Understanding Labor Market Dynamics in Urban India Amidst the Pandemic: A Study Employing Supervised Learning Methods

Title

Understanding Labor Market Dynamics in Urban India Amidst the Pandemic: A Study Employing Supervised Learning Methods

Creator

Singha Roy N.; Ghosh N.

Description

This study provides insights into the dynamic job ladder and challenges in the Indian labor market, particularly when facing external shock. It examines the fluidity of job transitions among the employed, unemployed, and those not in the laborforce, focusing on the urban labor market of India during the COVID-19 pandemic. Using data from the 2020-21 Periodic Labour Force Survey, a longitudinal panel dataset was created to track individuals across four quarters, enabling the monitoring of their activity status. Employing K-Nearest Neighbour classification, the study identifies vulnerabilities in labor market engagement. It further explores factors driving transitions among the three states of labor market involvement, using a multinomial logistic model adjusted for selection bias. The research reveals significant movement within the labor force, with notable shifts between employment statuses. Even those currently employed are often vulnerable, at risk of detachment from the labor force at any time. Women were disproportionately affected, with evidence of discouraged worker effect, as many ceased jobs search duo to perceived job scarcity or unavailability of decent jobs. The study raised concerns about the sustainability of self-employment and the security of regular jobs. These findings expose enduring structural challenges exacerbated by the pandemic, calling for urgent action to address widespread unemployment, low female participation, and prevailing inequalities in the labor market. The Author(s), under exclusive licence to The Indian Econometric Society 2024.

Source

Journal of Quantitative Economics, Vol-22, No. 4, pp. 883-909.

Date

2024-01-01

Publisher

Springer

Subject

COVID-19; Employment; KNN algorithm; Labor market transition; Multinomial logistic regression; Urban India

Coverage

Singha Roy N., Department of Economics, Christ University, Hosur Road, Bengaluru, 560029, India; Ghosh N., Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 9711554

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1007/s40953-024-00413-x

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