Multidimensional Poverty Among Women Informal Workers: A Comparative Occupational Analysis

Women working in informal sector jobs represent the most vulnerable group in urban labor markets of developing countries, but poverty among them is not fully addressed through income-based measurements. To assess poverty using an MPI based on the Alkire-Foster approach, we consider poverty along eight aspects, including education, health, housing and environment, job insecurity, financial inclusiveness, social protection, food security, and social exclusivity, with regard to 600 informal female workers from Lucknow, Uttar Pradesh, India. Stratified random sampling method was used to select the target population, which consists of four occupational groups: domestic workers (n = 150), street vendors (n = 150), construction workers (n = 150), and rag-pickers (n = 150). Both quantitative and qualitative approaches were employed, using descriptive analysis, MPI calculation, PCA, Chi-square tests, one-way ANOVA, binary logistic regression, and NVivo software. The results show that rag‑pickers have the highest prevalence (H = 79.3%) and depth (A = 58.6%) of multidimensional poverty, giving them an MPI score of 0.465, followed by domestic workers (MPI = 0.312), construction workers (MPI = 0.398), and street vendors (MPI = 0.341). There is evidence of a statistically significant difference in MPI across the occupations through the ANOVA test, where F = 42.87 and p < .001. From the logistic regression analysis, illiteracy (β = 1.843), lack of social security (β = 1.621), non-availability of credit (β = 1.354), and migration (β = 1.197) are found to be strong predictors of multidimensional poverty. It shows how structural discrimination of women, stigmatization of occupation, and social exclusion perpetuate poverty.