北京市住房价格和租金的空间分异与相互关系
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摘要
当前中国住房销售市场、住房租赁市场发展不平衡,研究住房价格、租金的空间分异与相互关系,对建立"租售并举"的住房制度具有重要参考价值。利用2016年北京市各住宅小区的住房价格、租金数据,及2006—2016年北京市逐月住房销售价格指数、住房租赁价格指数,从时空尺度剖析了住房价格、租金的空间分异与相互关系,并剖析了背后的差异机制。结果表明:(1)北京市住房价格和租金的空间格局均呈多中心圈层递减结构,且南北差异明显,但租金的空间分异程度弱于住房价格。(2)住房价格具有中等程度的空间相关性,受政策等随机性因素影响相对较大,而租金具有强烈的空间相关性,受区位交通等确定性因素影响相对较大。(3)住房价格和租金的价格剖面线并不相同,住房价格易受学区、大型公园等的影响,而租金更易受就业所在地、建筑年龄等的影响。售租比呈混乱斑驳、相对均质的扁平化分布特征,且小区越高档,售租比越高。(4)北京市住房销售市场和住房租赁市场基本相对独立发展,更符合双重市场的特征。产生上述差异的主要原因在于住房销售市场和住房租赁市场的市场特征、服务人群以及市场发育程度不同。
At present, the development of China's housing sales market and housing rental market are unbalanced. The study on the spatial differentiation and relationship between housing prices and housing rents is of important reference value for the establishment of the "renting and purchasing" housing system. Using the data of housing prices and rental prices of residential units in 2016, and the 2006-2016 monthly housing sales price index and rental price index in Beijing, the paper explores the spatial differentiation and relationship between housing prices and rents from space-time scales, as well as the difference mechanism. The results show that:(1) The housing prices and rents both diminish from the multi-center to the outside. There are great differences in the distribution of housing prices and rents between the northern and southern parts of Beijing. Compared with the housing prices, rents show weaker spatial differentiation.(2) Housing prices have a moderate spatial correlation, which is mainly caused by uncertain factors(such as policy factors, and human factors), while rents have a strong spatial correlation, which is mainly caused by certain factors(such as location, and public facilities).(3) The profiles of housing prices and rents are different, since housing prices are sensitive to the school districts and urban large parks, but rents are more sensitive to the employment center and building age. The price-to-rent ratio is relatively homogeneous across the region, and the higher the housing price, the higher the price-to-rent ratio.(4) Beijing's housing sales market and housing rental market is in mutually independent development, in line with the characteristics of the dual market theory. The main reason for the above differences is that the market characteristics, the oriented population as well as the market development of the housing sales market and housing rental market are different.
At present, the development of China's housing sales market and housing rental market are unbalanced. The study on the spatial differentiation and relationship between housing prices and housing rents is of important reference value for the establishment of the "renting and purchasing" housing system. Using the data of housing prices and rental prices of residential units in 2016, and the 2006-2016 monthly housing sales price index and rental price index in Beijing, the paper explores the spatial differentiation and relationship between housing prices and rents from space-time scales, as well as the difference mechanism. The results show that:(1) The housing prices and rents both diminish from the multi-center to the outside. There are great differences in the distribution of housing prices and rents between the northern and southern parts of Beijing. Compared with the housing prices, rents show weaker spatial differentiation.(2) Housing prices have a moderate spatial correlation, which is mainly caused by uncertain factors(such as policy factors, and human factors), while rents have a strong spatial correlation, which is mainly caused by certain factors(such as location, and public facilities).(3) The profiles of housing prices and rents are different, since housing prices are sensitive to the school districts and urban large parks, but rents are more sensitive to the employment center and building age. The price-to-rent ratio is relatively homogeneous across the region, and the higher the housing price, the higher the price-to-rent ratio.(4) Beijing's housing sales market and housing rental market is in mutually independent development, in line with the characteristics of the dual market theory. The main reason for the above differences is that the market characteristics, the oriented population as well as the market development of the housing sales market and housing rental market are different.
