上海市房地产市场有效性的实证研究

发布时间：2018-04-16 19:42

本文选题：上海市房地产市场 + 弱有效性　；参考：《华东师范大学》2014年硕士论文

【摘要】：房地产市场是经济系统的重要组成部分,由于其价值量和利润空间大于一般资本市场,所以成为了投资者的热衷领域,大量投资和投机行为的涌入提高了房地产市场价格。这种现状一方面是有利的,对中国经济做出了重要贡献,但是另一方面由于住房紧系着民生问题,房价上涨过快导致低收入群体无力承担高房价而面临严重的住房困难。所以探讨房地产市场价格的形成轨迹及对信息的反映状况,验证房地产市场是否有效,对于完善房地产市场的发展具有显著的意义。本文以上海市房地产市场为研究对象,数据选取于中房上海指数2005年第一季度至2013年第四季度的季度数据,为了提高检验的精确度,将房地产市场细分为新房市场和二手房市场分别开展弱有效性的实证检验。新房市场选用了城市综合指数、住宅指数、写字楼指数和商铺指数,二手房市场选用了销售价格指数和租赁价格指数,总共216组检测数据。弱有效性的检验运用了随机游走模型理论,选用单位根检验和序列相关性检验两种方法。单位根检验结果显示上海市各细分市场的有效性不一致,其中新房市场的写字楼市场和商铺市场,二手房市场的住房租赁市场达到了弱有效性,新房市场的住宅市场和二手房市场的房屋销售市场没有达到弱有效性。序列相关性检验结果则是上海市房地产市场各个细分市场和整体市场均尚未达到弱有效性。结合两种检测结果可以认为,上海市房地产市场整体上尚未达到弱有效性,房屋价格不遵循随机游走过程,投资者可以在市场上获取额外收益。由于检验到上海市房地产市场未达到弱有效性,即房地产价格不能完全反应市场历史信息,那么为了解释其对市场信息的反应程度,本文采用向量自回归模型检验上海市房屋价格对土地交易情况、房地产投资额、城市居民人均可支配收入和GDP变化的反应情况,选取了上海市1995年至2012年的上述5个变量总共90组年度数据。协整检验的结果为,长期内,上海市房地产市场价格对城市居民人均可支配收入和GDP的变化反映比较敏感；向量误差修正模型显示,短期内,上海市房地产市场价格对土地交易情况和房地产投资额的反映程度显著;进一步采用脉冲响应函数和方差分解分析各变量在受到冲击后对房地产市场价格的影响情况,结果显示各变量对房价均产生影响,且影响程度随着时间逐渐减弱,其中城市居民人均可支配收入和GDP对房价变动的影响程度较其他两个变量高。
[Abstract]:The real estate market is an important part of the economic system, because its value and profit space is larger than the ordinary capital market, so it has become a keen field of investors, a large number of investment and speculative behavior to increase the real estate market prices.On the one hand, this kind of situation is advantageous, has made important contribution to Chinese economy, but on the other hand, because housing is tight to people's livelihood problem, the house price rises too fast causes the low income group to be unable to afford the high housing price, therefore faces the serious housing difficulty.Therefore, it is of great significance to discuss the formation track of real estate market price and reflect the information to verify whether the real estate market is effective or not, and to perfect the development of real estate market.This paper takes the real estate market of Shanghai as the research object. The data are selected from the first quarter of 2005 to the fourth quarter of 2013 of Shanghai Index of Zhongfang, in order to improve the accuracy of the test.The real estate market is divided into the new housing market and the second-hand housing market to carry out the empirical test of weak effectiveness.The new housing market selected the city composite index, housing index, office index and shop index, the second-hand housing market selected sales price index and rental price index, a total of 216 sets of test data.The theory of random walk model is used to test the weak validity, and two methods, unit root test and sequence correlation test, are used.The results of unit root test show that the effectiveness of the subdivision markets in Shanghai is not consistent. Among them, the office and commercial markets in the new housing market and the housing rental market in the second-hand housing market have achieved weak effectiveness.New housing market housing market and second-hand housing market housing sales market has not reached weak effectiveness.The result of sequential correlation test is that the market segments and the whole market of Shanghai real estate market have not yet reached the weak efficiency.Combined with the two test results, it can be concluded that the Shanghai real estate market as a whole has not yet reached a weak efficiency, housing prices do not follow the random walk process, investors can obtain additional income in the market.Since the test shows that the real estate market in Shanghai has not reached a weak validity, that is, the real estate price cannot fully reflect the historical information of the market, then in order to explain the degree of its reaction to the market information,This paper uses the vector autoregressive model to test the response of housing prices in Shanghai to land transactions, real estate investment, per capita disposable income of urban residents and GDP changes.A total of 90 sets of annual data were selected from 1995 to 2012 in Shanghai.The results of cointegration test show that, in the long run, the price of Shanghai real estate market is sensitive to the change of per capita disposable income and GDP of urban residents, and the vector error correction model shows that, in the short term,The price of Shanghai real estate market reflects the land transaction situation and the real estate investment significantly, and the impulse response function and variance decomposition are used to analyze the impact of the variables on the real estate market price after the impact.The results show that each variable has an effect on house price, and the influence degree is gradually weakened with time. The influence of per capita disposable income and GDP on house price change is higher than that of the other two variables.
【学位授予单位】：华东师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F299.23

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