Migration Reshapes Tribal Livelihoods in West Bengal, Study Finds

For millions of Adivasi households across rural India, the decision to leave home for work has long been framed as a symptom of distress. A new study from West Bengal suggests the picture is more complicated: migration, rather than simply draining villages of their working hands, appears to be a deliberate strategy that reshapes how tribal families earn, diversify, and survive. The research, published in the journal Discover Sustainability, draws on detailed household surveys of 450 Scheduled Tribe families and quantifies, for the first time in this setting, how movement interacts with the portfolio of livelihoods that marginalized rural households assemble.

The study was conducted by Mriganka Dolui and Sanjit Sarkar of the Department of Geography at Central University of Karnataka, who surveyed households across an eastern Indian state between 2023 and 2024. Their central question was deceptively simple: do households that send migrants away build different economic lives from those that stay put? To answer it, the researchers combined a classic tool of ecology, the Simpson Diversification Index, with econometric modeling, treating a family’s income sources the way an ecologist might treat species in a ecosystem—as a portfolio whose balance determines resilience.

The numbers are striking. Migrant households recorded an average Simpson Diversification Index value of 0.420, notably higher than their non-migrant counterparts, indicating a broader spread of income across activities. Nearly four in ten migrant households—39.23 percent—adopted what the researchers call a combination livelihood strategy, mixing farm and non-farm earnings rather than relying on a single source. And across every livelihood category examined, migrant households earned more than non-migrant households, a pattern that challenges the assumption that out-migration necessarily signals household decline.

The statistical core of the paper rests on two models. A multinomial logistic regression was used to estimate how migration status shifts the odds of choosing particular livelihood strategies, while a Tobit censored model handled the bounded nature of the diversification index, which cannot fall below zero. The results showed that migration was associated with a 2.389-fold higher likelihood of pursuing non-farm livelihoods and a 6.502-fold higher likelihood of combining multiple strategies, compared with households that did not migrate. In plain terms, a migrant household was more than six times as likely to juggle several income streams as a comparable non-migrant one.

Migration was not the only lever. The models also identified structural factors that independently shaped diversification. A higher wealth index increased the diversification score by 0.173, access to Self-Help Group assistance added 0.201, and participation in MGNREGA—the national rural employment guarantee scheme—contributed 0.149. These coefficients matter because they point to institutional scaffolding: households plugged into collective savings groups or guaranteed public works were measurably better at spreading their economic bets, regardless of whether anyone in the family had migrated.

The context behind these findings is a landscape of agrarian insecurity. Scheduled Tribe communities in India remain among the most marginalized populations, often holding little or no land and facing limited local employment. When harvests fail or wages stagnate, the household economy has few buffers. The authors frame migration not as a rupture but as one thread in a web of livelihood strategies—a calculated response to structural constraint rather than a pure act of desperation. That reframing carries weight for how policymakers read census and survey data on rural mobility.

Methodologically, the study leaned on bivariate analysis using the chi-square statistic to test associations between migration status and livelihood choices before moving to the multivariate models. The survey instrument captured sociodemographic characteristics—household size, education, landholding, caste and tribal identity—alongside income sources, allowing the researchers to disentangle the effect of migration from the confounding influence of household endowments. The work formed part of a doctoral thesis by the first author, supported by a research fellowship from the University Grants Commission.

The implications reach beyond West Bengal. If migration functions as a diversification engine, then policies that treat out-migration purely as a problem to be curbed may miss the point. Instead, the findings suggest that safe migration corridors, skill development, and portability of social entitlements could amplify the income gains that migrant households already achieve, while Self-Help Groups and employment guarantee schemes provide complementary stability for those who stay. The authors argue that policy efforts and targeted interventions should be integrated to stabilize household income and welfare, rather than addressing migration and rural livelihoods in separate silos.

There are, of course, limits to what a cross-sectional survey of 450 households can establish. The study identifies associations, not causal proof; households that migrate may differ from those that do not in ways the models cannot fully capture. Yet the consistency of the pattern—higher diversification, higher incomes, and a strong statistical association between migration and mixed livelihood strategies—makes a compelling case that mobility and rural development are intertwined rather than opposed. For India’s tribal communities, the road out of the village, the study suggests, may be one of the most important roads into a more secure economic future.

Subject of Research: The relationship between migration and livelihood diversification among Scheduled Tribe households in West Bengal, India

Article Title: Nexus of migration and differentiated livelihood mobility among scheduled tribes in West Bengal

Article References: Dolui, M., & Sarkar, S. (2026). Nexus of migration and differentiated livelihood mobility among scheduled tribes in West Bengal. Discover Sustainability. https://doi.org/10.1007/s43621-026-04968-y

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04968-y

Keywords: migration, livelihood diversification, Scheduled Tribes, West Bengal, Simpson Diversification Index, multinomial logistic regression, MGNREGA, Self-Help Groups, rural livelihoods, India, agrarian insecurity, household income