引文
[1]宋伟轩,刘春卉.长三角一体化区域城市商品住宅价格分异机理研究.地理研究,2018,37(1):92-102.[Song Weixuan,Liu Chunhui.The price differentiation mechanism of commercial housing in the Yangtze River Delta.Geographical Research,2018,37(1):92-102.]
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[5]王敏,黄滢.限购和房产税对房价的影响:基于长期动态均衡的分析.世界经济,2013,(1):141-159.[Wang Min,Huang Ying.Restrictions on purchasing and property taxes on house prices:An analysis based on long-term dynamic equilibrium.The Journal of World Economy,2013,(1):141-159.]
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[10]Kuntz M,Helbich M.Geostatistical mapping of real estate prices:An empirical comparison of Kriging and Cokriging.International Journal of Geographical Information Science,2014,28(9):1904-1921.
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[12]王文莉,武优勐.基于房价发现过程的房价租金关系研究综述.经济问题探索,2015,(1):173-178.[Wang Wenli,Wu Youmeng.A review of the relationship of housing and rent based on housing price discovery process.Inquiry into Economic Issues,2015,(1):173-178.]
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[15]贾士军,周春山.城市房屋参考租金测定与空间分布:以广州为例.经济地理,2009,29(4):618-623.[Jia Shijun,Zhou Chunshan.Reference rent measurement and the spatial distribution for urban real estate:A case of Guangzhou.Economic Geography,2009,29(4):618-623.]
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[18]Clayton J.Rational expectations,market fundamentals and house price volatility.Real Estate Economics,1996,24(4):441-470.
[19]Case K E,Shiller R J,Quigley J M.Comparing wealth effects:The stock market versus the housing market.NBERWorking Paper Series,2001:1-17.
[20]Gallin J.The long-run relationship between house prices and rents.Real Estate Economics,2008,36(4):635-658.
[21]周京奎.货币政策、银行贷款与住房价格:对中国4个直辖市的实证研究.财贸经济,2005,26(5):22-27.[Zhou Jingkui.Monetary policy,bank loans and housing prices:An empirical study of four municipalities in China.Finance&Trade Economics,2005,26(5):22-27.]
[22]周永宏.当前我国房价与租金关系的经济学分析:一个市场区隔理论的解释.当代财经,2005,(10):13-16.[Zhou Yonghong.An economic analysis of the relationship between housing price and rent in China:An explanation of market segmentation theory.Contemporary Finance&Economics,2005,(10):13-16.]
[23]杜红艳,马永开.我国房价与租金Granger因果关系的实证研究.管理评论,2009,21(1):94-99.[Du Hongyan,Ma Yongkai.An empirical study of Granger causality between the housing price and the rent of Chinese real estate market.Management Review,2009,21(1):94-99.]
[24]张所地,赵华平,李斌.房地产宏观调控影响下的房价与租金关系研究:基于中国35个大中城市面板数据的实证分析.数理统计与管理,2014,33(2):305-316.[Zhang Suodi,Zhao Huaping,Li Bin.The relationship between real estate price and rent under the effect of macro-control:Empirical evidence from thirty-five large and medium scale cities of China.Journal of Applied Statistics and Management,2014,33(2):305-316.]
[25]于璐,郑思齐,刘洪玉.住房价格梯度的空间互异性及影响因素.经济地理,2008,28(3):406-410.[Yu Lu,Zheng Siqi,Liu Hongyu.The spatial variation and affecting factors of the housing price gradients:The case of Beijing.Economic Geography,2008,28(3):406-410.]
[26]秦波,焦永利.北京住宅价格分布与城市空间结构演变.经济地理,2010,30(11):1815-1820.[Qin Bo,Jiao Yongli.Housing price distribution and urban spatial restructuring in Beijing.Economic Geography,2010,30(11):1815-1820.]
[27]Gunterman K L,Norrbin S.Explaining the variability in apartment rents.Real Estate Economics,1987,15(4):321-340.
