JIANGHAN ACADEMIC ›› 2015, Vol. 34 ›› Issue (5): 96-103.doi: 10.16388/j.cnki.cn42-1843/c.2015.05.013

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Regional Market Integration,Labor Mobility and Income Inequality——Empirical Analysis Based on the Three Provinces in the Middle Reach of Yangtze River

FANG Qi-yun,WU Guang-hao   

  1. School of Economics,Huazhong University of Science and Technology,Wuhan 430074,China
  • Received:2015-08-04 Revised:2015-08-04 Online:2015-10-15 Published:2015-09-29

Abstract: With the deepening of regional cooperation,the regional market integration becomes a trend in the future,but how the regional market integration affects the income inequality is still not very clear. Taking the three provinces in the middle reach of Yangtze River as an example,we use fixed effect panel method and panel quantile regression method to investigate the effects of regional market integration,labor mobility on income inequality. Fixed effect panel estimation results show that the regional market integration,labor mobility is helpful to reduce the income gap. By promoting permanent labor inflow, regional market integration reduces income gap, while temporary labor inflow does not significantly improve income inequality. Panel quantile regression model can reflect the relationship between variables,and the results show that regional market integration,labor mobility may reduce income inequality where income inequality is more obvious. Robustness test shows that previous results are reliable and steady. So,deepening regional market integration, eliminating the administrative and institutional barriers, reforming the household registration system,et al ,to promote permanent inflow of the labor force,it will help to reduce income inequality. On the other hand,the government should take differentiation policies in different areas,actively participate in market integration and eliminating of the institutional barriers which hinder the labor mobility to ameliorate income inequality.

Key words: regional market integration, labor mobility, income inequality, panel quantile regression

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