Simulation of Economic Distribution Evolution and Its Driving Forces in Beijing-Tianjin-Hebei Metropolitan Region
The evolution of economic growth in Beijing-Tianjin-Hebei Metropolitan Region （short for BTHMR） are simulated using Kernel density estimation based on the data of the population, capital invest- ment, and GDP of 140 county-level sub-regions of BTHMR in 1995-2007. And further its driving forces are simulated using spatial lag models based on the variables, such as capital deepening, technological efficiency and technological progress, which derived from the DEA and Malmquist index models, in different periods. Several conclusions are drawn as follows： 1） The shape of economic spatial distribution have changed signifi- cantly, from two peaks in 1995 to one peak in 2001, then, two peaks again, with a bigger and bigger gap be- tween poor sub-region groups and rich ones, which indicates that the BTHMR had undergone a change from convergence to club convergence. 2） Capital deepening, technological efficiency, technological progress and spatial dependence play important roles in the economic growth of BTHMR. 3） Capital deepening and techno- logical efficiency have statistically significant impacts on the economic spatial distribution evolution while the spatial dependence and technological progress have not although they both were important driving forces in economic growth. The distribution change of capital deepening and the increasing importance of technological efficiency have contributed to the economic distribution evolution rather than the increasing importance of cap- ital deepening and the distribution change of technological efficiency. The results indicate that the distribution effects of capital deepening and coefficient effects of technological efficiency had become the channel, through which capital deepening and technological efficiency changed the economic distribution evolution.
kernel density estimationeconomic growth distributionspatial dependence effectBeijing-Tian- jin-Hebei Metropolitan Region
NETL
NSTL
万方数据
维普
