Vocational opportunities for agricultural migrants in northern India: Insights from grassroots

Abstract

The livelihood of Indian farmers is primarily shaped by agriculture and its allied components. The degree of intricacy and contributions of each agricultural activity, although, vary with different social-ecological systems. Migration is considered an approach to livelihood adaptation; however, the migrants face challenges in new social-ecological settings due to their limited access to resources. This research aimed to develop a predictive model for sustainable agricultural employment options in Rajasthan and Uttar Pradesh (UP). In this study, states were selected purposively, while respondent farmers were chosen using a stratified multistage sampling design. A total of 480 resident and migrant farmers were selected to collect data. The machine learning algorithm, based on classification and regression tree (CART) analysis, was applied that could help to identify factors and prospects for migrant farmers in the agricultural sector. Results indicated that milk yield, operational land holding, and rabi crop yield were significant predictors. Further, milk yield, rabi crop yield, and kharif crop yield were observed to be the essential factors contributing to profitable ventures. The recommendations provided by Krishi Vigyan Kendra’s professionals led to the identification of key income-generating activities, such as livestock management, vegetable production, and organic farming. These prospects are tailored to the location-specific context where migrant farmers reside. Overall, this research shed light on viable employment opportunities, ultimately contributing to the well-being of migrant workers in northern India, in addition to the policy interventions focused on capacity building and providing an enabling environment to the migrants.