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ECONOMIC SURVEY 2016-17 Summary Chapter 12 – India on the Move and Churning: New Evidence

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Following is the Summary of ECONOMIC SURVEY 2016-17 – Chapter 12 – India on the Move and Churning: New Evidence


  • From ages, the people migrate for work and education and this has brought about structural transformation of economies of countries by distribution of surplus labour from low productive agriculture activity to high productive manufacturing or service sectors.
  • This kind of migration results in remittance flows and the remittances increase the household spending in the less-developed receiving regions. There by decreasing the inequalities
  • Ex: In China, high economic growth rates have been accompanied by mass migration from the rural hinterlands to urban hotspots, mainly along the coast.
  • It was earlier held that the internal migration in India is low (around 33 million) based on 2001 Census, and as not increasing very rapidly. But new methodologies used by economic researchers suggest the contrary evidence that India is on the move, and labour flows are increasing rapidly.

How are the new methodologies used?

  • Cohort-based Migration Metric (CMM) is developed to gauge net migration at the state and district level- which showsless affluent state see more people migrating out while the most affluent states are the largest recipients of migrants.
  • Migration is accelerating- The annual rate of growth of labour migrants nearly doubled to 4.5 per cent per annum in 2001-11 from 2.4 per cent in 1991- 2001.
  • Indians are increasingly on the move – the first-ever estimates of internal work-related migration indicate an annual average flow of close to 9 million people between the states.

What are the important findings of the new study methodologies?

Railway passenger data based migration metric-
Monthly data was obtained from the Ministry of Railways on unreserved passenger traffic between every pair of stations in India for the years 2011-2016;

  • The key idea is to use net annual flows of unreserved passenger travel as a proxy for work-related migrant flow. This class of travel serves less affluent people, who are more likely to travel for work-related reasons.
  • This acceleration has been accompanied by the surge of the economy.
  • Internal political borders impede the flow of people but language does not seem to be a demonstrable barrier to the flow of people.
  • Based on gravity model the labour migrant flows within states are 4 times the labour migrant flows across states, even when the neighbouring district is nearer.
  • A breakdown by gender reveals that the acceleration of migration was more for females.
  • In the 1990s female migration was low, and migrants were shrinking as a share of the female workforce.
  • But in the 2000s the picture turned around completely: female migration for work not only grew far more rapidly than the female workforce, but increased at nearly twice the rate of male migration.
  • Internal migration rates have dipped in Maharashtra and surged in Tamil Nadu, Karnataka and Kerala reflecting the growing pull of southern states in India’s migration dynamics.
  • Out-migration rates increased in Madhya Pradesh, Bihar and Uttar Pradesh.
  • Strong positive relationship between the CMM scores and per capita incomes at the state level.
  • Relatively less developed states such as Bihar and Uttar Pradesh have high net out- migration.
  • Relatively more developed states take positive CMM values reflecting net in- migration: Goa, Delhi, Maharashtra, Gujarat, Tamil Nadu, Kerala and Karnataka.
  • Districts with high net in-migration tend to be city-districts such as Gurugram, Delhi and Mumbai.
  • Districts with high net out- migration are located in the major sending states such as Uttar Pradesh and Bihar.

Figure 1- Average Net Flows at State Level

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Source: Survey Calculations

Figure 1 shows the net flows for the 26 states. Positive (negative) numbers denote in (out)-migration.

  • The largest recipient was the Delhi region, which accounted for more than half of migration in 2015-16.
  • Uttar Pradesh and Bihar taken together account for half of total out-migrants.
  • Maharashtra, Goa and Tamil Nadu had major net in-migration, while Jharkhand and Madhya Pradesh had major net out-migration.
  • India as a whole the annual net flows amount to about 1 per cent of the working age population.  Gravity model for migration

If these are the conclusions, let us find out answers for some questions that may arise from this.

Are these data points verifiable?

  • These data points agree with the Gravity model of Migration.
  • This model is an empirical observation which finds that the migrant/passenger flows between two geographies is directly proportional to the level of economic activity/population of these two geographies and inversely proportional to some measure of physical distance between the two geographies.

What is border-effect on Migration within the country?

  • ‘Border effect’ in the migration, refers to migrant flows between states are lower than flows within states.
  • The estimates suggest that on average flows within states are around four times the flows across states. This coefficient varies between 8 and 2.8 for same-state neighbouring districts vs. same state non- neighbouring districts.

Why is there no language effect on migration within the country?

  • There is little evidence that language is a barrier to the migration flows. When similar analyses are done internationally there is a strong language effect, namely that countries with a common language see larger migrant flows.
  • In trade, the common language effect is estimated to be about 16 to 30 per cent more than countries that do not.
  • But within India, in both trade and labour flows, language doesn’t seem to matter.
  • For example, flows from Gujarat to Tamil Nadu are about 7 lakhs annually. And southern states which don’t speak Hindi much seem to attract more in-migration that other Hindi-belt states.


Dr Ambedkar once said, “An India on the move is an India of churn.”

  • These new estimates, showing that migration within India is between 5 and 9 million annually, indicate that labour mobility in India is much higher than previously estimated.
  • This study predicts an increasing rate of growth of migrants over the years. The numbers show that internal migration has been rising over time, nearly doubling in the 2000s relative to the 1990s.
  • One plausible hypothesis for this acceleration 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.

This acceleration despite problems like domicile provisions for working in different states, lack of portability of benefits, legal and other entitlements upon relocation.

To sustain this churn, however, these policy hurdles have to be overcome by the following measures:-

  • Portability of food security benefits, healthcare, and a basic social security framework for the migrant are crucial – potentially through an interstate self-registration process.
  • While there do currently exist multiple schemes that address migrant welfare, they are implemented at the state level, and hence require inter-state coordination of fiscal costs of migration.
  • The domestic remittances market, exceeds Rs. 1.5 lakh crores growing at an annual rate of 15% p.a, it can also be leveraged to enhance financial inclusion for migrant workers and their families in the source region.

Such measures would vastly enhance the welfare gains of migration and encourage even greater integration of labour markets in India.


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