[28]徐建华.现代地理学中的数学方法:2版.北京:高等教育出版社,2002.[Xu Jianhua.Mathematical Methods in Contemporary Geography:2nd ed.Beijing:Higher Education Press,2002.]
[29]王洋,方创琳,盛长元.扬州市住宅价格的空间分异与模式演变.地理学报,2013,68(8):1082-1096.[Wang Yang,Fang Cuanglin,Sheng Changyuan.Spatial differentiation and model evolution of housing prices in Yangzhou.Acta Geographica Sinica,2013,68(8):1082-1096.]
[30]崔娜娜,冯长春,宋煜.北京市居住用地出让价格的空间格局及影响因素.地理学报,2017,72(6):1049-1062.[Cui Nana,Feng Changchun,Song Yu.Spatial pattern of residential land parcels and determinants of residential land price in Beijing since 2004.Acta Geographica Sinica,2017,72(6):1049-1062.]
[31]吴学文,晏路明.普通Kriging法的参数设置及变异函数模型选择方法:以福建省一月均温空间内插为例.地球信息科学,2007,9(3):104-108.[Wu Xuewen,Yan Luming.Setting parameters and choosing optimum semivariogram models of ordinary Kriging interpolation:A case study of spatial interpolation to January average temperature of Fujian province.Geo-Information Science,2007,9(3):104-108.]
[32]楼立明.城市地价信息的空间分析及其应用研究.杭州:浙江大学硕士学位论文,2004.[Lou Liming.Spatial analysis and application of urban land price information.Hangzhou:Master Dissertation of Zhejiang University,2004.]
[33]王劲峰.空间分析.北京:科学出版社,2006.[Wang Jinfeng.Spatial Analysis.Beijing:Science Press,2006.]
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(1)静态租赁回报率:指年内租金收益与售价的占比,根据当前租金回报,选择投资时机。
(2)长期租赁回报率:指租金增长情况下,长期出租物业可获得的租金回报,可判断长期的租金收益。
(3)5年租赁后转售回报率:指5年内持有物业并出租,于第5年末出售物业可获得的回报率,包含租金回报和房产增值两部分收益后测算得到的回报率。根据转售回报,判断最佳转售时机。
[2]刘海猛,石培基,潘竟虎,等.中国城镇房价收入比时空演变的多尺度分析.地理科学,2015,35(10):1280-1287.[Liu Haimeng,Shi Peiji,Pan Jinghu,et al.Spatio-temporal evolution on housing price to income ratio of China by multiscale analysis.Scientia Geographica Sinica,2015,35(10):1280-1287.]
[3]Hill R J,Syed I A.Hedonic price-rent ratios,user cost,and departures from equilibrium in the housing market.Regional Science and Urban Economics,2016,56:60-72.
[4]甘霖,冯长春,王乾.北京市房价与地价的动态关系:基于结构方程模型的实证分析.地理研究,2016,35(10):1831-1845.[Gan Lin,Feng Changchun,Wang Qian.Dynamic relationship between housing price and land price in Beijing:Based on structural equation modeling.Geographical Research,2016,35(10):1831-1845.]
[5]王敏,黄滢.限购和房产税对房价的影响:基于长期动态均衡的分析.世界经济,2013,(1):141-159.[Wang Min,Huang Ying.Restrictions on purchasing and property taxes on house prices:An analysis based on long-term dynamic equilibrium.The Journal of World Economy,2013,(1):141-159.]
[6]马敏蕾,吕斌,冯长春.基于GIS基础上的北京住房价格空间格局研究.中国国土资源经济,2008,21(12):26-28.[Ma Minlei,Lv Bin,Feng Changchun.Study on the spatial pattern of Beijing housing price based on GIS.Resource Industrial Economy,2008,21(12):26-28.]
[7]付益松,张明.城市房价空间分布及其影响因素分析.测绘科学,2017,42(8):49-52.[Fu Yisong,Zhang Ming.Research on the spatial distribution of city housing price and its influencing factors.Science of Surveying and Mapping,2017,42(8):49-52.]
