Employment Type, Gender, and Earnings Inequality among Rural Agricultural Workers in Telangana: A Cross-sectional Data Analysis

Ramavath Kavitha, Syam Prasad and Mudavath Paramesh
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Ramavath Kavitha: Department of Economics, Central University of Kerala, Kasaragod, Kerala, India.
Syam Prasad: Department of Economics, Central University of Kerala, Kasaragod, Kerala, India.
Mudavath Paramesh: Department of Public Administration and Policy Studies, Central University of Kerala, Kasaragod, Kerala, India.

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Abstract: Aims: This study examines earnings inequality among rural agricultural workers in Telangana by analysing the associations of employment type, gender, age, and education with monthly labour earnings. Study Design: Cross-sectional quantitative study. Place and Duration of Study: The study uses unit-level data from the Periodic Labour Force Survey (PLFS) 2023–24 conducted by the Ministry of Statistics and Programme Implementation (MoSPI), Government of India. Methodology: The study analyses rural agricultural workers engaged in self-employment and casual labour. Monthly labour earnings were classified into three mutually exclusive categories: Zero Earnings, ₹1–5,000, and above ₹5,000. Multinomial Logistic Regression, Average Marginal Effects, and Predicted Probability analyses were employed to examine the associations between individual characteristics, employment type, and earnings outcomes. Results: Employment type exhibited the strongest association with earnings outcomes. Compared with self-employed workers, casual labourers had substantially higher odds of being in both the ₹1–5,000 category (β = 4.138, p < 0.001) and the Above ₹5,000 category (β = 4.120, p < 0.001), relative to the Zero Earnings category. Senior workers had significantly lower odds of earning above ₹5,000 than younger workers (β = −1.211, p < 0.01). Higher education was negatively associated with the ₹1–5,000 and above ₹5,000 categories. Gender was significantly associated with the ₹1–5,000 category, while the gender difference in the Above ₹5,000 category was not statistically significant at the 5 per cent level. Predicted probabilities further indicated that employment type was more strongly associated with the probability of earning above ₹5,000 than gender. Conclusion: The findings show that employment type has a stronger association with earnings than gender among rural agricultural workers in Telangana. The study highlights the need to strengthen income security for self-employed and unpaid family workers, expand productive employment opportunities, and improve access to social protection. These findings are consistent with Labour Market Segmentation Theory and provide useful policy insights for promoting inclusive rural development in Telangana.

Date: 2026-08-21
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Published in Journal of Global Economics, Management and Business Research, 2026, 18 (3), pp.291-307

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05723855

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