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Describing the impacts of COVID-19 on the labor market in Japan until June 2020
The Labor Force Survey, a large-scale government statistics, and the causal forest algorithm are used to estimate the group average treatment effect of the COVID-19 on the employment status for each month from January to June 2020. We find that (1) because of the seasonality in employment status at...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Singapore
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8286989/ https://www.ncbi.nlm.nih.gov/pubmed/34305434 http://dx.doi.org/10.1007/s42973-021-00081-z |
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author | Fukai, Taiyo Ichimura, Hidehiko Kawata, Keisuke |
author_facet | Fukai, Taiyo Ichimura, Hidehiko Kawata, Keisuke |
author_sort | Fukai, Taiyo |
collection | PubMed |
description | The Labor Force Survey, a large-scale government statistics, and the causal forest algorithm are used to estimate the group average treatment effect of the COVID-19 on the employment status for each month from January to June 2020. We find that (1) because of the seasonality in employment status at monthly level, whether we use January 2020 as the base month for comparison, as done in most of the studies or whether we use the same month last year as the base comparison group makes a large difference; (2) whether we include those who are absent from work among the employed or not makes a large difference in the measure of the impact of COVID-19 and its changes; (3) if we use the employment measure which does not include those who are absent from work among the employed, 25–30% among the employed are adversely affected and that 10% of the employed experienced more than 10% decline in employment probability in April, 2020; (4) those who are the most affected by the COVID-19 are those who are unemployed or work part-time in the hotel and restaurant industry and service occupations; (5) in addition, younger and female respondents are more affected than are older and male respondents; and (6) we observe no clear differences in the impacts of COVID-19 with respect to living location, education status, and firm size among the most affected. |
format | Online Article Text |
id | pubmed-8286989 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-82869892021-07-19 Describing the impacts of COVID-19 on the labor market in Japan until June 2020 Fukai, Taiyo Ichimura, Hidehiko Kawata, Keisuke Jpn Econ Rev (Oxf) Special Issue: Article The Labor Force Survey, a large-scale government statistics, and the causal forest algorithm are used to estimate the group average treatment effect of the COVID-19 on the employment status for each month from January to June 2020. We find that (1) because of the seasonality in employment status at monthly level, whether we use January 2020 as the base month for comparison, as done in most of the studies or whether we use the same month last year as the base comparison group makes a large difference; (2) whether we include those who are absent from work among the employed or not makes a large difference in the measure of the impact of COVID-19 and its changes; (3) if we use the employment measure which does not include those who are absent from work among the employed, 25–30% among the employed are adversely affected and that 10% of the employed experienced more than 10% decline in employment probability in April, 2020; (4) those who are the most affected by the COVID-19 are those who are unemployed or work part-time in the hotel and restaurant industry and service occupations; (5) in addition, younger and female respondents are more affected than are older and male respondents; and (6) we observe no clear differences in the impacts of COVID-19 with respect to living location, education status, and firm size among the most affected. Springer Singapore 2021-07-19 2021 /pmc/articles/PMC8286989/ /pubmed/34305434 http://dx.doi.org/10.1007/s42973-021-00081-z 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 | Special Issue: Article Fukai, Taiyo Ichimura, Hidehiko Kawata, Keisuke Describing the impacts of COVID-19 on the labor market in Japan until June 2020 |
title | Describing the impacts of COVID-19 on the labor market in Japan until June 2020 |
title_full | Describing the impacts of COVID-19 on the labor market in Japan until June 2020 |
title_fullStr | Describing the impacts of COVID-19 on the labor market in Japan until June 2020 |
title_full_unstemmed | Describing the impacts of COVID-19 on the labor market in Japan until June 2020 |
title_short | Describing the impacts of COVID-19 on the labor market in Japan until June 2020 |
title_sort | describing the impacts of covid-19 on the labor market in japan until june 2020 |
topic | Special Issue: Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8286989/ https://www.ncbi.nlm.nih.gov/pubmed/34305434 http://dx.doi.org/10.1007/s42973-021-00081-z |
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