上海房地产泡沫预测及风险防范问题研究
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摘要
上海作为全国重要的金融中心之一,是全国经济发展的龙头城市,因此上海经济的繁荣稳定对整个宏观经济的重要性是不言而喻的。上海房地产市场出现波动的话将会对周边城市的房地产市场产生负面影响,严重的话还将可能危及全国房地产市场乃至整个金融系统的稳定。因此如何保持上海房地产市场的健康发展从而促进金融市场的稳定是一个迫切需要解决的问题。
本文的目的是探索归纳出上海房地产泡沫的根源,提出一种判断房地产泡沫的衡量标准,能够预测未来两三年的泡沫情况,并针对结果提出有效的政策建议。
本文主要通过比较借鉴香港和美国房地产市场的发展经验,找出目前上海房地产市场所存在问题的原因,构建房地产泡沫综合指标系数来判断历年和预测未来房地产泡沫的程度,并分析归纳出导致房地产泡沫的几个主要诱因,从而为有针对性的调控纠偏政策的出台和实施指明了方向。
论文的第一章研究了房地产泡沫形成的根源,归纳了国内外房地产泡沫形成原因的相关理论,分析了影响中国房地产泡沫形成的短期原因和长期原因,其中短期原因有结构性失衡和政策性失衡,长期原因有土地价格和居民可支配收入。第二章以香港房地产市场为借鉴,描述了香港的房地产泡沫,并列举了香港房地产市场的风险防范措施。第三章首先列举分析了诸多影响房地产市场的因素。然后叙述了本文宏观经济变量与房地产泡沫相关性的分析方法,最后设计了三个房地产泡沫测度指标,分别是:房地产价格指数/CPI(价值方面、同步指标)、房地产开发投资额占固定资产投资的比例(供给方面、先行指标)以及房屋空置率(需求方面、滞后指标),其中房地产开发投资额为先行指标,反映对房地产市场提前一至三年做出的决策与承诺,具有预兆意义。房价增长率为同步指标,可以反映当前房地产市场景气度。空置率为滞后指标,作为房地产市场供给过剩和投资投机需求失衡的标志,可以用来检验房地产市场是否过热。并以这三个指标的乘积作为房地产泡沫综合指标系数,以此衡量房地产泡沫的存在与否及其大小。第四章首先描述了美国次贷危机对上海的影响以及国内房地产泡沫的形成及其对上海的影响,然后介绍了上海房地产市场的发展、现状与特点,并使用房地产泡沫综合指标系数对上海房地产市场的泡沫程度进行了评估和预测,最后以第三章所选取的五个因素来解释分析所得到的结果,其中还通过上海银行最新的信贷数据报告就不良贷款特征与美国次贷进行了类比。论文的第五章叙述了目前上海房地产市场所存在的主要问题,并提出相应的战略对策。
本文最后得出的结果是上海房地产市场在过去几年里泡沫逐渐膨胀,近年来已经有过热迹象,应警惕未来两三年里北京奥运会与上海世博会期间上海本地的房地产市泡沫情况。
本文的创新之处在于:(一)方法创新,对相关检测指标的选取做了修正,从而更加适用于中国的房地产市场;结合上海流动人口较多的特点,使用房地产出租面积与销售面积的比值作为空置率;利用居民有效收入来代替最常见的房价收入比。(二)观点创新,认为在我国实行土地批租制的情况下,房地产投资价值应小于产权完整的国家;结合我国现有的土地所有权制度,得出了房龄越高,住房价格波动幅度就越小,消费品特征也随之越明显,而投资价值相对弱化的观点;在房地产价格上升时期,以租赁价格作为衡量房地产泡沫程度的一个重要因素。租赁价格与房地产价格趋势偏离越明显,则泡沫越大;把房地产泡沫形成原因分为短期原因与长期原因。(三)思路创新,诸如针对上海城市流动人口问题,政府应加大对租赁市场的支持力度;把支持居民解决住房问题纳入财政支出政策的范围;允许把住房公积金用于支付房租;保持公积金贷款利率长期不变,进一步提高商业贷款利率等。
Shanghai, as one of the major financial center in China, is a city of powerhouse in China’s economic development. Therefore, it is apparent that the prosperity and stability of Shanghai’s economy is of great significance to the overall macro economy. The fluctuation in the real estate market in Shanghai will exert negative influence on the real estate market of those periphery cities. If the fluctuation is serious enough, it will jeopardize the stability of the national real estate market, and even the whole financial system. So it is an urgent problem to solve how to keep Shanghai real estate market in the track of sound development and promote the stability of the financial system.
To explore and induce the original causes of foam in the real estate market of Shanghai, this paper proposes a benchmark to measure and judge the foam in the real estate market, which can be used to predict the foam in two or three years, and effective policies and suggestions are put forward here specific to the outcome of the foam.
This paper is to find out the causes of problems in current Shanghai real estate market, construct a composite index to judge and predict the degree of the foam over the past years and in the future respectively by comparing the real estate of Shanghai with that of Hong Kong and the U.S. and utilizing their development experience as a source of reference. In addition, this paper educes several major precipitating factors that lead to the foam in the real estate market through the Analysis on Relativity. Therefore, this paper appropriately helps to define the directions in making some regulations and correcting errors in unveiling and implementing policies.
