Study On The Growth Mechanism Of Minimum Wages In China Based On The Perspective Of Spatial Statistics

The minimum wages aims to protect the legal rights of the low-income people and provide a way for laborers to share the result of the development of economy.However,the growth mechanism of minimum wages is the effective way of implementing the minimum wages and is the precondition of a harmonious labor relationship.The ELES model is utilized to measure the minimum wages standard of the 35 large cities,meanwhile,a dynamic model is used to adjust the result,which helps to explore inner discipline of the growth mechanism of minimum wages.The spatial-temporal nonstationarityof the growth mechanism of minimum wages is evident because of the regional differences.Based on the provincial panel data from 2006 to 2014,this paper uses exploratory spatial method to analyze spatial autocorrelation of the minimum wage.The weighted autoregressive models,which can eliminate spatial autocorrelation,are adopted to explore the evolution of the growth mechanism of minimum wages.Temporally Weighted Regression(TWR)? Geographically Weighted Regression(GWR)and Geographically and Temporally Weighted Regression(GTWR)were used to measure spatial-temporal nonstationarity of the growth mechanism of minimum wages.The empirical results show the results as follow.The current minimum wages standard in China is low and varies from different areas.The proportion of the minimum wages standard and the average wages is not suitable for our anticipation,so are the proportion of the minimum wages standard and the per capita GDP.In the global perspective,the minimum wage shows positive spatial autocorrelation.The partial results of spatial autocorrelation analysis show that the growth of minimum wage in one area has no positive effect on the surrounding areas.The empirical analysis shows that family burden,salary,employment and human resource have positive influence on the growth of minimum wages while development of economy,time-lagged effect of minimum wages and opening degreee cannot lead to the improvement of the growth of minimum wages.Effect of all variables towards the growth of minimum wages have improved without spatial autocorrelation and the weighted simultaneous autoregressive model(WSAR)has better fitting goodness and explanatory power.The GTWR performs better than other models on goodness-of-fit and model goodness,and the signs of most c-oefficients of GTWR are consistent with the expected,and the strong time volatility and spatial nonstationaryty are showed,the skewness of the distribution of predictors' residuals is not evident.At last,some advices are put forward to improve the growth mechanism of minimum wages according to the empirical result,and point out the direction of further study.