On Income Inequality in Urban Areas in China During the Period 2002–2013: Comparing the Case of Urban Locals With That of Rural Migrants

To explore income inequality in urban China, this paper investigates disparities between- and within-urban locals and rural migrants from 2002 to 2013, using three waves of the China Household Income Project (CHIP) data. While the existing literature concentrates on the wage disparity between these two groups, our results show that the Gini among the migrants increased by 17.86% between 2007 and 2013 and that among the locals increased by 15.54% from 2002 to 2007. The urban–migrant average income gap decreased during the whole period mainly due to higher growth in migrants’ average income. Estimates based on Mincerian earnings functions for both groups reveal the significant role of the education, occupation and type of contract in determining the within-group inequality. In addition, using a recentred influence function (RIF), we observe that short-term and other types of contracts, duration of the job, in-system ownership, marriage and skill have inequality-enhancing effects for migrants. The variation of skills has a larger impact on the income disparity among migrants than on that among urban locals. The RIF-based Blinder–Oaxaca decomposition of the mean difference of incomes shows that labour market discrimination between the two groups is not significant; however, both pure explained and unexplained differences are significant when applying the RIF decomposition to the variance of the logarithms of incomes. While the type of contract significantly reduces the pure explained difference between migrants and urban locals, occupation has a positive impact on this difference between these two groups. The heterogenity analysis shows that the factors influencing incomes in these two groups are different. We recommend labour market intervention to reduce unreasonable occupational and sectoral disparities, especially in the net inflow provinces, to mitigate urban inequality in China effectively.