Research On Consumption Structure Of Urban Residents In Beijing

Under national economic accounting, consumption, together with investment and net export, are considered as the troika pulling the economic growth. In recent years, the development of consumption and its structure is attracting more and more attention from the government and society at all levels. As one of basic economic activity in human society, consumption is the behavior and the process to consume certain realistic objects in order to meet certain demands. Consumption structure is the combination, correlation and dynamic status of various specific contents of consumption, as well as is the percentage of each content in total consumption, under certain social and economic conditions. Residential consumption structure can indicate the satisfaction degree of meeting urban residents’ demand for material and cultural life, and it is also the indicator of a nation’s economic development level and its material and cultural living standards. Since consumption structure is constrained by the level of economic development, the growth of per capita GDP and residential income would certainly promote the growth of consumption, which could then inevitably leads to the rationalization of consumption structure and the gradual increase of consumption levels, and hence, the economic development and industrial restructuring would be stimulated in return.Starting from the research background, this thesis referred to the existing and relevant research materials, using qualitative and quantitative methods to study the residential income and the development of consumption structure in Beijing. Firstly, this thesis qualitatively analyses the economic efficiency and income efficiency of Beijing’s urban consumption structure with ELES module, quantitatively evaluates the level of development correlation through constructing comprehensive model with effective function and coupled function, and estimates the trend of consumption structure development and consumption hot spots with BP neural network forecast module. Secondly, the thesis provides an empirical analysis on the residential income and consumption structure in Beijing, and evaluates the current consumption structure in Beijing and forecasts the trend with the developed comprehensive model mentioned above. Finally, based on the forecast of future hot spots of residential consumption in Beijing, this thesis gives suggestions on consumption structure optimization and residential consumption expansion in Beijing.