Classification Study Of Housing Prices, Income And Housing Affordability

In recent years, along with China’s rapid economic development and urbanization process accelerated, the price of real estate showed a rapid upward trend. In order to curb housing prices, the Government has launched a series of macro-control policies, These macro-control policies present initial results, but conceal its "one size fits all" disadvantage. The macro-control policies accidental injury portion of the rigid demand mainly due to the ability to pay of the different income groups is different, to cause housing units, location and other requirements are not the same, as a result, prices for residential, income and housing afford ability the ability classification research is particularly important.In this paper, an overview of the historical literature, explore the respective advantages and disadvantages of the ratio method and the income approach, the clustering analysis of high-dimensional data similarity function areas for improvement to make it more economic sense.In this paper, through the establishment of four-dimensional data (region, income and price indicators, time and income stratification), to build the level of development, the pace of development indicators coordination, as well as a comprehensive index of similarity function, residential property prices in our province, household income and housing ability to pay cluster analysis, the31provinces and cities across the country is divided into four major categories.The main conclusions are as follows:1、Based on the clustering analysis of patterns of the country from the three angles of income, housing prices and housing affordability is divided into four categories, four major categories of indicators in the absolute level, level of development, indicators of the level of coordination have shown similar characteristics the absolute value of both the same or less, at the same time the level of volatility is also consistent.2、According to the classification results, we propose the appropriate policy recommendations. Use tax policy to regulate the high-end residential and developed areas, to maintain ordinary commercial housing purchase of limited credit policy, and at the same time continue to build affordable housing, to achieving the goals of the policy objectives of the living room. This paper has the following innovations:1、Using the cluster analysis of high-dimensional data. In the past, most of the scholars use panel data clustering analysis, to the neglect of some of the key variables. In the study room housing affordability problems, people of different income levels is not the same as the preferences of the purchase of housing, leading to its payment capacity a huge difference, this article from the region, income and price indicators, time and income stratification four dimensions were cluster analysis.2、The past clustering analysis of the improvement of the similarity function. Clustering analysis, the domestic part of the similarity function proposed by the lack of economic sense, can only be explained statistically. In this paper, then any economic system, there is an indicator representative of the entire economic system uptime, and other indicators deviate from the characterization of the index value for clustering.