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Labour Market Dynamics and Worker Flows in India: Impact of Covid-19
Tracking and analyzing the labour market dynamics at regular, frequent intervals is critical. However, this was not possible for India, a large emerging economy with a significant population undergoing demographic transition, due to a paucity of data. We use the new dataset Centre for Monitoring Ind...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer India
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9862225/ https://www.ncbi.nlm.nih.gov/pubmed/36713957 http://dx.doi.org/10.1007/s41027-022-00420-7 |
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author | Chatterjee, Partha Dev, Aakash |
author_facet | Chatterjee, Partha Dev, Aakash |
author_sort | Chatterjee, Partha |
collection | PubMed |
description | Tracking and analyzing the labour market dynamics at regular, frequent intervals is critical. However, this was not possible for India, a large emerging economy with a significant population undergoing demographic transition, due to a paucity of data. We use the new dataset Centre for Monitoring Indian Economy (CMIE)—Consumer Pyramids Household Survey (CPHS) and use a panel to create Labour Flow Charts and Transition Matrices for India from January 2019 to December 2021. To the best of our knowledge, this is the first time these were created for India. We then use that to look at the impact of Covid-19 on the Indian labour market. We not only look at transitions between employment, unemployment and out of labour force, but also across types of employment—full-time and part-time. The rich data also allows us to consider heterogeneity in the labour market and look at the differential impact of the pandemic across different education groups and gender. From the labour flow charts and transition probabilities, we find that while all groups have been impacted, the magnitude of the impact is different across groups. The recovery is also uneven, and the extent depends on education levels. Further, we do an event study analysis to examine the likelihood of getting a full-time job across different educational and gender groups. Men, on average, enjoy a higher likelihood of getting a full-time job than women. The likelihood coefficients also go up with increasing educational qualifications. Looking at skill heterogeneity, while the likelihood of getting a full-time job either goes down for most groups during the pandemic or the change is minuscule, strikingly it goes up for those with no education, for both men and women. The likelihood coefficients remain elevated for men even after the restrictions are removed, and that for women reverts to the level seen before the pandemic. Finally, this paper provides a way to continuously monitor the dynamics of the labour market as data is released in the regular intervals in the future, which would be of great value for researchers and policymakers alike. |
format | Online Article Text |
id | pubmed-9862225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer India |
record_format | MEDLINE/PubMed |
spelling | pubmed-98622252023-01-23 Labour Market Dynamics and Worker Flows in India: Impact of Covid-19 Chatterjee, Partha Dev, Aakash Indian J Labour Econ Article Tracking and analyzing the labour market dynamics at regular, frequent intervals is critical. However, this was not possible for India, a large emerging economy with a significant population undergoing demographic transition, due to a paucity of data. We use the new dataset Centre for Monitoring Indian Economy (CMIE)—Consumer Pyramids Household Survey (CPHS) and use a panel to create Labour Flow Charts and Transition Matrices for India from January 2019 to December 2021. To the best of our knowledge, this is the first time these were created for India. We then use that to look at the impact of Covid-19 on the Indian labour market. We not only look at transitions between employment, unemployment and out of labour force, but also across types of employment—full-time and part-time. The rich data also allows us to consider heterogeneity in the labour market and look at the differential impact of the pandemic across different education groups and gender. From the labour flow charts and transition probabilities, we find that while all groups have been impacted, the magnitude of the impact is different across groups. The recovery is also uneven, and the extent depends on education levels. Further, we do an event study analysis to examine the likelihood of getting a full-time job across different educational and gender groups. Men, on average, enjoy a higher likelihood of getting a full-time job than women. The likelihood coefficients also go up with increasing educational qualifications. Looking at skill heterogeneity, while the likelihood of getting a full-time job either goes down for most groups during the pandemic or the change is minuscule, strikingly it goes up for those with no education, for both men and women. The likelihood coefficients remain elevated for men even after the restrictions are removed, and that for women reverts to the level seen before the pandemic. Finally, this paper provides a way to continuously monitor the dynamics of the labour market as data is released in the regular intervals in the future, which would be of great value for researchers and policymakers alike. Springer India 2023-01-21 2023 /pmc/articles/PMC9862225/ /pubmed/36713957 http://dx.doi.org/10.1007/s41027-022-00420-7 Text en © The Author(s), under exclusive licence to Indian Society of Labour Economics 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 | Article Chatterjee, Partha Dev, Aakash Labour Market Dynamics and Worker Flows in India: Impact of Covid-19 |
title | Labour Market Dynamics and Worker Flows in India: Impact of Covid-19 |
title_full | Labour Market Dynamics and Worker Flows in India: Impact of Covid-19 |
title_fullStr | Labour Market Dynamics and Worker Flows in India: Impact of Covid-19 |
title_full_unstemmed | Labour Market Dynamics and Worker Flows in India: Impact of Covid-19 |
title_short | Labour Market Dynamics and Worker Flows in India: Impact of Covid-19 |
title_sort | labour market dynamics and worker flows in india: impact of covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9862225/ https://www.ncbi.nlm.nih.gov/pubmed/36713957 http://dx.doi.org/10.1007/s41027-022-00420-7 |
work_keys_str_mv | AT chatterjeepartha labourmarketdynamicsandworkerflowsinindiaimpactofcovid19 AT devaakash labourmarketdynamicsandworkerflowsinindiaimpactofcovid19 |