Bubble Degrees Measurement And Difference Research Of Urban Real Estate Market

This paper first introduces the housing cycle theory, assets speculation theory and real estate bubble theory. By understanding the real estate cycle, we can realize that there are price fluctuations in the real estate cycle, which may trigger speculation in the property market and produce price bubble. By reviewing assets speculative theory, we can more clearly know the internal and external factors that there exist speculative behaviors in the real estate market, and we can analyze the speculative driving reasons from the objective and subjective levels. Through the analysis and summary of the real estate bubble theory, we can understand the causes of the real estate bubble and the present test methods.Based on the above theory and according to the real estate price formation theory of Muellbarer and Murphy and the rational bubble model of Blanchard and Fischer and the measurement methods of Chou Benkyou Hou,we construct the bubble degrees measurement model. Under the support of the related literature, we construct the model of factors influencing bubble degrees. And then with the bubble degrees as the dependent variable, we choose GDP growth rate, per-capita disposable income growth rate and the other six indexes as the independent variables to construct the bubble degrees model of influence factors. Through the analysis of the data and empirical research, firstly we find out that M2is the main reason that leads to bubble degrees time difference, so the change curves of four cities are quite similar. Secondly, we find out the different influence degree of each independent variable and rank them. From the high end to the low end, they are GDP growth rate, sales area growth rate, M2growth rate, investment growth rate in real estate development, per-capita disposable income growth rate, registered population rate, investment growth rate in real estate development of GDP and completion area growth rate. They are all quarterly and annulus compared. Except the completion area growth rate and the bubble degrees are negatively correlated, the other independent variables are all positively correlated with the bubble degress. The probable innovation of the thesis concentrates on six aspects:First of all, the thesis chooses quarterly data of four cities as the study examples; Secondly, it constructs the model which can measure bubble degrees at any time; Thirdly, it suggests bubbles are both positive and negative. The positive bubble means the house price is higher than the based value and the negative bubble means the house price is lower than the based value; Fourthly, it analyzes the bubble degrees time difference with the policy change and it finds out the M2is the main reason that leads to bubble degrees time differenc; Fifthly, it makes a regression analysis of the research about the affecting factors of bubble degrees; Sixthly, combined with affecting factors variables, it analyzes bubble degrees city difference and ranks the factors.