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Abstract/Description
Pakistan has a total labor force of 65.5 million in 2019. According to the Labour Force Survey 2017-18, more than one-third of the labor force is working in urban areas, and one-tenth comprises rural-urban migrants. It is evident that rural-urban migration increases labor supply in the urban labor market and consequently causes a reduction in wages, particularly for unskilled and semi-skilled workers. This study makes the first attempt to evaluate the wage gap among urban native and rural-urban migrant workers using a sample of 12,302 workers, comprising 10,793 urban natives and 1,509 rural-urban migrants, extracted from the latest Labour Force Survey, 2017-18. The paper uses exploratory data analysis to explore the economic and socio-demographic characteristics (i.e., age in years, working hours, gender, marital status, education, sector of employment, and occupation) of urban-native and rural-urban migrant workers. It uses Conditional Quantile Regression to examine the wage gaps between urban-native workers and rural-urban migrants. Previous studies have used the Ordinary Least Square to analyze wage gaps across gender, occupation, and sectors in Pakistan. However, the OLS is sensitive to outliers, while Quantile Regression is a robust estimation technique. Preliminary findings indicate substantial differences in the mean wages among the natives and rural-urban migrants in the industrial and services sectors. The native-urban managers earn higher incomes at all percentiles in the distribution. Within-group inequality confirms lower earnings for female workers than the male, irrespective of their migration status. However, the gender wage gap decreases at higher percentiles in both groups. Education offers positive returns for both groups (native and rural-urban migrants) throughout the wage distribution. The uneducated urban-natives earn more than their rural-urban migrant counterparts, while the reverse holds for the educated urban. The results may be used to tailor policies that ensure effective implementation of minimum wages, job security for vulnerable workers such as rural-urban migrants and women, and an equal chance of participation in the skill development programs for all workers.
Keywords
Conditional quantile regression, Exploratory data analysis, Minimum wages, Urban labor market, Rural-urban migrant, Wage Gap
Session Theme
Sustainable Energy and Urbanization - Session - IIIA
Session Type
Parallel Technical Session
Session Chair
Dr. Samina Khalil, Director – AERC, University ofKarachi
Session Discussant
Dr. Heman Das Lohano, Professor - IBA Karachii
Start Date
3-4-2021 4:00 PM
End Date
3-4-2021 5:30 PM
Recommended Citation
Umair, M., & Naz, L. (2021). Wage Gap among urban natives and rural-urban migrants in Pakistan. CBER Conference. Retrieved from https://ir.iba.edu.pk/esdcber/2021/day2/18
Wage Gap among urban natives and rural-urban migrants in Pakistan
Pakistan has a total labor force of 65.5 million in 2019. According to the Labour Force Survey 2017-18, more than one-third of the labor force is working in urban areas, and one-tenth comprises rural-urban migrants. It is evident that rural-urban migration increases labor supply in the urban labor market and consequently causes a reduction in wages, particularly for unskilled and semi-skilled workers. This study makes the first attempt to evaluate the wage gap among urban native and rural-urban migrant workers using a sample of 12,302 workers, comprising 10,793 urban natives and 1,509 rural-urban migrants, extracted from the latest Labour Force Survey, 2017-18. The paper uses exploratory data analysis to explore the economic and socio-demographic characteristics (i.e., age in years, working hours, gender, marital status, education, sector of employment, and occupation) of urban-native and rural-urban migrant workers. It uses Conditional Quantile Regression to examine the wage gaps between urban-native workers and rural-urban migrants. Previous studies have used the Ordinary Least Square to analyze wage gaps across gender, occupation, and sectors in Pakistan. However, the OLS is sensitive to outliers, while Quantile Regression is a robust estimation technique. Preliminary findings indicate substantial differences in the mean wages among the natives and rural-urban migrants in the industrial and services sectors. The native-urban managers earn higher incomes at all percentiles in the distribution. Within-group inequality confirms lower earnings for female workers than the male, irrespective of their migration status. However, the gender wage gap decreases at higher percentiles in both groups. Education offers positive returns for both groups (native and rural-urban migrants) throughout the wage distribution. The uneducated urban-natives earn more than their rural-urban migrant counterparts, while the reverse holds for the educated urban. The results may be used to tailor policies that ensure effective implementation of minimum wages, job security for vulnerable workers such as rural-urban migrants and women, and an equal chance of participation in the skill development programs for all workers.
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