【作者】 郑文娟；

【导师】 贾生华；

【作者基本信息】 浙江大学 ， 企业管理， 2011， 博士

【摘要】 我国城市住房市场在快速城市化和转轨市场化的双重力量共同推动下得以繁荣发展,成为进一步推动经济增长和社会进步的重要平台。然而,我国城市住房价格与住房租金之间却出现关系偏离的现象,严重影响到我国住房市场的持续稳健发展,受到许多理论研究者的密切关注。已有的国内研究多从解释我国城市住房买卖市场与住房租赁市场之间的失衡来解释住房价格与住房租金之间的偏离现象,并未能够很好地把握与解决问题。为此,本研究提出从“因素观”视角来解释我国城市住房价格与住房租金之间关系偏离的问题,认为正是由于我国城市住房价格与住房租金的关键影响因素基本上截然不同,导致在同一制度环境下住房价格和住房租金会出现明显不同的变化趋势,甚至出现两者相互背离的特殊现象。本研究在对我国城市住房价格和住房租金关系偏离的问题进行充分论述的基础上,大量研读关于城市住房价格和住房租金影响因素及其相互关系的国内外已有文献,并按照其对城市住房市场认识的不断深化、对实证研究方法应用的不断完善的过程,从“单一市场”、“双重市场”与“整体市场”三个方面对已有文献进行梳理与归纳,为本文后续研究奠定良好的理论与工具基础。同时,为了更好地使理论与实际相结合,本研究对我国城市住房市场进行深入剖析,提炼总结住房买卖市场与住房租赁市场的各自特点,并对两个细分市场之间“服务对象不一致、发展速度不一致、显化价值不一致”的双重结构特征进行归纳分析,为本文后续研究奠定扎实的环境与制度基础。基于上述理论与现实背景充分准备的基础上,本文从“因素观”视角来研究我国城市住房价格与住房租金问题,试图回答两大问题：第一,我国城市住房价格与住房租金各自的关键影响因素分别是什么?第二,我国城市住房价格与住房租金之间关系在短期上与长期上具体如何表现?本文共安排四章实证研究分别对此进行回答,均采用2003-2008年全国35个大中城市的面板数据。关于第一个问题,论文第四章与第五章均利用STATAIO.0软件,对该数据进行面板数据固定效应模型分析处理,分别识别出我国城市住房价格和住房租金的关键影响因素。关于第二个问题,论文第六章和第七章均利用Eviews 6.0软件来实证我国城市住房价格与住房租金的短期与长期关系；其中,第六章顺次进行单位根检验、协整检验以及误差修正模型分析,实证研究两者的短期关系表现；第七章则对住房价格与住房租金的联立方程模型进行两阶段最小二乘法回归分析,解决被解释变量间的内生性,实证研究两者的长期关系表现。通过系统的理论分析与实证研究,本文主要得出以下四个研究结论：第一,我国城市住房价格和住房租金的关键影响因素差异十分明显。住房价格的关键影响因素既有需求类因素又有供给类因素,其中属于需求类因素的有住房租金、住宅价格增长率、人口自然增长率、人均地区生产总值、建成区绿化率、就业率6个因素；属于供给类因素的有土地价格、房屋竣工成本、住宅完成投资额、住宅竣工面积、土地购置面积5个因素。而影响住房租金的关键因素则以需求类因素为主,分别是住房价格、住房价格增长率、固定资产投资额、非户籍人口比重、在岗职工平均工资、人均GDP、第三产业占GDP比重和规模以上工业企业数量等8个因素。住房价格和住房租金共同的关键影响因素只有住房价格增长预期和人均地区生产总值。由于住房价格和住房租金各自的关键影响因素差异悬殊,导致两者在相同时空中对共同环境表现出不同的反应。尤其是在中国这种特殊的制度环境下,住房价格增长期望等因素产生非正常的显著作用,造成我国城市住房价格脱离了住房租金资本化的基本价值而大幅高涨。第二,在短期上,我国城市住房价格和住房租金相互影响、互为因果。在双重市场理论分析框架中,将住房价格和住房租金视为相互的外生影响因素进行实证分析,发现我国城市住房价格和住房租金的短期相互关系具有对称性,即住房价格变化是住房租金变化的短期原因,住房租金变化也是住房价格变化的短期原因。具体而言,影响住房价格的短期原因是上年的住房价格和同年的住房租金；影响住房租金的短期原因是上年的住房租金、前二年至同年的住房价格。这个关于住房价格和住房租金短期上相互影响的结论与现实中的观察比较符合,即在短期内我国城市住房价格和住房租金相互作用,但两者所受到的力量来源并不相同,各自产生不同的波动趋势,从而导致在短期上两者之间的涨幅和大小差异甚大。第三,在长期上,我国城市住房价格显著影响住房租金,但住房租金却无法显著影响住房价格。在整体市场理论分析框架下,将住房价格和住房租金视为相互的内生影响因素进行实证分析,发现我国城市住房价格和住房租金之间的长期相互关系具有单向性。具体而言,住房价格每上升1元/平方米,则每月的住房租金就会相应地上升0.0017元/平方米,该长期影响关系通过了显著性统计检验,即住房价格是住房租金的显著性长期原因；每月的住房租金每上升1元/平方米,则住房价格就会相应地上升28.41元/平方米,该长期影响关系却没有通过显著性统计检验,即住房租金不是住房价格的显著性长期原因。这个关于住房价格和住房租金长期上单向影响关系的结论也与现实中的观察比较吻合,即在长期上我国城市住房价格逐渐脱离住房租金资本化的基本价值,导致房价收入比与房价房租比都显著地超过了国际经验值。第四,我国城市住房价格和住房租金相互偏离的特殊现象背后有更深层的体制原因。其可能的原因在于现阶段我国社会财富不断增加,引发城市居民投资性需求急剧增多,与此同时我国当前金融体系尚未健全,因而导致社会资金过度集中于住房买卖市场。因此,本文提出两个引导我国城市住房价格和住房租金协调发展的可行对策：一方面,尽快开拓我国个人投资渠道、进一步完善金融市场体系；另一方面,进一步协调我国城市住房买卖市场与住房租赁市场之间的平稳发展。与国内已有的研究成果相比,本文学术价值和创新点主要体现在四个方面：第一,“因素观”视角的提出及已有研究视角的比较,有助于提高研究者对我国城市住房价格和住房租金问题的深层认识与实证分析。已有的国内研究多从解释住房买卖市场与住房租赁市场之间的失衡,来间接解释住房价格与住房租金之间的关系偏离问题,本文将其分别归纳为体制观、区隔观、政策观、文化观、投机观等。本文则从“因素观”视角出发,以探索住房价格与住房租金的各自关键影响因素,来进一步分析住房价格与住房租金之间的关系问题,可以促进该领域研究从“市场间接解释价格问题”向“因素直接解释价格问题”上深化。同时,对国内外已有文献按照“单一市场”、“双重市场”、“整体市场”三个方面的梳理与归纳,有助于该领域后续研究不断完善对理论基础的把握和研究工具的应用。对我国城市住房市场的发展背景与市场特征的刻画分析,为国内该领域的后续研究走向“本土化”奠定了扎实的背景基础。第二,利用面板数据固定效应模型分别对我国城市住房价格和住房租金的关键影响因素进行实证分析,不仅强化了对住房价格影响因素识别的理论研究,也填补了我国缺乏对住房租金影响因素实证研究的理论空白。当前国内学者对城市住房价格影响因素开展的实证研究较多,但研究结论尚存在较多争议；与此同时,对城市住房租金影响因素开展的实证研究尚十分稀少,其重要原因是缺乏城市层面的住房租金数据资料。本论文通过住房租金数据抽样,结合相关统计资料,获取2003-2008年全国35个大中城市的面板数据,并利用面板回归模型对我国城市住房价格和住房租金的重要影响因素进行实证分析,在研究方法上有较大创新,而且是国内首次通过实证研究识别出我国住房租金的城市层面影响因素。第三,首次通过面板单位根检验、面板协整与面板误差修正模型分析,从城市层面掌握了我国住房价格和住房租金的短期关系。国内已有研究一般是采用全国住房价格指数的时间序列数据来研究住房价格与住房租金之间的短期关系,得出的研究结论差异甚大。应用全国价格指数进行实证研究存在两方面不足,一是全国综合数据无法很好地反映出不同城市的较大差异性,二是国内的现有价格指数无法很好地代替价格水平数据来反映住房价格和住房租金的真正表现。本研究创新地利用城市面板数据,从城市层面实证我国住房价格和住房租金的短期关系,使国内理论研究对该现实问题有了更深入的了解,而且也推进该领域理论研究从全国层面深化到了城市层面。第四,首次通过构建城市住房价格和住房租金的联立方程模型,解决住房价格和住房租金的“内生性”,从城市层面实证了我国住房价格与住房租金的长期关系。国内已有的关于住房价格与住房租金之间长期关系的实证研究,都将两者视为相互的外生影响因素,造成了对两者因果关系的争论不休。本研究通过分析我国城市住房买卖市场与住房租赁市场的联动分析框架,应用2003-2008年全国35个大中城市的面板数据,构建我国城市住房价格和住房租金的联立方程模型,利用两阶段最小二乘法解决方程估计的内生性问题,准确掌握住房价格与住房租金之间的长期关系,并对两者的相互影响程度进行了量化。这使国内理论研究对该现实问题有了更深入的掌握,而且也促进该领域实证研究由“外生性”走向“内生性”。更多还原

