pandemic |
title | Electricity-consumption data reveals the economic impact and industry recovery during the pandemic |
title_full | Electricity-consumption data reveals the economic impact and industry recovery during the pandemic |
title_fullStr | Electricity-consumption data reveals the economic impact and industry recovery during the pandemic |
title_full_unstemmed | Electricity-consumption data reveals the economic impact and industry recovery during the pandemic |
title_short | Electricity-consumption data reveals the economic impact and industry recovery during the pandemic |
title_sort | electricity-consumption data reveals the economic impact and industry recovery during the pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8497577/ https://www.ncbi.nlm.nih.gov/pubmed/34620905 http://dx.doi.org/10.1038/s41598-021-98259-3 |
work_keys_str_mv | AT wangxinlei electricityconsumptiondatarevealstheeconomicimpactandindustryrecoveryduringthepandemic AT sicaomingzhe electricityconsumptiondatarevealstheeconomicimpactandindustryrecoveryduringthepandemic AT gujinjin electricityconsumptiondatarevealstheeconomicimpactandindustryrecoveryduringthepandemic AT liuguolong electricityconsumptiondatarevealstheeconomicimpactandindustryrecoveryduringthepandemic AT liuwenxuan electricityconsumptiondatarevealstheeconomicimpactandindustryrecoveryduringthepandemic AT qiujing electricityconsumptiondatarevealstheeconomicimpactandindustryrecoveryduringthepandemic AT zhaojunhua electricityconsumptiondatarevealstheeconomicimpactandindustryrecoveryduringthepandemic |