First, the origin of the formation of foam in real estate market is discussed and conclusions about the origin of the formation of foam in real estate market home and abroad are made. In the first chapter, some short-term and long-term causes leading to foam in China’s real estate market are obtained. Short-term causes include structural and policy-related unbalance, while long-term causes are exemplified by land price and residents disposable income. Next, with the source of reference of Hong Kong real estate, foam in it is described and measures of risk-prevention are also listed. In the third chapter, quite a number of elements that influence the real estate market are first listed and analyzed, and then the analytical approach used in this paper to the correlation between macroeconomic variable and foam in real estate market is explained, and finally, three indicators to measure the foam in real estate are designed, namely, Price Index of City Real Estate/CPI (Value, Concurrent Indicators), Ratio of the investment in real estate development to investment in fixed property(Supply, Leading Indicators), and Vacancy Rate in the real estate market(Demand, Lagging Indicators). The investment of real estate development, as a concurrent indicator, reflects the decisions and promises made one to three years ago on the real estate market, which is of prognostic importance. The growth rate of real estate price, as a leading indicator, reveals the degree of boom in the current real estate market. The vacancy rate, as a lagging indicator, can be utilized to test whether the real estate market is over-developed or not, because it is a symbol of the oversupply and the unbalance in the demand of investment or speculation in the real estate market. The product of the three indicators, as the composite index in real estate market, is used to judge whether there exists foam in real estate market and appraise the degree. At the beginning of Chapter Four, the impact of US Subprime Lending Crisis on Shanghai is described, and then the development history, current situation, and major characteristics of Shanghai real estate market are introduced. The composite index in real estate market is taken to evaluate and predict the degree of foam in Shanghai real estate market. At the end of this chapter, the result is analyzed with the help of the five elements shown in the third chapter. In addition, some comparisons about non-performing loans (also called dead loans) between Shanghai and the United States are made with the latest loan statistics of Bank of Shanghai. In the fifth chapter, some major problems of current Shanghai real estate market are under discussion, and some corresponding strategic methods are proposed as well. It is concluded in this paper that foam in the real estate marker of Shanghai has been inflating in the last several years and it has been overdeveloped. Thereby, it is of great significance that the foam in the real estate of Shanghai should be on people’s guard in Beijing Olympic Games and Shanghai EXPO in two or three years.
There are three innovations in this paper. First, it is the innovation in method. How to select the concerned test indicators is revised to make them more suitable for China’s real estate market. Moreover, on the basis of the large floating population in Shanghai, the ratio of lease area to the sales area of the real estate is regarded as the vacancy rate. What’s important, the Residents Disposable Income is used to take the place of the most commonplace House Price Ratio. Second, it is the innovation in points of view. It is proposed that the value of investment in the real estate should be less than that in those countries owning the entire property right on the condition that China is currently undertaking the Land Leasehold System. Attached to the fact that China is now undertake the Land Ownership System, it is also put forward that the older the real estate is, the smaller the extent of the fluctuation of housing price, and the more obvious the consumption characteristics will be, while the investment value will be reduced correspondingly. It is even raised that the leasing price used to measure the degree of foam in the real estate market is quite an important factor when the real estate price is up. If the deviation between the leasing price and real estate price is becoming bigger and bigger, then the foam will be compounding. Apart from them, the origin of the formation of foam in the real estate market is categorized into short-term and long-term causes. Third, it is the innovation in the train of thought. For example, on account of the problem of floating population in Shanghai, it is suggested that the government should step their support in the lease market, the support for the solution of the residents housing problems should be included into public financial expenditure policy, the housing fund should be allowed to pay the rents, and keeping the rate of housing fund loan rate constant for a long time and increasing the commercial loan rate should be undergone.