【Abstract】 Under the double powers of the rapid urbanization and the transition of market, China’s urban housing market has been booming in recent decades. However, the special relationship between urban housing prices and housing rents has become a serious social phenomenon in China. A large number of theoretical researchers have paid close attention to this issue, that most of them try to explain the reason for the" imbalance between China’s urban housing market and the housing rental market, not the really reason for the divergence between the housing prices and housing rents. Therefore, this research proposes to explain the deviation relationship between China’s urban housing prices and housing rents from the "factors’view", that is precisely because the key factors for China’s urban housing prices and housing rents are vary, resulting housing prices and housing rents change differently in the same environment. Thus, the short-term and long-term relationship between China’s urban housing prices and housing rents are very special.Based on the full exposition of the essence of China’s urban housing prices and housing rents problem, the author read a lot of domestic and international existing research literatures on the issue of urban housing prices and housing rents, and made a scientific summary on this literatures—divide the different theory analysis framework into "the single market theory", "the double markets theory" and "the integral markets theory". Meanwhile, the practice of China’s urban housing market is analyzed in-depth in this paper. The most specific feature of the dual structure of China’s urban housing market is the "inconsistent on clients, inconsistent on pace of development, and inconsistent on the manifest of housing value". The reading of literatures and the analysis of environment are order to laid a solid theory and practical foundation for the continue study.Based on the well-prepare of the above theoretical background and practical background, two important questions needed to be answered from the "factors’view" perspective in this paper. First, what are the key factors each for China’s urban housing prices and housing rents? Second, how are the short-term and long-term relationship between China’s urban housing prices and housing rents? Four empirical studys were arranged to answer these questions, in all of which the panel data of year 2003-2008 for 35 large and medium cities were used. Both of ChapterⅣand ChapterⅤused STATA10.0 software for carrying out the fixed panel model regression analysis, identifing each key factors for the urban housing prices and housing rents. ChapterⅥused Eviews 6.0 software for carrying out unit root test, cointegration and error correction model analysis respectively, positiving out of the short-term relationship between China’s urban housing prices and housing rents in performance. ChapterⅦused Eviews6.0 software for carrying out the two-stage least squares analysis for the simultaneous equations model of housing prices and housing rents, positiving out of the long-term relationship between China’s urban housing prices and housing rents. Through the theoretical and empirical analysis, this paper draws the following main conclusions:(1) The key factors for China’s