商品住宅的空置问题及对策研究
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摘要
商品住宅高空置问题是目前房地产运行中最突出的问题之一,空置适度与否直接影响到住宅产业和国民经济能否持续健康发展。因此,空置成为社会各界关注的焦点,如何消化当前住宅市场大量空置商品房以及避免新增空置商品住宅成为亟待解决的问题。
本文从对空置率的内涵理解开始,运用了比较分析的方法,对比分析了国内外关于空置的解释。同时,在比较分析国内外关于空置率的计算方法的基础上,对我国商品住宅空置率的计算方法进行了改进,建立了适合我国房地产业住宅市场空置率的计算方法,提出了关于衡量空置的统计指标体系。本文采用了规范研究和实证分析相结合的方法,以西安市住宅市场为例,收集资料数据,构建房地产空置率影响因素的框架,运用灰色关联度分析法对西安市商品住宅空置的影响因素进行全面深入的分析,并且运用灰色预测GM(1,1)模型对未来西安房地产市场的发展做出了展望。最后针对目前商品住宅过度空置的现状,从政府、开发商、金融机构以及中介机构四个方面提出了减少空置的政策建议。
At present,the commercial housing industry with high vacancy is one of the most serious problems in the real estate market.Whether vacant moderate or not directly affects the housing industry and the national economy healthy development.On account of its great influence on the housing industry and even the economy of the whole country,the Problem of the commodity residential housing vacancy attracts the attention of the society.How to digest the current massive housing vacant as well as avoid increasing new vacant commercial housing,which is urgently await to be solved.
This dissertation,starting from introduce the concept of the housing vacancy,utilizing the comparative analysis method,contrast and analyze the vacancy explanation of the domestic and foreign scholar's theory and vacancy rate computational method.On the foundation of discussing the computation methods of the residential housing vacancy rate,the author gives some suggestions on the improvement of method,and establishes new computational method.For the sake of better measuring real estate market,the author advances the index system of the residential housing vacancy.Taking the Xi'an housing market as the example,this article use the method which the standard research and the real diagnosis analysis unifies,,collect data,construct the influence factor frame of real estate vacancy rate.Then the author comprehensively analysis the influence factors of Xi'an commodity housing vacancy with grey interrelate method and make the forecast to the future Xi'an real estate market by gray forecast GM(1,1) model.Finally,aiming at present situation of excessive vacancy in commodity housing,the author put forward the policy and proposal of reducing vacancy from four aspects:the government,the Property developer,the financial organ as well as the facilitating agency.
本文从对空置率的内涵理解开始,运用了比较分析的方法,对比分析了国内外关于空置的解释。同时,在比较分析国内外关于空置率的计算方法的基础上,对我国商品住宅空置率的计算方法进行了改进,建立了适合我国房地产业住宅市场空置率的计算方法,提出了关于衡量空置的统计指标体系。本文采用了规范研究和实证分析相结合的方法,以西安市住宅市场为例,收集资料数据,构建房地产空置率影响因素的框架,运用灰色关联度分析法对西安市商品住宅空置的影响因素进行全面深入的分析,并且运用灰色预测GM(1,1)模型对未来西安房地产市场的发展做出了展望。最后针对目前商品住宅过度空置的现状,从政府、开发商、金融机构以及中介机构四个方面提出了减少空置的政策建议。
At present,the commercial housing industry with high vacancy is one of the most serious problems in the real estate market.Whether vacant moderate or not directly affects the housing industry and the national economy healthy development.On account of its great influence on the housing industry and even the economy of the whole country,the Problem of the commodity residential housing vacancy attracts the attention of the society.How to digest the current massive housing vacant as well as avoid increasing new vacant commercial housing,which is urgently await to be solved.
This dissertation,starting from introduce the concept of the housing vacancy,utilizing the comparative analysis method,contrast and analyze the vacancy explanation of the domestic and foreign scholar's theory and vacancy rate computational method.On the foundation of discussing the computation methods of the residential housing vacancy rate,the author gives some suggestions on the improvement of method,and establishes new computational method.For the sake of better measuring real estate market,the author advances the index system of the residential housing vacancy.Taking the Xi'an housing market as the example,this article use the method which the standard research and the real diagnosis analysis unifies,,collect data,construct the influence factor frame of real estate vacancy rate.Then the author comprehensively analysis the influence factors of Xi'an commodity housing vacancy with grey interrelate method and make the forecast to the future Xi'an real estate market by gray forecast GM(1,1) model.Finally,aiming at present situation of excessive vacancy in commodity housing,the author put forward the policy and proposal of reducing vacancy from four aspects:the government,the Property developer,the financial organ as well as the facilitating agency.