本文的目的是探索归纳出上海房地产泡沫的根源,提出一种判断房地产泡沫的衡量标准,能够预测未来两三年的泡沫情况,并针对结果提出有效的政策建议。
本文主要通过比较借鉴香港和美国房地产市场的发展经验,找出目前上海房地产市场所存在问题的原因,构建房地产泡沫综合指标系数来判断历年和预测未来房地产泡沫的程度,并分析归纳出导致房地产泡沫的几个主要诱因,从而为有针对性的调控纠偏政策的出台和实施指明了方向。
论文的第一章研究了房地产泡沫形成的根源,归纳了国内外房地产泡沫形成原因的相关理论,分析了影响中国房地产泡沫形成的短期原因和长期原因,其中短期原因有结构性失衡和政策性失衡,长期原因有土地价格和居民可支配收入。第二章以香港房地产市场为借鉴,描述了香港的房地产泡沫,并列举了香港房地产市场的风险防范措施。第三章首先列举分析了诸多影响房地产市场的因素。然后叙述了本文宏观经济变量与房地产泡沫相关性的分析方法,最后设计了三个房地产泡沫测度指标,分别是:房地产价格指数/CPI(价值方面、同步指标)、房地产开发投资额占固定资产投资的比例(供给方面、先行指标)以及房屋空置率(需求方面、滞后指标),其中房地产开发投资额为先行指标,反映对房地产市场提前一至三年做出的决策与承诺,具有预兆意义。房价增长率为同步指标,可以反映当前房地产市场景气度。空置率为滞后指标,作为房地产市场供给过剩和投资投机需求失衡的标志,可以用来检验房地产市场是否过热。并以这三个指标的乘积作为房地产泡沫综合指标系数,以此衡量房地产泡沫的存在与否及其大小。第四章首先描述了美国次贷危机对上海的影响以及国内房地产泡沫的形成及其对上海的影响,然后介绍了上海房地产市场的发展、现状与特点,并使用房地产泡沫综合指标系数对上海房地产市场的泡沫程度进行了评估和预测,最后以第三章所选取的五个因素来解释分析所得到的结果,其中还通过上海银行最新的信贷数据报告就不良贷款特征与美国次贷进行了类比。论文的第五章叙述了目前上海房地产市场所存在的主要问题,并提出相应的战略对策。
本文最后得出的结果是上海房地产市场在过去几年里泡沫逐渐膨胀,近年来已经有过热迹象,应警惕未来两三年里北京奥运会与上海世博会期间上海本地的房地产市泡沫情况。
本文的创新之处在于:(一)方法创新,对相关检测指标的选取做了修正,从而更加适用于中国的房地产市场;结合上海流动人口较多的特点,使用房地产出租面积与销售面积的比值作为空置率;利用居民有效收入来代替最常见的房价收入比。(二)观点创新,认为在我国实行土地批租制的情况下,房地产投资价值应小于产权完整的国家;结合我国现有的土地所有权制度,得出了房龄越高,住房价格波动幅度就越小,消费品特征也随之越明显,而投资价值相对弱化的观点;在房地产价格上升时期,以租赁价格作为衡量房地产泡沫程度的一个重要因素。租赁价格与房地产价格趋势偏离越明显,则泡沫越大;把房地产泡沫形成原因分为短期原因与长期原因。(三)思路创新,诸如针对上海城市流动人口问题,政府应加大对租赁市场的支持力度;把支持居民解决住房问题纳入财政支出政策的范围;允许把住房公积金用于支付房租;保持公积金贷款利率长期不变,进一步提高商业贷款利率等。
Shanghai, as one of the major financial center in China, is a city of powerhouse in China’s economic development. Therefore, it is apparent that the prosperity and stability of Shanghai’s economy is of great significance to the overall macro economy. The fluctuation in the real estate market in Shanghai will exert negative influence on the real estate market of those periphery cities. If the fluctuation is serious enough, it will jeopardize the stability of the national real estate market, and even the whole financial system. So it is an urgent problem to solve how to keep Shanghai real estate market in the track of sound development and promote the stability of the financial system.
To explore and induce the original causes of foam in the real estate market of Shanghai, this paper proposes a benchmark to measure and judge the foam in the real estate market, which can be used to predict the foam in two or three years, and effective policies and suggestions are put forward here specific to the outcome of the foam.
This paper is to find out the causes of problems in current Shanghai real estate market, construct a composite index to judge and predict the degree of the foam over the past years and in the future respectively by comparing the real estate of Shanghai with that of Hong Kong and the U.S. and utilizing their development experience as a source of reference. In addition, this paper educes several major precipitating factors that lead to the foam in the real estate market through the Analysis on Relativity. Therefore, this paper appropriately helps to define the directions in making some regulations and correcting errors in unveiling and implementing policies.
First, the origin of the formation of foam in real estate market is discussed and conclusions about the origin of the formation of foam in real estate market home and abroad are made. In the first chapter, some short-term and long-term causes leading to foam in China’s real estate market are obtained. Short-term causes include structural and policy-related unbalance, while long-term causes are exemplified by land price and residents disposable income. Next, with the source of reference of Hong Kong real estate, foam in it is described and measures of risk-prevention are also listed. In the third chapter, quite a number of elements that influence the real estate market are first listed and analyzed, and then the analytical approach used in this paper to the correlation between macroeconomic variable and foam in real estate market is explained, and finally, three indicators to measure the foam in real estate are designed, namely, Price Index of City Real Estate/CPI (Value, Concurrent Indicators), Ratio of the investment in real estate development to investment in fixed property(Supply, Leading Indicators), and Vacancy Rate in the real estate market(Demand, Lagging Indicators). The investment of real estate development, as a concurrent indicator, reflects the decisions and promises made one to three years ago on the real estate market, which is of prognostic importance. The growth rate of real estate price, as a leading indicator, reveals the degree of boom in the current real estate market. The vacancy rate, as a lagging indicator, can be utilized to test whether the real estate market is over-developed or not, because it is a symbol of the oversupply and the unbalance in the demand of investment or speculation in the real estate market. The product of the three indicators, as the composite index in real estate market, is used to judge whether there exists foam in real estate market and appraise the degree. At the beginning of Chapter Four, the impact of US Subprime Lending Crisis on Shanghai is described, and then the development history, current situation, and major characteristics of Shanghai real estate market are introduced. The composite index in real estate market is taken to evaluate and predict the degree of foam in Shanghai real estate market. At the end of this chapter, the result is analyzed with the help of the five elements shown in the third chapter. In addition, some comparisons about non-performing loans (also called dead loans) between Shanghai and the United States are made with the latest loan statistics of Bank of Shanghai. In the fifth chapter, some major problems of current Shanghai real estate market are under discussion, and some corresponding strategic methods are proposed as well. It is concluded in this paper that foam in the real estate marker of Shanghai has been inflating in the last several years and it has been overdeveloped. Thereby, it is of great significance that the foam in the real estate of Shanghai should be on people’s guard in Beijing Olympic Games and Shanghai EXPO in two or three years.