urban housing prices and housing rents are both overlap and significant different. Both the demanded-class and supplied-class factors affect the housing prices. There are 6 demanded-class factors, which are housing rents, growth rate of house prices, natural population growth rate, per capita GDP, greenbelt rate, employment rate. There are 5 supplied-class factors, which are the price of land categories, housing costs to completion, the amount of residential investment, residential area completed and the land acquisition area. However, the main factors for the housing rents are main the demanded-class factors, which are housing prices, growth rate of housing price, fixed asset investment, the proportion of non-household population, the average wage of workers, per capita GDP, GDP, the proportion of tertiary industry and the number of industrial quantity enterprises. The combinations of key factors for China’s urban housing prices and housing rents are different, resulting in the different reflection of housing prices and housing rents in the same environment. In China’s particular environment system, some special factors role unnormaly, which affect both the housing prices and housing rents, such as the expected growth of housing prices, resulting in China’s urban housing prices run wildly out of the basic capital value of the housing rents.(2) On the short term, the housing prices and housing rents are exogenous factors for each other in the framework of dual-market theory. Symmetry relationship between China’s urban housing prices and housing rents was found, that the change in housing prices could due to the change in housing rents, and the change in housing rents could also cause the change in housing prices. Specifically speaking, the most important factors for housing prices in the short-term are the housing prices in the last year and the housing rents in the same year, and the most important factors for housing rents in the short-term are the housing rents in the last year, the housing prices two years before and the housing prices in the same year. This conclusion of the short-term impact between housing prices and housing rents is in line with the observation of the reality. That is, China’s urban housing prices and housing rents interact with each other in the short term. However, each of them has different power source, due to the different fluctuating trends they have, resulting in the great differences in gains and size between them on the short term.(3) On the long term, the housing prices and housing rents are endogenous factors for each other in the framework of integral-market theory. One-way relationship between housing prices and housing rents was found, that the housing prices are the significant long-tern causes for the housing rents, but the housing rents are not the significant long-tern causes for the housing prices. In particular, housing prices rose for every 1 yuan/square meter, the monthly housing rent will be increased accordingly 0.0017 yuan/square meter. This long-term impact relationship between the housing prices and housing rents was significant by the statistical tests, that housing prices are the significant long-term causes for housing rents. At the same time, monthly housing rents per increase of 1 yuan/square meter, the housing prices will rise accordingly 28.41 yuan/square meter. However, This long-term effects relationship between the housing prices and housing rents are not significant by statistical tests. Namely, housing rents was not the significant long-term causes for housing prices. This conclusion of the one-way relationship between housing prices and housing rents is good agreement with the observed in reality,that in the long term, the housing prices are gradually away from the basic value of rental housing capital. This leading to price earnings ratio and price rent ratios are significantly more than the value of international experience.