TL;DR
This study analyzes labour market flows and determinants for urban Indian workers using a validated panel dataset from the PLFS, revealing key patterns and factors influencing job transitions.
Contribution
It introduces a novel matching procedure to link PLFS data across years, enabling detailed analysis of labour market transitions in India.
Findings
Documented stylized facts about worker flows
Estimated effects of individual characteristics on job transitions
Validated a data linking method for longitudinal analysis
Abstract
This paper studies gross labour market flows and determinants of labour market transitions for urban Indian workers using a panel dataset constructed from Indian Periodic Labour Force Survey (PLFS) data for the period 2017--18 to 2019--20. Longitudinal studies based on the PLFS have been hampered by data problems that prevent a straightforward merging of the 2017--18 and 2018--19 data releases. In this paper, we propose and validate a matching procedure based on individual and household characteristics that can successfully link almost all records across these two years. We use the constructed data set to document a number of stylised facts about gross worker flows and to estimate the effects of different individual characteristics and work histories on probabilities of job gain and loss.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