There are three innovations in this paper. First, it is the innovation in method. How to select the concerned test indicators is revised to make them more suitable for China’s real estate market. Moreover, on the basis of the large floating population in Shanghai, the ratio of lease area to the sales area of the real estate is regarded as the vacancy rate. What’s important, the Residents Disposable Income is used to take the place of the most commonplace House Price Ratio. Second, it is the innovation in points of view. It is proposed that the value of investment in the real estate should be less than that in those countries owning the entire property right on the condition that China is currently undertaking the Land Leasehold System. Attached to the fact that China is now undertake the Land Ownership System, it is also put forward that the older the real estate is, the smaller the extent of the fluctuation of housing price, and the more obvious the consumption characteristics will be, while the investment value will be reduced correspondingly. It is even raised that the leasing price used to measure the degree of foam in the real estate market is quite an important factor when the real estate price is up. If the deviation between the leasing price and real estate price is becoming bigger and bigger, then the foam will be compounding. Apart from them, the origin of the formation of foam in the real estate market is categorized into short-term and long-term causes. Third, it is the innovation in the train of thought. For example, on account of the problem of floating population in Shanghai, it is suggested that the government should step their support in the lease market, the support for the solution of the residents housing problems should be included into public financial expenditure policy, the housing fund should be allowed to pay the rents, and keeping the rate of housing fund loan rate constant for a long time and increasing the commercial loan rate should be undergone.
引文
1包宗华,“中国房地产泡沫破裂论”为什么会“破裂”[J]。中国房地产,2005 年,第 1 期,P7～P9。
2李涛、伍建平,房地产泡沫的成因、评估与预控[J]。建筑经济,2004 年第 5 期 P93～P95。
1 姜春海,中国房地产市场投机泡沫实证分析[J]。管理世界,2005 年第 12 期,P35～P38。
1 谢然浩,住房结构不合理仍普遍存在[N]。经济日报,2005 年 7 月 28 日第 2 版。
1 杨朝军、廖士光,“批租制”下的中国地产投资价值研究[J]。经济研究,2005 年 9 月,P66～P77。
1 巴曙松,驱动房地产价格上扬的金融因素[N]。中国房地产报,2005 年 6 月 13 日。
1《上海房地产市场预警指标体系研究》课题组,上海市房地产市场预警预报指标体系研究报告[R]2003 年 9月。
1 左小蕾,理清房地产价格调控的政策宗旨[N]。金融时报,2005 年 4 月 11 日
[1]巴曙松,货币政策为何对房地产市场日趋敏感[N]。中国经济时报,2005 年 4 月 4 日第 2版。
[2]包宗华,怎样看待我国的住房价格[J]。中国房地产,2004 第 1 期。
[3]车峰,利率对中美房地产市场影响的比较分析[D]。北京:首都经济贸易大学,2006。
[4]崔光灿,货币、汇率影响房价的传导关系[J]。上海房地(房地金融),2006 年 7 月。
[5]董佳慧,我国货币政策调控房价有效性研究[D]。吉林:东北师范大学,2006 年。
[6]段忠东、曾令华、黄泽先,房地产价格波动与银行信贷增长的实证研究[J]。金融论坛,2007 年第 2 期。
[7]方大炜,预期房价上涨率指标在监察房地产泡沫中的应用[J]。苏州大学学报,2007 年 3月第 2 期。
[8]高晓慧。地价和房价的基本关系[J]。中外房地产导报,2001 年第 6 期。
[9]韩立达、徐海鑫,论我国汇率调整与房地产业发展[J]。中国物价,2005 年 8 月。
[10]胡妍斌,香港银行业防范房地产信贷风险的措施[J]。新金融,2006 年第 8 期。
