Dissertation
Dissertation > Economic > Economic planning and management > Economic calculation, economic and mathematical methods > Economic and mathematical methods

Residential real estate prices in Chengdu and Empirical Analysis of Factors Affecting

Author GaoChengXia
Tutor WangYuGui
School Sichuan Normal University
Course Geography
Keywords Real estate prices Factors Mathematical model Multiple regression analysis
CLC F224
Type Master's thesis
Year 2011
Downloads 189
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2011, Chengdu goal is to become the best business environment in central and western China, the best living environment, the overall strength of the strongest modern large urban centers, while housing problem is striving for the best living environment in Chengdu a fixed target. Government and the public are very concerned about the housing problem. The healthy development of real estate, the price is one of the most important criteria. At present, China's real estate prices continue to rise is facing serious problems, how to play an active role in the real estate industry in the national economy, the consolidated actual situation and the results of previous studies, drawn there are many factors that affect the price: GNP, economic growth, the level of income, tax policy, land policy, consumer psychology. In fact, housing prices is not one single factor, a separate forces the result; instead of multiple factors, the result of various forces. According to the 2006 Chengdu various quantifiable data to make impact analysis of the factors Chengdu real estate prices, select a greater impact on the real estate prices have universal significance of factors: GDP, total population, the second industry the output value of tertiary industry output value, fixed investment, urban per capita disposable income of urban per capita consumption expenditure, the total number of motor vehicles, real estate investment, per capita green area, real estate sales, residential area is completed, the number of beds in health institutions which 13 index as the initial equation, the independent variable indicators into consideration, the principal component analysis, to identify the impact of Chengdu real estate price fluctuations of the main factors include: real estate costs and market supply and demand factors, factors of economic development, investment and environmental improvement three aspects. Then performed on each factor and the price correlation analysis of selected third larger correlation output, per capita disposable income, per capita public green area of ​​commercial housing completed in the area of ​​commercial housing sales area, the per capita GDP which six factors, using SPSS software to build logic regression model, multiple linear regression analysis. For Chengdu each of the years 2001 to 2009 rates for the empirical analysis, forecasting results more in line with the true value, indicating that the selected indicators and the model is in line with the actual situation, the analysis results have practical significance. This paper mainly studies the main city of Chengdu (Wuhou District, Jinjiang, Qingyang District, Jinniu, Chenghua Note: High-tech Zone classified as Wuhou) residential property. This data comes from statistics information network and Chengdu Statistical Yearbook 2006 data. In this paper, the principal component analysis and multiple linear regression methods. In present the real estate price factor analysis and research are more qualitative analysis of the article can be found everywhere, just illustrates these factors have an impact on real estate prices, and no measurement of various factors on the extent of the impact of urban housing prices. On quantitative aspects of the analysis, but few, therefore, this paper attempts to apply quantitative thinking to identify the impact of the factors that real estate prices in Chengdu, the theoretical and empirical papers on the basis of a unified, real estate prices and a detailed analysis of each factor in Chengdu The relationship between the layers from the general to the depth reached Chengdu residential real estate price growth law and main influencing factors and impact.

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