[8]孙倩,洪开荣.基于Cokriging的住房价格空间格局分析:以长沙市为例.经济地理,2014,34(12):99-105.[Sun Qian,Hong Kairong.The house price spatial distribution pattern analysis based on Cokriging:The case of Changsha.Economic Geography,2014,34(12):99-105.]
[9]梅志雄,黎夏.基于ESDA和Kriging方法的东莞市住宅价格空间结构.经济地理,2008,28(5):862-866.[Mei Zhixiong,Li Xia.Spatial analysis of house's price in Dongguan based on ESDA and Kriging techniques.Economic Geography,2008,28(5):862-866.]
[10]Kuntz M,Helbich M.Geostatistical mapping of real estate prices:An empirical comparison of Kriging and Cokriging.International Journal of Geographical Information Science,2014,28(9):1904-1921.
[11]蔡菊花,贾士军.基于Hedonic模型的住宅租赁价格影响因素分析.经济研究导刊,2010,(30):150-152.[Cai Juhua,Jia Shijun.Analysis of influencing factors of residential rental price based on hedonic price model.Economic Research Guide,2010,(30):150-152.]
[12]王文莉,武优勐.基于房价发现过程的房价租金关系研究综述.经济问题探索,2015,(1):173-178.[Wang Wenli,Wu Youmeng.A review of the relationship of housing and rent based on housing price discovery process.Inquiry into Economic Issues,2015,(1):173-178.]
[13]Zhai D,Shang Y S,Wen H Z,et al.Housing price,housing rent,and rent-price ratio:Evidence from 30 cities in China.Journal of Urban Planning and Development,2018,144(1):1-9.
[14]苏亚艺,朱道林,耿槟.北京市住宅租金空间结构及其影响因素.经济地理,2014,34(4):64-69.[Su Yayi,Zhu Daolin,Geng Bin.The spatial structure and affecting factors of the housing rental in Beijing.Economic Geography,2014,34(4):64-69.]
[15]贾士军,周春山.城市房屋参考租金测定与空间分布:以广州为例.经济地理,2009,29(4):618-623.[Jia Shijun,Zhou Chunshan.Reference rent measurement and the spatial distribution for urban real estate:A case of Guangzhou.Economic Geography,2009,29(4):618-623.]
[16]Ozanne L,Thibodeau T.Explaining metropolitan housing price differences.Journal of Urban Economics,1983,13(1):51-66.
[17]郑文娟.中国城市住房价格与住房租金的影响因素及相互关系研究.杭州:浙江大学博士学位论文,2011.[Zheng Wenjuan.Study on the determinants and relationship between China's urban housing prices and rents.Hangzhou:Doctoral Dissertation of Zhejiang University,2011.]
[18]Clayton J.Rational expectations,market fundamentals and house price volatility.Real Estate Economics,1996,24(4):441-470.
[19]Case K E,Shiller R J,Quigley J M.Comparing wealth effects:The stock market versus the housing market.NBERWorking Paper Series,2001:1-17.
[20]Gallin J.The long-run relationship between house prices and rents.Real Estate Economics,2008,36(4):635-658.
[21]周京奎.货币政策、银行贷款与住房价格:对中国4个直辖市的实证研究.财贸经济,2005,26(5):22-27.[Zhou Jingkui.Monetary policy,bank loans and housing prices:An empirical study of four municipalities in China.Finance&Trade Economics,2005,26(5):22-27.]
[22]周永宏.当前我国房价与租金关系的经济学分析:一个市场区隔理论的解释.当代财经,2005,(10):13-16.[Zhou Yonghong.An economic analysis of the relationship between housing price and rent in China:An explanation of market segmentation theory.Contemporary Finance&Economics,2005,(10):13-16.]
