Abstract

Keywords: Housing price; Analysis of main influence factors; multiple linear regression Abstract. Housing price problem is an important economic and social issue of widespread concern, which affects the life quality of urban residents and also affects the continued steady growth of national economy. Based on method of multiple linear regression analysis, this paper studies the relationship between housing prices and the influencing factors in the aspects of demand and supply, and identifies the main factors of influencing the housing prices. It tries to provide the valuable reference for the government to regulate the housing market effectively. The modern real estate industry has become a pillar industry of Chinese national economy, and the housing price is the key in the real estate industry. The housing price level is not only related to the living standards of the masses, but also related to the global economic development. However, in recent years, due to the cyclical and regional real estate development, there is imbalance in the market of supply and demand. Together with the increased raw material prices and costs, the house price is becoming more and higher. The housing price is an extremely complex issue, to study the main influence factors and to find out the change rules have important theoretical and practical significance to promote the sustainable and healthy development of the residential real estate market. Many scholars presented some valuable results on the study of housing price. Zhao (1) used the factor analysis method to analyze twelve influence factors for housing price, and finally selected two main influence factors. She also pointed out that China's real housing prices have been gradually rising. Guo and Yuan (2) studied the interactions relationship between real estate market and interest rates from 1998 to 2008, and the results indicated that there is a co-integration relationship between interest rates and housing price. Li studied the panel data of 30 provinces and cities from 2000 to 2011, and used the EBA (extreme bounds analysis) model to explore the robustness factors which influence the housing prices. The conclusion is drawn that the land price, the cost of completion housing, population and urban and rural incomes are four main influence factors for the housing price. Xue (3) pointed out that the housing market has always maintained a good momentum of development since the Chinese real estate industry has entered the commercialization stage. Guo and Wang (4) established a dynamic econometrics model to analyze the main influence factors for housing prices, and pointed out that there is a long-term equilibrium relationship between housing prices and the housing supply and demand variables. Li (5) selected some important indexes which influence housing prices, and used statistical software to analyze the factor analysis from the original data. Then four representative factors, i.e., economic factor, the real estate factor, transportation environmental factor, the expected factor are selected. Liu (6) reviewed and summarized the latest research on foreign housing price factors from the perspective of supply-demand balance, and the related literature was summarized in terms of land, income, tax, financial, location and other domestic achievement. Based on existing results, this paper studies the relationship between housing price and its influencing factors based on method of multiple linear regression analysis. The aim is to find out the main factors of influencing the housing prices and to provide the valuable reference for the government to regulate the housing market effectively.

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