[11]建设部政策研究中心课题组,怎样认识当前房地产市场形式[N]。中国经营报,2004 年10 月 18 日第 4 版。
[12]姜春海,中国房地产市场投机泡沫实证分析[J]。管理世界,2005 年第 12 期。
[13]况伟大,房价与地价关系研究:模型及中国数据检验[J]。财贸经济,2005 年 11 月。
[14]况伟大,空间竞争、房价收入比与房价[J]。财贸经济,2004 年第 7 期。
[15]李非,台湾“泡沫经济”的形成与崩溃[J]。当代亚太,1995 年第 4 期。
[16]李宏瑾,房地产市场、银行信贷与经济增长——基于面板数据的经验研究[J]。国际金融研究,2005 年第 7 期。
[17]李健飞、史晨昱,我国银行信贷对房地产价格波动的影响[J]。上海财经大学学报,2005年第 4 期。
[18]李啸虎,城市房地产市场波动和预警系统研究--以乌鲁木齐市为例[D]新疆:新疆大学,理学、人文地理学,2006。
[19]刘琳,黄英,刘洪玉,房地产泡沫测度系数研究[J]。价格理论与实践,2003 年第 3 期。
[20]刘琳、刘洪玉,地价与房价关系的经济学分析[J]。数量经济技术经济研究,2003 年第 7期。
[21]刘明兴、罗俊伟,泡沫经济与金融危机[J]。经济学家,2000 年第 4 期。
[22]苗启虎、王方华,房价地价上涨孰因孰果[J]。价格理论与实践,2004 年第 12 期。
[23]邵贤炤，银行信贷行为与房地产泡沫――理论与国际经验研究[D]。吉林:吉林大学,2006。
[24]石长丽,房地产信贷与中国房地产泡沫相关性分析[D]。北京:对外经济贸易大学金融系,2006。
[25]宋勃、高波,房价与地价关系的因果检验:1998-2006[J]。当代经济科学,2007 年 1 月第 29 卷第 1 期。
[26]王金明、高铁梅,对我国房地产市场需求和供给函数的动态分析[J]。中国软科学,2004年第 4 期。
[27]翁少群,张红,基于模糊模式识别理论的中国房地产市场发展阶段判别研究[J]。土木工程学报,2004 年第 5 期
[28]吴广谋、黄佳,地价与房价关系探析[J]。价值工程,2007 年第 7 期。
[29]武康平、皮舜、鲁桂华,中国房地产市场与金融市场共生性的一般均衡分析[J]。数量经济技术经济研究 2004 年第 10 期。
[30]谢百三、王巍,我国商业银行在房地产热潮中的两难选择[J]。国际金融研究,2005 年第3 期。
[31]谢经荣、丰雷等,地产泡沫与金融危机:国际经验及其借鉴[M]。经济管理出版社,2002年 1 月。
[32]徐艳,北京房价过高的原因和房价控制[J]。城市问题,2002 年第 1 期。
[33]严金海,中国的房价与地价:理论、实证和政策分析[J]。数量经济技术经济研究,2006年第 1 期。
[34]杨慎,客观看待房价上涨问题[J]。中国房地信息,2003 年第 2 期。
[35]杨学亮,浅谈城市房价与低价[N]。中国环境管理干部学院学报,2007 年 3 月第 17 期。
[36]杨永华,论房价和房价收入比[J]。经济学家,2006 年 2 月。
[37]姚先国、黄炜华,地价与房价的关系[J]。中国土地,2001 年 9 月。
[38]野口悠纪雄著,汪斌译.土地经济学[M]。北京:商务印书馆,1997 年。
[39]叶艳兵和丁烈云,房地产预警指标体系设计研究[J]。基建优化,2001 年 6 月第 22 卷第3 期。
[40]叶瑛、胡海龙,香港房地产贷款风险防范经验借鉴[J]。西安金融,2004 年第 7 期。
[41]易宪容,房地产调控重点应落在银行信贷上[N]。中国城乡金融报,2006 年 11 月 20 日第3 版。
[42]易宪容,房地产市场走向:从 2006 年说起[J]。中国发展观察,2007 年 1 月。
[43]易宪容,中国房地产市场过热与风险预警[J]。财贸经济,2005 年第 5 期。
[44]张宏斌,房价中的地价因素及其作用分析[J]。中国土地,2001 年 9 月。
[45]张泓铭和陈则明,城市房地产预警研究(上)--综合模拟法的研究[J]。房地产市场,2004 年 11 月第 287 期。
[46]张涛、龚六堂、卜永祥,资产回报、住房按揭贷款与房地产均衡价格[J]。金融研究,2006年第 2 期。
[47]赵黎明,贾永飞,钱伟荣,房地产预警系统研究[J]。天津大学学报(社会科学版), 1999年第 4 期。
[48]张文新,国外地价与房价关系及其启示[J]。中国土地科学,2004 年第 3 期。
[49]周京奎,金融支持过度与房地产泡沫——理论与实证研究[M]北京:北京大学出版社,2005年 11 月。
[50]Adrian Cooper,The impact of interest rates and the housing market on the UK economy[J].Economic Outlook,2004.
[51]Agarwal,V.B.and R.A.Phillips,Mortgage Rate Buy-Downs:Implications for Housing Price Indexes[J]Social Science Quarterly,VOL65,1984.
[52]Alonso & William,Location and Land Use[M]Cambridge University Press,1964.
[53]Arcelus,F and A.Meltzer,The Markets for Housing and Housing Services[J].Journal of Money,Credit and Banking,1973,5.
[54]Bertrand Renaud,The 1985-1994 Global Real Estate Cycle:Its causes and Consequences[R].World Bank Research Paper,1995.
[55]Chen and Wang,The Procyclical Leverage Effect of Collateral Value on Bank Loans-Evidence from the Transaction Data of Taiwan[J].Economic Inquiry, July,2006.
[56]Cheshire P. & Sheppard S. ,The welfare economics of land use planning[J]. Journal of Urban Economics,2002,VOL52.
[57]Davies Gordon W. A model of the urban residential land and housing markets[J].The Canadian Journal of Economics, 1997, 10(3).
