A Statistical Analysis Of Relationship Between Income Distribution Inequality And Commodity Price Change

Especially in recent years, China’s real estate industry has become one of the main factors affecting the development of national economy, which means that the healthy development of real estate industry will affect the entire national economy. On the question of whether real estate prices fluctuate around its value have different opinions.This paper, based on the perspective of income distribution inequality, starting from the existing mathematical model of economic theory, has collected national commercial housing price index time series of operation in1987-2011, and2001-2011panel data of31provinces, to combine a variety of statistical methods to describe exploration and empirical analysis. On the whole, in view of the time series data, the author firstly has carried on the commercial housing price and housing price to income ratio, the gini coefficient, thayer index indicators such as descriptive statistics, and then to the unit root test, stability test, ADRL-the ECM model and causality test. In view of the panel data of31provinces, the description of the major statistical indicators for the statistical analysis and panel data model based on conditional expectation, estimates that for the mixed data model based on conditional quantile estimates, finally has carried on the space description statistical analysis and regression model to estimate the cross-sectional data space. In both countries level time series and panel data of31provinces, descriptive statistics and model estimation results show that:a causal connection between real estate prices and the inequality of income distribution, and the distribution of income inequality and commercial housing prices mostly exists nonlinear u-shaped curve relationship, a small number of nonlinear inverted u-shaped curve relationship exists. In terms of research on the details of the31provinces in China commercial housing price spatial statistical analysis, discovered the existence of the spatial autocorrelation, mapped the Moran’s I,LISA distribution, real estate prices, global and local autocorrelation of housing price to income ratio. On the basis of the basic OLS model, by considering the spatial geographical factors, spatial lag and error model is established, using the panel data of31provinces from2001to2011, the commercial housing price and housing price to income ratio of our country space measurement inspection, found that spatial lag and spatial error model explain ability is better than OLS. It also suggests that commercial housing price and housing price to income ratio is spatial lag autocorrelation and spatial error autocorrelation. Based on the results of statistical analysis, the paper further analyzed the causes of the real estate bubble from several aspects to deepen the understanding of the real estate bubble tendency. According to the causes of the real estate bubble, for the government to curb real estate bubble, the best way is to strengthen unequal income distribution regulation and so on.