Migrant workers in urban labour markets in India: wage differentials, assimilation and occupational attainment

Abstract

The paper examines the wage differentials and returns to human capital of migrant and non-migrant workers in the urban labour markets in India. Using unit-level data from the Employment, Unemployment and Migration Survey (2007)(2008), the regression analysis examines the effect of various factors particularly human capital and years since migration in determining wage differentials in different specifications. The results showed that the migrants (both rural and urban) earned higher daily wages than non-migrant workers across states, but the wage advantage was higher for urban migrants than rural migrants both in regular and casual work. Segregating the wage gap into different observable factors, the results showed that the migrant wage advantage was mainly explained by the difference in nature of employment, type of occupation, location of job and other socio-religious factors but not due to differences in human capital. However, in case of urban migrants, education plays a major role in explaining the wage advantage over non-migrants, particularly in regular wage work. Even though the migrants showed a higher wage advantage, the gap reduced with the duration of stay at the destination labour market. While modelling the occupational attainment among migrants and non-migrants, the study found that education plays an important role in enabling migrants, especially urban migrants, get access to higher-paying occupations.

Consequences of Labour Migration on Wages and Employment: Evidence from India

“…Economic migrants are largely working-age men who move from rural to urban areas and within urban areas. These migrants are relatively well off, better educated and belong to higherpaying occupations than non-migrant workers at the destination (Hnatkovska and Lahiri 2015;Khan 2016Khan , 2017Kundu and Saraswati 2012;Vakulabharanam and Thakurata 2014).…”

“…Khan (2016) examined the wage differentials between migrants and non-migrants using the quintile decomposition method and found that most of the migrant wage advantage is because of the difference in observable characteristics. The migrant wage advantage is seen not only in the case of formal employment but also among informal workers across industries in the urban labour markets in India (Khan 2017;Srivastava 2011). The descriptive statistics suggest that migrants are more likely to be highly educated, have migrated to places with higher average per capita incomes and highskill regions, and are less likely belong to socially disadvantageous groups.…”

“…If this argument holds, then migrants would be working at lower wages. But recent evidence suggests that migrants earn higher wages in casual wage work and have a lower unemployment rate than non-migrant workers (Khan 2016(Khan , 2017. This indicates that there is a preference for migrant workers over local workers in the informal sector possibly for their discipline, motivation, and work intensity.…”

Mental health assimilation of rural–urban migrants in developing countries: Evidence from Indonesia's four cities

“…Among others are Meng and Gregory (2005), Breunig et al (2013), Abramitzky et al (2014) and Pakrashi and Frijters (2017). Some of this assimilation literature is on cases of internal migration (Ge, 2017;Khan, 2017). However, few studies have observed the mental health consequences of migration (de Maio & Kemp, 2010;Lerner et al, 2005;Lu, 2010aLu, , 2010b.…”

“…In the context of internal migration, people tend to move from low‐wage home labour markets, typically in rural areas, to high‐wage destination labour markets, typically in urban areas (Chauvin et al, 2017; Gollin et al, 2014). The convergence of earnings between rural–urban migrants compared to those of the urban population (non‐migrants), or the rural–urban migrants' economic assimilation process, is of great interest in the discourse of social and economic mobility of migrants in developing nations (Effendi et al, 2010; Khan, 2017; Qu & Zhao, 2017).…”