[58]Davis,Philip and Haibin Zhu,Bank lending and commercial property cycles:some cross-country evidence[R].BIS Working Papers,2004.
[59]Dongchul Cho,Interest Rate,Inflation,and Housing Price:With an Emphasis on Chonsei Price in Korea[R].15th NBER East Asian Seminar on Economics,Tokyo,May ,2004.
[60]Dowall D E & Landis J D,Land-Use controls and housing costs:an examination of San Francisco[J].Areuea Journal,1982,VOL10.
[61]Edward G, Joseph G, Hilber C. Housing affordability and land price:is there a crisis in American cities[C]. NBER Work Paper, 2002.
[62]Evans A. Housing prices and land prices in the South East-a review[M]. London,The House Builders Federation,1987.
[63]Franklin Allen and Douglas Gale,Bubbles and Crises[R].Working Paper,The Wharton School,University of Pennsylvania,1998.
[64]Gerlach,Stefan and Wensheng Peng,Bank lending and property prices in Hong Kong[J].Journal of Banking&Finance,2005(29).
[65]Goodman,J.L.,Interest Rates and Housing Demand 1993-1995:Common Sense versus Econometrics[R]Paper presented at the Mid-year AREUEA Meeting of 1995.
[66]Granger C,Investigation causal relations by econometric models and cross spectral methods[J].Econometrica,1963,37.
[67]Harris J. The effect of Real Rates of Interest on Housing Price[J].Journal of Real Estate Finance and Economics,1989,2.
[68]Kar-yiu Wong , Housing Market Bubbles and Currency Crisis : The Case of Thailand[J].Japanese Economic Review,2001,Vol.52.
[69]Kau,James B.and Donald C. Keenan,The theory of housing interest rates[J].Journal of financial and quantitative analysis,volume XV,No.4,November,1980.
[70]Kenny,G.,Modelling the Demand and Supply Sides of the Housing Market:Evidence from Ireland[J].Economic Modelling,1999,16.
[71]Kim J.,Housing price hike and price stabilization policy in Korea[A].Residential welfare and housing policies:the experience and future.Seoul Korea,2005.
[72]Monk J A, Royce S C, Dunn J. The relationship between land supply and housing production[M].York,Joseph Rowntree Foundation,1994.
[73]MostafaMorsiElAraby,The role of the state in managing urban land supply and prices in Egypt[J].Habitat International,2003,VOL27.
[74]Muth & Pichattl F,Cities and Housing[M].University of Chicago Press,1969.
[75]Norman G.Miller and Michael A.Sklarz.,A Note on Leading Indicators of Housing Market Price Trends[J].The Journal of Real Estate Research,1986,9.
[76]O’sullivan,Urban Economics(4th Edition)[M]The McGraw-Hill Companies,Inc,2000.
[77]Paul Krugman,Bubble,Boom,Crash:Theoretical Notes on Asia's Crisis[R]working paper,MIT,Cambridge,Massachusetts,1998.
[78]Peng R, WheatonW C. Effects of restrictive land supply on housing in HongKong and econometric analysis[J].Journal of Housing Research, 1994, 5(2).
[79]Richard J.Herring and Susan Wachter,Real estate booms and banking bust:an international perspective[R].working paper,University of Pennsylvania,1999.
[80]Smith B A.,The supply of urban housing[J]. The Quarterly Journal of Economics,1976,90(3).
[81]Takatoshi,Tokuo Iwaiskao,Explaining Asset Bubbles in Japan[J].Bank of Japan:Monetary and Economic Studies.Vol. 14,July,1996.