引文
[1]中华人民共和国国家统计局.中国国家统计年鉴[M].北京:中国统计出版社.2000-2007
[2]中国房地产市场年鉴编委会.中国房地产市场年鉴[M].北京:中国计划出版社2000-2006
[3]2008-2009年度全国房地产政策研究报告.http://viww.soufun.com
[4]赵江涛.我国商品住宅的空置及其对策研究[D].西安建筑科技大学硕士学位论文,2005:7-8
[5]Jud.G.D and J.Frew.A Typical ity and the Natural Vacancy Rate Hypothesis.A REWEUEA Journal,1990(18):295-301
[6]谢贤程.香港房地产市场[M].香港:商务印刷馆,1995
[7]孙峤,郑思齐,刘洪玉.住宅空置统计的国际比较及借鉴意义[J].统计研究,2005(8):8-12
[8]严每蓉.房地产统计体系中有关空置指标设置的探讨[J].中外房地擦很难导报,2000(21)
[9]贾海.商品房空置率计算方法初探[J].中国统计,2003(7):11-12
[10]贾海.我国商品房空置率计算方法及合理区间研究[J].城市开发.2004(3):70-74
[11]邓聚龙.灰预测与灰决策[M].武汉:华中科技大学出版社.2000
[12]罗党.灰色决策问题分析方法[M].河南:黄河水利出版社.2005
[13]肖新平,宋中民,李锋.灰技术基础及其应用[M].北京:科学出版社.2005
[14]刘思峰,党耀国.灰色系统理论及其应用[M].北京:科学出版社.2007
[15]西安房地产信息网.http://www.800j.com.cn
[16]西安市统计信息网.http://www.xatj.gov.cn
[17]西安统计局.西安市统计年鉴[M].中国统计出版社,2000-2007
[18]郭斌,张礼娜.西安市房地产业与相关产业的发展关系[J].价值工程,2008(4):38-40
[19]姚翠友,严艳茹,杨艳红.基于灰色关联的北京市商品房空置的影响因素分析[J].商场现代化,2008(11):186-188
[20]赵丽丽,焦继文.房价影响因素的灰色关联度分析[J].统计与决策,2007(23):74-75
[21]郝凤英,贺昌政.基于自组织数据挖掘的住宅空置影响因素分析[J].当代经济,2006(9):32-33
[22]王建刚.商品住宅市场分析与需求总量控制[D].武汉大学硕士学位论文,2005
[23]朱少颜.商品住宅空置问题的研究[D].暨南大学硕士学位论文,2004
[24]张仕廉,陈玲燕.空置商品房转化为廉租房的动力机制研究[J].建筑经济,2008(8):43-45
[25]潘向敏.我国廉租住房保障体制研究[D].复旦大学硕士学位论文,2008
[26]候本明.建立廉租房供应体系盘活空置商品住房[J].城市开发,1999(9):36-39
[27]郭峰.基于大系统控制的房地产预警系统及应用研究[D].重庆大学博士学位论文,2005
[28]郭涛.西安房地产预警系统研究[D].西安建筑科技大学硕士学位论文,2007
[29]贺亮.中国房地产住宅市场统计指标体系研究[D].南京林业大学硕士学位论文,2006
[30]包宗华.全面建立房地产金融体系[J].中国金融家,42-45
[31]郑鑫.完善天津住房公积金制度的对策研究[D].天津大学硕士学位论文,2006
[32]中华人民共和国国家统计局信息网 http://www.stars.gov.cn
[33]施梁.由商品房空置谈城市住房的可持续发展及其规划设计[J].华中建筑,1999(4)
[34]William C W.Vacancy,Search,and Price in a Housing Market Matching Model,Journal of Political Economy,VOI98,No.6,1990,P1270-1292.
[35]Thedore D.S.,The Duration of rental Housing Vacancies,Journal of Urban Economics,36,1994,P143-160.
