Exploring Income-Linked Disparities in Social Security Access among Women Gig Workers in Kerala, India: Evidence from Logistic Regression Analysis

Abstract

This study examines the factors influencing access to social security among women gig workers in the Malabar region of Kerala, India. It focuses on socioeconomic, demographic, and occupational characteristics that may affect such access. Primary data were collected from 300 women gig workers in the districts of Kannur, Kozhikode, and Malappuram. A snowball sampling method was used to reach respondents because gig workers are widely dispersed and largely part of the unorganized workforce. Logistic regression analysis was applied to identify the key factors affecting access to social security, and chi-square tests were used to examine the association between selected variables and access outcomes. The results show that, among the variables included in the model, only monthly family income has a statistically significant influence on access to social security. However, the explanatory power of the model is relatively low, accounting for only 3.26 percent of the variation in social security access. These findings highlight the limited coverage of social protection among women gig workers and underline the need for targeted policy measures to improve labour welfare and social protection. By providing empirical evidence on income-related differences in access to social security, the study adds to the growing literature on vulnerabilities within the gig economy, particularly among women engaged in informal employment.