[82]Tse Raymond Y C.,Housing price, land supply and revenue from land sales[J].Urban Studies,1998, 35(8).
2李涛、伍建平,房地产泡沫的成因、评估与预控[J]。建筑经济,2004 年第 5 期 P93～P95。
1 姜春海,中国房地产市场投机泡沫实证分析[J]。管理世界,2005 年第 12 期,P35～P38。
1 谢然浩,住房结构不合理仍普遍存在[N]。经济日报,2005 年 7 月 28 日第 2 版。
1 杨朝军、廖士光,“批租制”下的中国地产投资价值研究[J]。经济研究,2005 年 9 月,P66～P77。
1 巴曙松,驱动房地产价格上扬的金融因素[N]。中国房地产报,2005 年 6 月 13 日。
1《上海房地产市场预警指标体系研究》课题组,上海市房地产市场预警预报指标体系研究报告[R]2003 年 9月。
1 左小蕾,理清房地产价格调控的政策宗旨[N]。金融时报,2005 年 4 月 11 日
[1]巴曙松,货币政策为何对房地产市场日趋敏感[N]。中国经济时报,2005 年 4 月 4 日第 2版。
[2]包宗华,怎样看待我国的住房价格[J]。中国房地产,2004 第 1 期。
[3]车峰,利率对中美房地产市场影响的比较分析[D]。北京:首都经济贸易大学,2006。
[4]崔光灿,货币、汇率影响房价的传导关系[J]。上海房地(房地金融),2006 年 7 月。
[5]董佳慧,我国货币政策调控房价有效性研究[D]。吉林:东北师范大学,2006 年。
[6]段忠东、曾令华、黄泽先,房地产价格波动与银行信贷增长的实证研究[J]。金融论坛,2007 年第 2 期。
[7]方大炜,预期房价上涨率指标在监察房地产泡沫中的应用[J]。苏州大学学报,2007 年 3月第 2 期。
[8]高晓慧。地价和房价的基本关系[J]。中外房地产导报,2001 年第 6 期。
[9]韩立达、徐海鑫,论我国汇率调整与房地产业发展[J]。中国物价,2005 年 8 月。
[10]胡妍斌,香港银行业防范房地产信贷风险的措施[J]。新金融,2006 年第 8 期。
[11]建设部政策研究中心课题组,怎样认识当前房地产市场形式[N]。中国经营报,2004 年10 月 18 日第 4 版。
[12]姜春海,中国房地产市场投机泡沫实证分析[J]。管理世界,2005 年第 12 期。
[13]况伟大,房价与地价关系研究:模型及中国数据检验[J]。财贸经济,2005 年 11 月。
[14]况伟大,空间竞争、房价收入比与房价[J]。财贸经济,2004 年第 7 期。
[15]李非,台湾“泡沫经济”的形成与崩溃[J]。当代亚太,1995 年第 4 期。
[16]李宏瑾,房地产市场、银行信贷与经济增长——基于面板数据的经验研究[J]。国际金融研究,2005 年第 7 期。
[17]李健飞、史晨昱,我国银行信贷对房地产价格波动的影响[J]。上海财经大学学报,2005年第 4 期。
[18]李啸虎,城市房地产市场波动和预警系统研究--以乌鲁木齐市为例[D]新疆:新疆大学,理学、人文地理学,2006。
[19]刘琳,黄英,刘洪玉,房地产泡沫测度系数研究[J]。价格理论与实践,2003 年第 3 期。
[20]刘琳、刘洪玉,地价与房价关系的经济学分析[J]。数量经济技术经济研究,2003 年第 7期。
[21]刘明兴、罗俊伟,泡沫经济与金融危机[J]。经济学家,2000 年第 4 期。
[22]苗启虎、王方华,房价地价上涨孰因孰果[J]。价格理论与实践,2004 年第 12 期。
[23]邵贤炤，银行信贷行为与房地产泡沫――理论与国际经验研究[D]。吉林:吉林大学,2006。
[24]石长丽,房地产信贷与中国房地产泡沫相关性分析[D]。北京:对外经济贸易大学金融系,2006。
[25]宋勃、高波,房价与地价关系的因果检验:1998-2006[J]。当代经济科学,2007 年 1 月第 29 卷第 1 期。
[26]王金明、高铁梅,对我国房地产市场需求和供给函数的动态分析[J]。中国软科学,2004年第 4 期。
[27]翁少群,张红,基于模糊模式识别理论的中国房地产市场发展阶段判别研究[J]。土木工程学报,2004 年第 5 期
[28]吴广谋、黄佳,地价与房价关系探析[J]。价值工程,2007 年第 7 期。
[29]武康平、皮舜、鲁桂华,中国房地产市场与金融市场共生性的一般均衡分析[J]。数量经济技术经济研究 2004 年第 10 期。
[30]谢百三、王巍,我国商业银行在房地产热潮中的两难选择[J]。国际金融研究,2005 年第3 期。
[31]谢经荣、丰雷等,地产泡沫与金融危机:国际经验及其借鉴[M]。经济管理出版社,2002年 1 月。
[32]徐艳,北京房价过高的原因和房价控制[J]。城市问题,2002 年第 1 期。
[33]严金海,中国的房价与地价:理论、实证和政策分析[J]。数量经济技术经济研究,2006年第 1 期。
[34]杨慎,客观看待房价上涨问题[J]。中国房地信息,2003 年第 2 期。
[35]杨学亮,浅谈城市房价与低价[N]。中国环境管理干部学院学报,2007 年 3 月第 17 期。
[36]杨永华,论房价和房价收入比[J]。经济学家,2006 年 2 月。
[37]姚先国、黄炜华,地价与房价的关系[J]。中国土地,2001 年 9 月。
[38]野口悠纪雄著,汪斌译.土地经济学[M]。北京:商务印书馆,1997 年。
[39]叶艳兵和丁烈云,房地产预警指标体系设计研究[J]。基建优化,2001 年 6 月第 22 卷第3 期。
[40]叶瑛、胡海龙,香港房地产贷款风险防范经验借鉴[J]。西安金融,2004 年第 7 期。
[41]易宪容,房地产调控重点应落在银行信贷上[N]。中国城乡金融报,2006 年 11 月 20 日第3 版。
[42]易宪容,房地产市场走向:从 2006 年说起[J]。中国发展观察,2007 年 1 月。
[43]易宪容,中国房地产市场过热与风险预警[J]。财贸经济,2005 年第 5 期。
[44]张宏斌,房价中的地价因素及其作用分析[J]。中国土地,2001 年 9 月。
[45]张泓铭和陈则明,城市房地产预警研究(上)--综合模拟法的研究[J]。房地产市场,2004 年 11 月第 287 期。
[46]张涛、龚六堂、卜永祥,资产回报、住房按揭贷款与房地产均衡价格[J]。金融研究,2006年第 2 期。
[47]赵黎明,贾永飞,钱伟荣,房地产预警系统研究[J]。天津大学学报(社会科学版), 1999年第 4 期。
[48]张文新,国外地价与房价关系及其启示[J]。中国土地科学,2004 年第 3 期。
[49]周京奎,金融支持过度与房地产泡沫——理论与实证研究[M]北京:北京大学出版社,2005年 11 月。
[50]Adrian Cooper,The impact of interest rates and the housing market on the UK economy[J].Economic Outlook,2004.
