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Impact of COVID‐19 Shock on a Segmented Labor Market: Analysis Using a Unique Panel Dataset

Author

Listed:
  • Satadru Das
  • Saurabh Ghosh
  • Debojyoti Mazumder
  • Jitendra Tushavera

Abstract

This article studies and quantifies the impact of COVID‐related shock on segmented labor market by using Periodic Labour Force Survey of India. We employ transition matrices, cumulative distribution functions, and machine learning techniques. We find that labor market outcomes, both in terms of employment status and income, became even more divergent between the formal and informal sectors during the first wave of pandemic and remained divergent in the recovery phase. The classification analysis highlights that the sector in which the worker was employed (formal or informal sector) was an important predictor of income loss during the first wave. Additionally, the decline in income was influenced by individual and household‐level characteristics, whereas the recovery is explained by aggregate characteristics, like state of residence, industry and occupation classification, and employment status.

Suggested Citation

  • Satadru Das & Saurabh Ghosh & Debojyoti Mazumder & Jitendra Tushavera, 2025. "Impact of COVID‐19 Shock on a Segmented Labor Market: Analysis Using a Unique Panel Dataset," Bulletin of Economic Research, Wiley Blackwell, vol. 77(4), pages 477-500, October.
    • Handle: RePEc:bla:buecrs:v:77:y:2025:i:4:p:477-500
    DOI: 10.1111/boer.12500
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    References listed on IDEAS

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