COVID-19 and the changing profiles of poverty in India: A fuzzy set analysis and imputation approach using PLFS data

Abstract

This paper has the double aim of contributing to the debate on poverty in India by looking at the changing poverty profiles during the pandemic and addressing the challenges posed by the longstanding data limitations for poverty analysis. We use a fuzzy-set methodology to assess the changes in poverty characteristics over time and a stochastic multiple imputation method to enhance the accuracy of the PLFS data. Our analysis encompasses both consumption- and income-based poverty, with a focus on historically marginalised groups such as children and women. We find that the post-shock economic recovery period seems to have bypassed these groups, leaving them struggling to improve their circumstances. In the consumption-based analysis, poverty is rising among larger households and casual labourers, while in the income-based analysis, households with children and working-age women are increasingly affected, with a growing gender disparity and a strong association with low-skilled jobs.