Determinants of Saving Behaviour and Financial Vulnerability among Women Gig Workers in Malabar, Kerala: A Logistic Regression Analysis

Muhammed Jamsheer T P *

Department of Economics, Sullamussalam Science College, Areekode, Affiliated to the University of Calicut, Kerala, India.

Noushad Chengodan

Department of Economics, PSMO College (Autonomous), Tirurangadi, Affiliated to the University of Calicut, Kerala, India.

*Author to whom correspondence should be addressed.


Abstract

This study investigates patterns of saving behaviour and financial vulnerability among women gig workers in the Malabar region of Kerala, a state characterised by high female literacy alongside substantial engagement in informal employment. Based on primary data collected from 300 women engaged in diverse gig occupations, the analysis employs descriptive statistics, logistic regression, and complementary log–log models to identify key socio-economic determinants of savings participation and financial vulnerability. The complementary log–log model is used to robustly estimate non-linear effects, thereby enhancing the reliability of the empirical inferences. The results indicate that income stability, financial goals, access to formal financial products, financial literacy, control over finances, and household responsibilities, particularly during financial emergencies, significantly shape the earnings and saving behaviour of women gig workers. In contrast, income volatility, job insecurity, and limited access to credit significantly exacerbate financial vulnerability. The empirical evidence suggests that inclusive finance, tailored financial literacy efforts, and effective social protection play a pivotal role in reducing income instability and enhancing livelihood security among women gig workers.

Keywords: Women Gig workers, savings, financial vulnerability, logistic regression, complementary log–log Model


How to Cite

T P, Muhammed Jamsheer, and Noushad Chengodan. 2026. “Determinants of Saving Behaviour and Financial Vulnerability Among Women Gig Workers in Malabar, Kerala: A Logistic Regression Analysis”. South Asian Journal of Social Studies and Economics 23 (2):58-68. https://doi.org/10.9734/sajsse/2026/v23i21263.

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