[36]Patric H.Hendershott,Bryan Maegregor and Raymond Y.C.Tse,Estimation of the Rental Adjustment Proeess,Real Eeonomics,Vol.30,No.2,165-183,2002[33]
[37]Kerry D.Vandell,Tax Strueture and Natural Vacancy Rates in the Commercial Real Estate Market,Real Estate Economics,VOI.31,No,2,245-267,2003
[2]中国房地产市场年鉴编委会.中国房地产市场年鉴[M].北京:中国计划出版社2000-2006
[3]2008-2009年度全国房地产政策研究报告.http://viww.soufun.com
[4]赵江涛.我国商品住宅的空置及其对策研究[D].西安建筑科技大学硕士学位论文,2005:7-8
[5]Jud.G.D and J.Frew.A Typical ity and the Natural Vacancy Rate Hypothesis.A REWEUEA Journal,1990(18):295-301
[6]谢贤程.香港房地产市场[M].香港:商务印刷馆,1995
[7]孙峤,郑思齐,刘洪玉.住宅空置统计的国际比较及借鉴意义[J].统计研究,2005(8):8-12
[8]严每蓉.房地产统计体系中有关空置指标设置的探讨[J].中外房地擦很难导报,2000(21)
[9]贾海.商品房空置率计算方法初探[J].中国统计,2003(7):11-12
[10]贾海.我国商品房空置率计算方法及合理区间研究[J].城市开发.2004(3):70-74
[11]邓聚龙.灰预测与灰决策[M].武汉:华中科技大学出版社.2000
[12]罗党.灰色决策问题分析方法[M].河南:黄河水利出版社.2005
[13]肖新平,宋中民,李锋.灰技术基础及其应用[M].北京:科学出版社.2005
[14]刘思峰,党耀国.灰色系统理论及其应用[M].北京:科学出版社.2007
[15]西安房地产信息网.http://www.800j.com.cn
[16]西安市统计信息网.http://www.xatj.gov.cn
[17]西安统计局.西安市统计年鉴[M].中国统计出版社,2000-2007
[18]郭斌,张礼娜.西安市房地产业与相关产业的发展关系[J].价值工程,2008(4):38-40
[19]姚翠友,严艳茹,杨艳红.基于灰色关联的北京市商品房空置的影响因素分析[J].商场现代化,2008(11):186-188
[20]赵丽丽,焦继文.房价影响因素的灰色关联度分析[J].统计与决策,2007(23):74-75
[21]郝凤英,贺昌政.基于自组织数据挖掘的住宅空置影响因素分析[J].当代经济,2006(9):32-33
[22]王建刚.商品住宅市场分析与需求总量控制[D].武汉大学硕士学位论文,2005
[23]朱少颜.商品住宅空置问题的研究[D].暨南大学硕士学位论文,2004
[24]张仕廉,陈玲燕.空置商品房转化为廉租房的动力机制研究[J].建筑经济,2008(8):43-45
[25]潘向敏.我国廉租住房保障体制研究[D].复旦大学硕士学位论文,2008
[26]候本明.建立廉租房供应体系盘活空置商品住房[J].城市开发,1999(9):36-39
[27]郭峰.基于大系统控制的房地产预警系统及应用研究[D].重庆大学博士学位论文,2005
[28]郭涛.西安房地产预警系统研究[D].西安建筑科技大学硕士学位论文,2007
[29]贺亮.中国房地产住宅市场统计指标体系研究[D].南京林业大学硕士学位论文,2006
[30]包宗华.全面建立房地产金融体系[J].中国金融家,42-45
[31]郑鑫.完善天津住房公积金制度的对策研究[D].天津大学硕士学位论文,2006
[32]中华人民共和国国家统计局信息网 http://www.stars.gov.cn
[33]施梁.由商品房空置谈城市住房的可持续发展及其规划设计[J].华中建筑,1999(4)
[34]William C W.Vacancy,Search,and Price in a Housing Market Matching Model,Journal of Political Economy,VOI98,No.6,1990,P1270-1292.
[35]Thedore D.S.,The Duration of rental Housing Vacancies,Journal of Urban Economics,36,1994,P143-160.
[36]Patric H.Hendershott,Bryan Maegregor and Raymond Y.C.Tse,Estimation of the Rental Adjustment Proeess,Real Eeonomics,Vol.30,No.2,165-183,2002[33]
[37]Kerry D.Vandell,Tax Strueture and Natural Vacancy Rates in the Commercial Real Estate Market,Real Estate Economics,VOI.31,No,2,245-267,2003