From Low to High Participation: Understanding the Increase in Female Workforce Participation in Assam

Abstract

Background: Economic growth and improvements in education, female workforce participation in Assam remains shaped by rural–urban disparities, socio-economic factors, and structural labour market challenges, necessitating an analysis of its trends and determinants. Aims: The study examines the trends, patterns, and determinants of female workforce participation in rural and urban Assam and tests the validity of the U-shaped hypothesis in this context. Study Design: Assam, identified as a lower-performing state under Sustainable Development Goal 5 (related to gender equality and women empowerment) in the SDG India Index 2020-21, is selected for the present study. The study utilizes unit-level data from the National Sample Survey Organisation (NSSO) Employment and Unemployment Survey (EUS) 2011-12 and the Periodic Labour Force Survey (PLFS) 2017-18 and 2023-24. Methodology: The female Workforce Participation Rate (WPR) is used as the main indicator of labour market participation. It is calculated as the percentage of female workers to the total female population in the corresponding age group. The analysis is carried out using the usual status (principal and subsidiary status) approach. Since the dependent variable is binary, a logit regression model has been used to examine the determinants of female workforce participation. Results: The findings show a substantial increase in female workforce participation in Assam during the recent period, with the rise being more pronounced than the national average. The increase is observed in both rural and urban areas, although rural areas continue to record higher participation. In contrast, male workforce participation shows relatively stable trends over time. Sector-wise trends show that female workforce participation is higher in rural areas than in urban areas. The study also finds a U-shaped relationship between education level and female WPR in Assam across all periods, with higher participation among illiterate and highly educated women than among women with middle levels of education. Logit regression results show that age, education level, vocational training, spouse employment status, and the number of elderly increased female workforce participation, while age squared, heads’ education and household size are negatively related to female workforce participation.