The Invisibles: Towards a Seasonal Migration Atlas of India

This report presents findings from the first year of a study to develop a Seasonal Migration Atlas of India. The Atlas seeks to (i) generate macro estimates of seasonal migrant workers at the state and national levels and (ii) document major migration streams. The groups whose numbers the Atlas seeks to capture are the seasonal or circular migrants and the semipermanent or long-term circular migrants. Seasonal or circular migrants comprise individuals, or groups of individuals, who migrate for temporary periods, either moving from place to place or to a fixed destination. Semi-permanent or long-term circular migrants comprise individuals who migrate for comparatively longer periods year after year, often to the same work place, and then revert back to the areas of their origin after their work life is over.

This phase of the research has used data generated on the number of workers who went back to their home states during the first phase of COVID lockdowns as a shadow indicator to estimate state level figures of seasonal migrant workers. It is assumed that the majority of the people who were stuck during the lockdowns and went back to their home states comprised seasonal migrants as described above. This data has been backed up by older state level profiles and case studies at the district and sub -district levels wherever available.

Through a series of compilation exercises and exhaustive desk research, the research team estimates that approximately 13.5 million workers returned to their home states during the first phase of COVID. The number of workers who left their destination states is approximately 14.6 million. While there is a slight mismatch between these two sets of figures, the high degree of congruity between them shows that the figures derived from various sources for incoming and outgoing workers proves to the veracity of data and approach adopted.

The state-wise estimates of migrant workers are also in agreement with the existing literature on seasonal migration patterns. The data set shows that the Eastern parts of the country – comprising Eastern Uttar Pradesh, Bihar, Jharkhand, West Bengal, and Odisha – are the largest source of migrant workers. The states of Maharashtra and Gujarat form the largest recipient states followed by the Northern cluster of NCR – Punjab and the cluster of Southern states – Kerala, Tamil Nadu, Karnataka, and Telangana.

The use of the shadow indicator – travellers during the lockdowns in the first phase of COVID, is constrained by certain limitations, some that were obvious and some that emerged after the data compilation exercise. The travellers included other categories besides migrant workers and there is a possibility that all the migrant workers did not go back. The data does not seem to have captured short distance and intra state migrants, which would include migrant agriculture workers. Moreover the huge exodus immediately after the announcement of the first lock down has not been captured in this set of data.

In carrying forward this project, it was necessary to develop a network of partners comprising field-based agencies and research organizations. The Centre for Labour Research and Action (CLRA) reached out to several such organizations in the major sending- and receivingstates, and got positive responses from seven of these organizations. These include Gram Vaani in Delhi and Bihar, Centre for Migration and Inclusive Development in Kerala, Partnering Hope Into Action (PHIA) Foundation Jharkhand, Youth for Unity and Voluntary Action (YUVA) in Maharashtra, Gram Vikas in Odisha, Samaj Pragati Sahyog in Maharashtra and Madhya Pradesh, and Community Awareness Research and Education Trust (CARE-T) in Tamil Nadu.

The Atlas project will continue working on this topic over the coming years, with attention to the major gaps that have emerged in this data set. These include the estimation of short distance intra-state migrants, mapping out of large tribal clusters of seasonal migrants in Central West India, development of state level profiles of seasonal migrants, and gender segregation of data.