New
estimates of labour migration in India have revealed that inter-state labor
mobility is significantly higher than previous estimates. This was stated in
the Economic Survey 2016-17 presented by the Finance Minister Shri Arun Jaitley
in the Parliament today. The study based on the analyses of new data sources
and new methodologies also shows that the migration is accelerating and was
particularly pronounced for females. The data sources used for the study are
the 2011 Census and railway passenger traffic flows of the Ministry of Railways
and new methodologies including the Cohort-based Migration Metric (CMM) .
The new Cohort-based
Migration Metric(CMM) shows that inter-state labor mobility averaged 5-6.5
million people between 2001 and 2011, yielding an inter-state migrant
population of about 60 million and an inter-district migration as high as 80
million. The first-ever estimates of internal work-related migration using
railways data for the period 2011-2016 indicate an annual average flow of close
to 9 million migrant people between the states. Both these estimates are
significantly greater than the annual average flow of about 4 million suggested
by successive Censuses and higher than previously estimated by any study.
Figure 1. Estimates of
annual migrant flows based on railway traffic data
The second finding from this new study
is that migration for work and education is accelerating. In the period
2001-2011 the rate of growth of labour migrants nearly doubled relative to the
previous decade, rising to 4.5 per cent per annum. Interestingly, the
acceleration of migration was particularly pronounced for females and increased
at nearly twice the rate of male migration in the 2000s. There is also a
doubling of the stock of inter-state out migrants to nearly 12 million in the
20-29year old cohort alone. One plausible hypothesis for this acceleration in
migration is that the rewards (in the form of prospective income and employment
opportunities) have become greater than the costs and risks that migration
entails. Higher growth and a multitude of economic opportunities could
therefore have been the catalyst for such an acceleration of migration.
Third, and a
potentially exciting finding, for which there is tentative but no conclusive
evidence, is that while political borders impede the flow of people, language
does not seem to be a demonstrable barrier to the flow of people. For example,
a gravity model indicates that political borders depress the flows of people,
reflected in the fact that migrant people flows within states are 4
times than migrant people flows across states. However, not sharing Hindi as a common language appears not to create
comparable frictions to the movement of goods and people across states.
Fourth, the patterns of
flows of migrants found in this study are broadly consistent with what is
expected - less affluent states see more out migration migrating out while the
most affluent states are the largest recipients of migrants. Figure 2 shows the
strong positive relationship between the CMM scores and per capita incomes at
the state level. Relatively poorer states such as Bihar and Uttar Pradesh have
high net out-migration. Seven states take positive CMM values reflecting net
in-migration: Goa, Delhi, Maharashtra, Gujarat, Tamil Nadu, Kerala and
Karnataka. Fifth, the costs of moving for migrants are about twice as much as
they are for goods – another confirmation of popular conception.
Figure 2. Cohort-based
Migration Metric vs. Real Incomes across States
Policy
actions to sustain and maximize the benefits of migration include: ensuring
portability of food security benefits, providing healthcare and a basic social
security framework for migrants – potentially through an inter-state
self-registration process. While there do currently exist multiple schemes that
have to do with migrant welfare, they are implemented at the state level, and
hence require greater inter-state coordination.
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DSM/NT/AD/RK