Study On The Determinant And Evolution Of Provincial Labor Income Share In China

The past30years witness a great change in China’s economy since China made the reform and opening-up into practice. However, the labor income share is decreasing persistently with the rapid development of China, and the trend of decreasing is even more dramatic recent years, which is not in accordance with now’s rapid growing. Labor income share may influence the structure of income distribution and the achievement of economic growing. The17th National Congress of CPC stressed the great need of improving progressively the ratio of income to national income distribution and augment the ratio of labor share to primary distribution. The study of China’s labor income share is closely connected with the economic growing which is meaningful and worthwhile. In this study, we pick the determinant of labor income share and its evolution as our starting point, and then review the literature, put forward the problems, and give a detailed analysis of China’s labor income share using the provincial data.Firstly, we identify the determinant of labor income share using the cutting-edge nonparametric variable detection method. It conludes that labor income not only depends on the production factor, but has a close relationship with the institutional and policy factors. While the institutional and policy factors influence the labor income with constraint more than just promotion, and the influencing mechanism manifests the transition from simple linear to complicated nonlinear.Secondly, we build the labor income share nonparametric varying-coefficients model from the factor contribution side, and identify the movement of labor income share under the policy of trade and industry structure. We find that the influence of trade to labor income share varies from different economic regions, even the trade policy is not significant in the second economic region; the influence of industry to labor income share is positive in general but varies from different regions as well, and the influence of industry in the third economic region is piecewise.Thirdly, we build the labor income share evolution nonparametric varying-coefficients model and identify the path of technical progress, trade and industry to the turning points, meanwhile we construct a Bootstrap statistic to test the real condition evolution in different regions. The empirical analysis tells us that different regions have different turning points and the GDP per capita of22000yuan,13400yuan and6600yuan is the turning points of each region; The influence of technical progress, trade and industry is negative in some extent, the technical progress is negative in the third economic region, trade is negative in the first and second economic region and industry is negative in the second economic region. The statistic test indicates the third economic region has already reached the underlying turning points, but the first and second have not.Lastly, we put forward the policy simulation according to the empirical analysis above. The simulation recommends that, improving the ratio of tertiary industry about10%is advisable in the first economic region, improving the ratio of secondary and tertiary industry altogether about5%is advisable in the second economic region and improving the ratio of secondary industry about15%is advisable in the third.