NEW WORKING PAPER BY S CHANDRASEKHAR, MUKTA NAIK, SHAMINDRA NATH ROY
URBAN GOVERNANCE MIGRATION

Beyond summing up salient migration trends from existing data sources; a new working paper by researchers from Centre for Policy Research and Indira Gandhi Institute for Development Research (IGIDR) builds on a critique of the estimations made by the Economic Survey 2017 to outline fresh ideas for developing leading indicators that will help inform policy. This is particularly needed because even as Indian policymakers are increasingly recognising the linkages between migration, labour markets and economic development, the lack of frequently updated datasets limits our understanding of migration.

We recognise the contribution of the Economic Survey in using innovative approaches to measure migration, viz. the age cohort metric that tracks age-cohorts across census periods and the measurement of mobility through the sale of unreserved railway tickets. However, we also see limitations – for instance, the high levels of work-related movement outlined in the Survey seems to be at odds with the challenges India is facing with job creation and also incongruent with indicative data from Census 2011 that shows a decline in the importance of work in the reasons for migration. These inconsistencies need additional exploration.

The relatively low estimation of migration by the first method (Census 2011) and the higher estimation by the second (Economic Survey 2017) speaks to discrepancies in how we define and understand different kinds of mobilities and migration in the country. For instance, we discuss how the high levels of seasonal migration and commuter movement revealed by analysing Census and NSSO (National Sample Survey Office) data demands urgent policy response especially on transportation and mobility. In fact, given relatively stable geographies of migration in India, receiving states can leverage data to evolve migrant-inclusive policies with a focus on cities, which are increasingly important destinations for migrants. These may require specific interventions in affordable housing, transport, basic services, political inclusion, skilling and livelihood. Moreover, portability of social benefits for inter-State migrants is an urgent area where inter-State mechanisms need to be strengthened.

Following the Economic Survey’s effort, we contend that the exercise of improving data on migration and commuting need not be restricted to revamping government surveys. Innovative ways of improving collecting information and tracking movement could include leveraging administrative data collected by the government through digital databases ranging from sources like birth and death registrations to scheme-related data. Ticket sales data from state road transport corporations, especially on routes where daily commuting is the norm, would be particularly useful for commuting-intensive destinations. Trails of ‘big data’ left by user transactions and digital activity, particularly mobile phone usage, are also areas that must be explored, subject to privacy considerations. Triangulating multiple datasets is important to improve data-driven policy reforms that can help India plan for those individuals who change locations permanently as well as those who move seasonally.

The thinking for this paper has emerged from the extensive work on migration done under the Strengthen and Harmonize Research and Action on Migration (SHRAMIC) initiative supported by the Tata Trusts, in which IGIDR, CPR and the National Institute of Urban Affairs (NIUA) have been involved as knowledge partners. Further, many insights emerge from the authors’ involvement, in the capacity of members and research support, with the Working Group on Migration established by the Ministry of Housing and Urban Affairs (MoHUA), Government of India and chaired by Partha Mukhopadhyay at CPR. Further impetus for the paper was provided by robust discussions on migration estimates fuelled by innovative approaches used in the Economic Survey 2017. The Economic and Political Weekly has recently accepted this paper for publication.