The high rural-urban wage gap in India

Kaivan Munshi and Mark Rosenzweig examined the low rate of rural-to-urban migration in India and find rural insurance markets as responsible for keeping adult males in villages. They point to the significantly slower growth of urbanization in India compared to countries like China, Indonesia, and Nigeria. In fact, India's urbanization rate is about 15% lower than countries with similar GDP per capita.

Focusing on workers with less than primary education (who are likely to perform similar menial tasks in both rural and urban areas) to avoid confounding effects of returns to education, they find,

The wage gap for India, at over 45%, is actually much higher than the corresponding gap for the other two countries, which is about 10%. One reason why urban wages are higher than rural wages is because the cost of living is higher in urban areas. When we account for these differences in the cost of living, the Indian wage gap declines to 27%. Although the Chinese and Indonesian data do not allow us to make the same adjustment, the nominal wage gap in these countries serves as an upper bound for the real wage gap because urban prices will always be higher than rural prices. It follows that the real wage gap in India is at least 16 percentage points larger than it is in China and Indonesia. There is evidently some friction that prevents rural Indian workers from taking advantage of more remunerative job opportunities in the city

The authors attribute the friction to informal rural insurance networks which draw strength from social capital and threats of social sanctions in tightly knit rural communities, 

The explanation that we propose for India’s low mobility is based on a combination of well-functioning rural insurance networks and the absence of formal insurance, which includes government safety nets and private credit. When an insurance network is active, households that receive a positive income shock provide a transfer (in cash or kind) to one or more households in the network that receive a negative shock. This smooths the consumption of each household over time, making risk-averse households better off. In rural India, informal insurance networks are organized along caste lines...  Frequent social interactions and close ties within the caste, which consists of thousands of households clustered in widely dispersed villages, support very connected and exceptionally extensive insurance networks.

An undoubted role for social insurance in mobility frictions apart, there are at least a few confounding factors and (not water-tight) assumptions that come in the way of identifying causal mechanisms. For example, the higher income families, independent of caste, are more likely to be socially aspirational and, therefore, more likely to migrate, irrespective of the strength of caste links or the marginal utility of attendant social insurance. 

There are potentially other compelling hypotheses about such frictions. Fundamentally, it may not be unreasonable to argue that there are social/behavioural and economic factors that contribute to the friction. Apart from the loss of social insurance, the former may include a high level of social inertia, by itself - people just prefer to stay in the comfort zones of their community. There may be differences in the nature and conditions of similarly placed jobs in rural and urban areas (rural jobs of the same kind may be less demanding and, therefore, less productive) and in the general quality of life for those with similar incomes. The latter may include the lack of affordable housing, loss of welfare benefits, and so on. It is most likely that all these factors interact in a complex manner, with wide variations in their dynamics based on the socio-economic contexts, to generate the frictions that retard migration to urban areas. 

We need to examine interventions that can potentially relax these factors. For example, better transportation networks may lower the social inertia and encourage migration. Similarly, a portable social insurance mechanism (through Aadhaar) may lower the economic cost of migration. In any case, policies to bridge the high rural-urban wage gap documented in the paper can be very powerful income growth-boosters.