Quantitative Study On The Consumption Trend Of Urban Residents In China

In recent years,economic growth shows new characteristics,which is undoubtedly closely related to the people's increasing income level and consumption ability.Consumption is the basic driving force to stimulate the economic growth of a country and a region.On the contrary,based on economic development consumption can be increased and people's living standards can be continuously improved.Therefore,it is of great significance to study the consumption trend of our country for national economic growth.This paper uses the data of consumption and income of urban residents in 31provinces(cities,autonomous regions)from 2002 to 2017 and tries to explain the consumption trend in China.The thesis is divided into the following two parts.In the first part,the relationship between consumption and income is studied based on spatial model.Based on the consumption theory,this paper introduces the research method of spatial measurement,tests the spatial correlation between income and consumption,establishes the spatial lag model and spatial error model,and analyzes the spatial relationship between consumption and income of urban residents in China.After analysis and comparison,it is concluded that the spatial error model is more suitable for the research data and the economic problems concerned by this paper,which also explains the interaction and influence of consumption level between regions very well in China.Therefore,the economic phenomenon is explained in accordance with the reality.In the second part,the relationship between consumption and income is studied based on interval symbolic data.According to the characteristics of the data in this paper,we extend the point data to the interval data,fully extract the internal information of the interval,and further analyze the development trend of China's consumption level.From the perspective of simulation and demonstration,this paper establishes the regression model under the middle point method,the upper and lower limit method and the middle point radius method,and uses appropriate evaluation indicators to evaluate the model results.The results show that the three methods can interpret the data better,but the midpoint radius method is more superior.Moreover,by applying Lasso regression method to interval symbolic data,some variables related to interval data are screened,a new regression method for interval symbolic data is proposed,and the effectiveness of the new method is verified.Finally,various models are applied to the empirical study to predict the futuredevelopment trend of China's urban residents' consumption.