Analysis of the Determinants of Income and Income Gap between Urban and Rural China
AbstractThis paper studies on the determinants of income and urban-rural income gap to shed light on the problem of urban-rural income inequality in China. OLS, conditional quantile regression and Blinder-Oaxaca decomposition methods are used to analyze four waves of the China Health and Nutrition Survey (CHNS) household data. Results show that education and occupation are essential determinants of households' income level. These two factors exert heterogeneous effects at different percentiles of the income distribution. In urban areas, education is more valued for high income earners, while for rural areas, specialized or tertiary education are more beneficial for the poorer households. Among all occupational types, farm activities show much lower returns than other types; and this is more evident for individuals at the left tail of the income distribution. We also find that for the sampled provinces, urban-rural income gap increases from the year of 2000 to 2004 but the gap decreases from 2004 to 2009. The income gap can be largely explained by the individuals' attributes, especially by level of education and type of occupation.
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Bibliographic InfoPaper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 7162.
Length: 28 pages
Date of creation: Jan 2013
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Find related papers by JEL classification:
- O15 - Economic Development, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
- O18 - Economic Development, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
- D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
- D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
This paper has been announced in the following NEP Reports:
- NEP-AGR-2013-02-16 (Agricultural Economics)
- NEP-ALL-2013-02-16 (All new papers)
- NEP-DEV-2013-02-16 (Development)
- NEP-LMA-2013-02-16 (Labor Markets - Supply, Demand, & Wages)
- NEP-PBE-2013-02-16 (Public Economics)
- NEP-TRA-2013-02-16 (Transition Economics)
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