[51]Agarwal,V.B.and R.A.Phillips,Mortgage Rate Buy-Downs:Implications for Housing Price Indexes[J]Social Science Quarterly,VOL65,1984.
[52]Alonso & William,Location and Land Use[M]Cambridge University Press,1964.
[53]Arcelus,F and A.Meltzer,The Markets for Housing and Housing Services[J].Journal of Money,Credit and Banking,1973,5.
[54]Bertrand Renaud,The 1985-1994 Global Real Estate Cycle:Its causes and Consequences[R].World Bank Research Paper,1995.
[55]Chen and Wang,The Procyclical Leverage Effect of Collateral Value on Bank Loans-Evidence from the Transaction Data of Taiwan[J].Economic Inquiry, July,2006.
[56]Cheshire P. & Sheppard S. ,The welfare economics of land use planning[J]. Journal of Urban Economics,2002,VOL52.
[57]Davies Gordon W. A model of the urban residential land and housing markets[J].The Canadian Journal of Economics, 1997, 10(3).
[58]Davis,Philip and Haibin Zhu,Bank lending and commercial property cycles:some cross-country evidence[R].BIS Working Papers,2004.
[59]Dongchul Cho,Interest Rate,Inflation,and Housing Price:With an Emphasis on Chonsei Price in Korea[R].15th NBER East Asian Seminar on Economics,Tokyo,May ,2004.
[60]Dowall D E & Landis J D,Land-Use controls and housing costs:an examination of San Francisco[J].Areuea Journal,1982,VOL10.
[61]Edward G, Joseph G, Hilber C. Housing affordability and land price:is there a crisis in American cities[C]. NBER Work Paper, 2002.
[62]Evans A. Housing prices and land prices in the South East-a review[M]. London,The House Builders Federation,1987.
[63]Franklin Allen and Douglas Gale,Bubbles and Crises[R].Working Paper,The Wharton School,University of Pennsylvania,1998.
[64]Gerlach,Stefan and Wensheng Peng,Bank lending and property prices in Hong Kong[J].Journal of Banking&Finance,2005(29).
[65]Goodman,J.L.,Interest Rates and Housing Demand 1993-1995:Common Sense versus Econometrics[R]Paper presented at the Mid-year AREUEA Meeting of 1995.
[66]Granger C,Investigation causal relations by econometric models and cross spectral methods[J].Econometrica,1963,37.
[67]Harris J. The effect of Real Rates of Interest on Housing Price[J].Journal of Real Estate Finance and Economics,1989,2.
[68]Kar-yiu Wong , Housing Market Bubbles and Currency Crisis : The Case of Thailand[J].Japanese Economic Review,2001,Vol.52.
[69]Kau,James B.and Donald C. Keenan,The theory of housing interest rates[J].Journal of financial and quantitative analysis,volume XV,No.4,November,1980.
[70]Kenny,G.,Modelling the Demand and Supply Sides of the Housing Market:Evidence from Ireland[J].Economic Modelling,1999,16.
[71]Kim J.,Housing price hike and price stabilization policy in Korea[A].Residential welfare and housing policies:the experience and future.Seoul Korea,2005.
[72]Monk J A, Royce S C, Dunn J. The relationship between land supply and housing production[M].York,Joseph Rowntree Foundation,1994.
[73]MostafaMorsiElAraby,The role of the state in managing urban land supply and prices in Egypt[J].Habitat International,2003,VOL27.
[74]Muth & Pichattl F,Cities and Housing[M].University of Chicago Press,1969.
[75]Norman G.Miller and Michael A.Sklarz.,A Note on Leading Indicators of Housing Market Price Trends[J].The Journal of Real Estate Research,1986,9.
[76]O’sullivan,Urban Economics(4th Edition)[M]The McGraw-Hill Companies,Inc,2000.
[77]Paul Krugman,Bubble,Boom,Crash:Theoretical Notes on Asia's Crisis[R]working paper,MIT,Cambridge,Massachusetts,1998.
[78]Peng R, WheatonW C. Effects of restrictive land supply on housing in HongKong and econometric analysis[J].Journal of Housing Research, 1994, 5(2).
[79]Richard J.Herring and Susan Wachter,Real estate booms and banking bust:an international perspective[R].working paper,University of Pennsylvania,1999.
[80]Smith B A.,The supply of urban housing[J]. The Quarterly Journal of Economics,1976,90(3).
[81]Takatoshi,Tokuo Iwaiskao,Explaining Asset Bubbles in Japan[J].Bank of Japan:Monetary and Economic Studies.Vol. 14,July,1996.
[82]Tse Raymond Y C.,Housing price, land supply and revenue from land sales[J].Urban Studies,1998, 35(8).