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Distributional effects of COVID-19
Using Italian Labour Force Survey data for the period 2019Q1-2020Q4 and applying quantile regression model accounting for sample selection bias, the paper investigates the effects of the first wave of the COVID-19 pandemic on the wage distribution of employees, exploiting differences across sectors...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9851096/ http://dx.doi.org/10.1007/s40821-022-00230-3 |
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author | Aina, Carmen Brunetti, Irene Mussida, Chiara Scicchitano, Sergio |
author_facet | Aina, Carmen Brunetti, Irene Mussida, Chiara Scicchitano, Sergio |
author_sort | Aina, Carmen |
collection | PubMed |
description | Using Italian Labour Force Survey data for the period 2019Q1-2020Q4 and applying quantile regression model accounting for sample selection bias, the paper investigates the effects of the first wave of the COVID-19 pandemic on the wage distribution of employees, exploiting differences across sectors and by working from home arrangement. The findings reveal that the pandemic seems to positively affect wages of the entire workforce. However, this short-term advantage might be temporary as potentially driven by occupational changes in employment composition, whereas teleworking arrangement entails a wage premium for all workers. Low paid workers, employed in hotel/restaurant sector and not teleworking during the outbreak, face a reduction in wages (− 13.7%), while employees of public administration and education sectors exhibit a wage premium. When considering the joint effect of COVID-19 and working from home arrangement, estimates show that, despite few exceptions, wages of teleworking employees have been not affected by the coronavirus. Finally, we also control for self-selection issue by implementing the inverse probability weighting estimator. |
format | Online Article Text |
id | pubmed-9851096 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-98510962023-01-20 Distributional effects of COVID-19 Aina, Carmen Brunetti, Irene Mussida, Chiara Scicchitano, Sergio Eurasian Bus Rev Regular Article Using Italian Labour Force Survey data for the period 2019Q1-2020Q4 and applying quantile regression model accounting for sample selection bias, the paper investigates the effects of the first wave of the COVID-19 pandemic on the wage distribution of employees, exploiting differences across sectors and by working from home arrangement. The findings reveal that the pandemic seems to positively affect wages of the entire workforce. However, this short-term advantage might be temporary as potentially driven by occupational changes in employment composition, whereas teleworking arrangement entails a wage premium for all workers. Low paid workers, employed in hotel/restaurant sector and not teleworking during the outbreak, face a reduction in wages (− 13.7%), while employees of public administration and education sectors exhibit a wage premium. When considering the joint effect of COVID-19 and working from home arrangement, estimates show that, despite few exceptions, wages of teleworking employees have been not affected by the coronavirus. Finally, we also control for self-selection issue by implementing the inverse probability weighting estimator. Springer International Publishing 2023-01-19 2023 /pmc/articles/PMC9851096/ http://dx.doi.org/10.1007/s40821-022-00230-3 Text en © The Author(s) under exclusive licence to Eurasia Business and Economics Society 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Regular Article Aina, Carmen Brunetti, Irene Mussida, Chiara Scicchitano, Sergio Distributional effects of COVID-19 |
title | Distributional effects of COVID-19 |
title_full | Distributional effects of COVID-19 |
title_fullStr | Distributional effects of COVID-19 |
title_full_unstemmed | Distributional effects of COVID-19 |
title_short | Distributional effects of COVID-19 |
title_sort | distributional effects of covid-19 |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9851096/ http://dx.doi.org/10.1007/s40821-022-00230-3 |
work_keys_str_mv | AT ainacarmen distributionaleffectsofcovid19 AT brunettiirene distributionaleffectsofcovid19 AT mussidachiara distributionaleffectsofcovid19 AT scicchitanosergio distributionaleffectsofcovid19 |