The Statistical Analysis Of Applicability Of Reverse Mortgage In China

Since the reform and opening policy in 1970s, with the rapid development of our social economy, people's living standard and medical level increased gradually. And the average expectancy life of people grew lead to the number of elderly population increased dramatically. By the end of 2000, the proportion of the population aged 60 or older in the total population up to 10.46, China has fully entered the aging society. In recent years, with the rapidly increasing of the degree of the aging population, its negative effects appeared, the traditional family pension and pension institutions gradually could not meet the rapidly growing demand for retirement. In this context, the reverse mortgage introduced to China, which refers to the elderly homeowners with independent property mortgage the house to financial institutions, financial institutions provide loans to the old man regularly until he was dead. It retains the elder residence of the original houses the same time improves the quality of life of the elder, it is a major breakthrough in the traditional pension way. In addition, the reverse mortgages will be huge benefit to activating social sunk capital, realizing better distribution of social resources, provoking innovation of financial instruments and establishing new generation relationship which fits into market-oriented economy. Based on this reason, the paper researches the needs and risks of the reverse mortgage, to explore its applicability in China.This paper follows the logical concept of "Theory-Analysis-Positive". Learn the reverse mortgage related theory firstly and then descriptively analyses the implementation of reverse mortgages under the background of aging basic conditions, using the BP neural network model to predict the value of the property and then the risk of fluctuations in value of the house will be explained. According to China's major urban demand differences for reverse mortgages analysis of the possible implementation of the path, and combined contents of this paper to summary, from reducing the risk and increasing the attractiveness to give policy advice.This article includes six chapters.The chapter I is the introduction, this paper Firstly describes the background and significance, then reviews the domestic and foreign literature associated with reverse mortgages, and finally explains the research methods and ideas of this article.The chapter II is the theoretical basis of the mortgage. Firstly elaborated the connotation of reverse mortgages and compared between the traditional mortgages and reverse mortgages, and then explained the three main risk factors, which are interest rate risk and longevity risk and volatility value of the house, the risk of fluctuations in house value is the key to the implementation of reverse mortgage, it is also the focus of this paper.The chapter III is the basic conditions to implement the reverse mortgage. This chapter use the descriptive statistical methods mainly to describe the characteristics of status aging and development, economic development and the degree of aging does not match, analyze the gap between the current pension, social security system and pension demands, emphases the higher homeownership rate in major cities, these constitute the basic to implement reverse mortgages, which is a start to analyze the applicability in China.The chapter IV is the study of the risk of real estate price forecasts based on fluctuations in the value of houses. This chapter describes the theory and learning process about BP neural network, selected 12 indicators from economic, demographic, policy, market four areas to compute index system. Using Matlab software based on quarterly data to forecast the average price of real estate, and according to the relative error of prediction, roughly measures the risk of fluctuations in value of the house.The chapter V is the difference between a reverse mortgage demand analyses. This chapter selected 12 indicators which affect reverse mortgage demand from economic development, population structure and social services three aspects. Mainly use the principal component analysis to analyze the 12 indicators of 35 cities. According to ranking the city scores on each main ingredients, and lastly analyze the feasible implementation path on the basis of differences in the demand for reverse mortgages.The chapter ? summarizes research and policy recommendations. In this chapter, the paper's contents and conclusions are summarized, and on this basis, put forward several recommendations to improve the reverse mortgage's attraction and reduce the risk of two angles, hope to do something to the promotion of the reverse mortgage in China.This paper attempts to do further empirical analysis on the basis of reverse mortgage related theories, mainly on the two aspects of the risk of fluctuations in the value of the house research and its demand difference. Selected 12 indicators from four aspects economy, population, policy, market which impact the fluctuations in the price to compute index system, based on quarterly data using BP neural network model to predict the value of the property, and described the risk of fluctuations in the value of housing on the basis of the forecast. On the analysis of the demand differences of reverse mortgages, we selected 12 indicators from social development, population structure and social security system three aspects which impact the demand, based on our 35 provincial capital cities and cities with independent planning, and the reverse mortgage demand differences were analyzed. However, due to the reverse mortgage has no formal implementation in our country, the acquisition of data has obstruction and the editor has some limitations in background knowledge, there are some shortcomings on the representation of indicators and reverse mortgage system integration of many disciplines. We can use the breakdown data and multidisciplinary cooperation to further deepen the study after the time.