(4) There is a special deeper institutional cause under the deviation between China’s urban housing prices and housing rents. The truth reason may be that the increasing wealth of our society at this stage leads to increasing residents’investment demand, and then leads to excessive concentration of capital in the property market because the current financial system is not fully developed in China. Therefore, the next step to guide the coordinated development of China’s urban housing prices and housing rents are two possible measures. Firstly, open up the channels of personal investment to further improve the China’s financial market system. Secondly, guide the steady development and further coordination between China’s urban housing market and the housing rental market.Compared with the existing research results, this paper has main academic value and innovation in the following areas:(1) The proposion of "factors’view" perspective will help researchers to improve the understanding of China’s urban housing prices and housing rents. Most of the existing mainstream researchs try to explain the imbalance between housing trading market and housing rental market, but not really explain the deviation between housing prices and housing rents. The proposion of "factors’view" perspective can promote the research in this field advancely and deeply from the "indirect interpretation of the market prices" to "factors directly explain the market prices".(2) The use of panel data model respectively to identify the key factors for the urban housing prices and housing rents, not only to strengthen the empirical study of housing prices, but also to fill China’s research gaps on house rents factors. There are very few studies on identifing factors for urban housing rents. This paper not only uses a better empirical method, but also fills the blank for the lack of theoretical study on urban housing rents in China.(3) The first time to identify the short-term relationship between the urban housing prices and housing rents using the the city level panel data. Most of the China’s Study used the national housing price index to obtain to short-term relationship between the urban housing prices and housing rents, which obtained very different conclusions. The national housing price index has two shortings, not exactly reflecting the cities’phenomonen and not instead of the price level perfectly. The innovative use of urban panel data would promote the related researchs.(4) The first time to consider the housing prices and housing rents as endogenous factors for each other in the "integral markets theory" framework, and to indentify the long-term relationship between China’s urban housing prices and housing rents. Most of the existing domestic empirical studies make the housing prices and housing rents as exogenous factors for each other when identifying the relationship between them. In this study, urban housing prices and housing rents simultaneous equations model was built, promoting the empirical research from the "exogenous" to "endogenous".更多还原