The Income Gap Between The Space-time Evolution And Forecast

Since the reform and opening up, with the national rapid economic development, the regional income disparities arc also widening. The large income gap will cause the increasing sense of injustice, inequality of society members, and seriously affect economic development. During the nearly two decades, the domestic scholars did a lot of research of income gap. The theories also experienced the changes from time scale to spatial scale. From the early economic growth theory to the recent study of regional economic theory, more and more scholars began to focus on income disparities in the spatial characteristics. During the period of Chinese economic transition, the spatial pattern of income disparity, divergence, convergence and the evolution of the law is the focus of research. But most of the works in income gap used spatial autocorrelation methods to analysis the spatial static pattern, and didn't reflect dynamic evolution of the spatial pattern. In addition, the studies of the prediction about the income gap are relatively small. On this basis, the goal of this study is to explore the spatial and temporal evolution of the income gap, and to predict this rule, the main contents are as follows:1) First using the comparative analysis between the region's Gini coefficient and coefficient of variation, the author explored the time and space evolution of income gap with the help of convergence theory of space, broke the study area into three economic gradient regions, and investigated the different gradient effect on the overall income gap. Finally, using the value of per capita income of Beijing between 2000 and 2009, gave the case analysis. The results show that Beijing has experienced an "up-down" volatility curve on the time variation of the income gap in time, with the obvious characteristics of the stage. On the spatial variations, the large income gap showed as the rapid development of Beijing city center and the relatively slow development of the suburbs. The gap between the first tier and the second, third tier structure was the key factor of the income gap in Beijing, and the contribution rate was more than 90%.2) Aiming at the shortage of the Markov chain and time series analysis methods used in the space and time prediction, a space and time trend prediction model was proposed. The author added a time variable t in the spatial trend surface analysis methods, and used the improved model to predict the spatial and temporal variations income gap in Beijing. The results showed that Beijing's Gini coefficient would remain at about 4.5 in the next 5 years, the income gap would be still large compared to the past few years, and the trend of income gap would be widening. The pace of development downtown would be still faster than suburban development speed.In this paper there are two main innovations.1) With the help of convergence theory of space, the author analyzed the process of income disparity from different stages, discussed the impact of different spatial scales on the income gap.2) Aiming at the shortage of the traditional methods used in the space and time prediction, the author added a time variable t in the spatial trend surface analysis methods,and built a improved model.