[23]杜红艳,马永开.我国房价与租金Granger因果关系的实证研究.管理评论,2009,21(1):94-99.[Du Hongyan,Ma Yongkai.An empirical study of Granger causality between the housing price and the rent of Chinese real estate market.Management Review,2009,21(1):94-99.]
[24]张所地,赵华平,李斌.房地产宏观调控影响下的房价与租金关系研究:基于中国35个大中城市面板数据的实证分析.数理统计与管理,2014,33(2):305-316.[Zhang Suodi,Zhao Huaping,Li Bin.The relationship between real estate price and rent under the effect of macro-control:Empirical evidence from thirty-five large and medium scale cities of China.Journal of Applied Statistics and Management,2014,33(2):305-316.]
[25]于璐,郑思齐,刘洪玉.住房价格梯度的空间互异性及影响因素.经济地理,2008,28(3):406-410.[Yu Lu,Zheng Siqi,Liu Hongyu.The spatial variation and affecting factors of the housing price gradients:The case of Beijing.Economic Geography,2008,28(3):406-410.]
[26]秦波,焦永利.北京住宅价格分布与城市空间结构演变.经济地理,2010,30(11):1815-1820.[Qin Bo,Jiao Yongli.Housing price distribution and urban spatial restructuring in Beijing.Economic Geography,2010,30(11):1815-1820.]
[27]Gunterman K L,Norrbin S.Explaining the variability in apartment rents.Real Estate Economics,1987,15(4):321-340.
[28]徐建华.现代地理学中的数学方法:2版.北京:高等教育出版社,2002.[Xu Jianhua.Mathematical Methods in Contemporary Geography:2nd ed.Beijing:Higher Education Press,2002.]
[29]王洋,方创琳,盛长元.扬州市住宅价格的空间分异与模式演变.地理学报,2013,68(8):1082-1096.[Wang Yang,Fang Cuanglin,Sheng Changyuan.Spatial differentiation and model evolution of housing prices in Yangzhou.Acta Geographica Sinica,2013,68(8):1082-1096.]
[30]崔娜娜,冯长春,宋煜.北京市居住用地出让价格的空间格局及影响因素.地理学报,2017,72(6):1049-1062.[Cui Nana,Feng Changchun,Song Yu.Spatial pattern of residential land parcels and determinants of residential land price in Beijing since 2004.Acta Geographica Sinica,2017,72(6):1049-1062.]
[31]吴学文,晏路明.普通Kriging法的参数设置及变异函数模型选择方法:以福建省一月均温空间内插为例.地球信息科学,2007,9(3):104-108.[Wu Xuewen,Yan Luming.Setting parameters and choosing optimum semivariogram models of ordinary Kriging interpolation:A case study of spatial interpolation to January average temperature of Fujian province.Geo-Information Science,2007,9(3):104-108.]
[32]楼立明.城市地价信息的空间分析及其应用研究.杭州:浙江大学硕士学位论文,2004.[Lou Liming.Spatial analysis and application of urban land price information.Hangzhou:Master Dissertation of Zhejiang University,2004.]
[33]王劲峰.空间分析.北京:科学出版社,2006.[Wang Jinfeng.Spatial Analysis.Beijing:Science Press,2006.]
[34]汤国安,杨昕.地理信息系统空间分析实验教程.北京:科学出版社,2006.[Tang Guo'an,Yang Xin.Experiment Tutorial of Geographic Information System Spatial Analysis.Beijing:Science Press,2006.]
[35]Cambardella C A,Moorman T B,Novak J M,et al.Field-scale variability of soil properties in central Iowa soils.Soil Science Society of America Journal,1994,58(5):1501-1511.
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(1)静态租赁回报率:指年内租金收益与售价的占比,根据当前租金回报,选择投资时机。
(2)长期租赁回报率:指租金增长情况下,长期出租物业可获得的租金回报,可判断长期的租金收益。
(3)5年租赁后转售回报率:指5年内持有物业并出租,于第5年末出售物业可获得的回报率,包含租金回报和房产增值两部分收益后测算得到的回报率。根据转售回报,判断最佳转售时机。
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