摘要
居民住房支付能力问题受到了社会的普遍关注和政府的高度重视。城市空间结构理论表明,城市土地利用与交通系统之间存在密切的互动关系,在空间上,住房成本与交通成本此消彼长。因此,单纯考虑住房成本与收入之间的比例关系不能全面的衡量可支付性。正是在这样的现实与理论背景之下,为了提供更为精细和实用的可支付性及其空间分布的信息,本文设计了住房与交通综合可支付性指数,并以北京为例进行了实际的计算与分析。
利用北京市城八区通勤成本、住房成本及家庭收入的数据,本文从是否拥有私家车和住房类型两个维度将家庭分成六个类型,分别计算了不同类型家庭的住房与交通综合可支付性指数(THAI)。通过将得到的指数与区块离城市中心的距离进行了线性回归,研究该指数的空间分布情况。之后,本文又将分类指数合并成为有车家庭、无车家庭和所有家庭的THAI,并进行了比较分析。
结果表明,有车家庭的THAI平均为59.30%,无车家庭的THAI平均为48.58%,所有家庭的THAI平均为52.18%(比传统的住房可支付性指数HAI高约10%)。自有住房-有车家庭的THAI随区块离城市中心距离的变化不呈现显著的梯度,住房成本与通勤成本的力量大致相当;自有住房-无车家庭的THAI随区块到城市中心距离的变化呈现显著的负梯度,主要是住房成本占主导;居住在市场化租赁房的家庭的THAI随到城市中心距离的变化呈现显著的正梯度,主要是通勤成本占主导。
本文的实证研究结果能够帮助政策制定者评估不同区位的住房与交通综合可支付性,为其进行保障性住房选址或交通规划等决策提供支持。最后,本文还提出了若干旨在提高居民住房与交通综合支付能力的政策建议。
The issue of housing affordability has attracted wide attention and concern from almost every aspect of the society. According to the theory of urban spatial structure, urban land use and urban transportation are closely integrated. In the spatial models, the rent (housing costs) is negatively correlated with transportation costs. Therefore, one cannot comprehensively appraise housing affordability by simply considering the ratio between housing costs and income. Under such theoretical and empirical background and in order to provide a more precise and practical spatial distribution of housing affordability, this paper establishes a housing affordability index which integrates both transportation costs and housing costs. In addition, a practical example of Beijing is provided.
Using zone-level data of household income, housing cost and transportation cost of 64 residential zones in Beijing, this paper calculates the new affordability index for six types of households sorted according to housing unit type and car-ownership. This thesis uses a new information tool, Transportation and Housing Affordability Index(THAI), to quantify the impact of transportation cost on the affordability of housing in Beijing. The indices are regressed on the distance from block to urban centre to examine the spatial distribution of the THAI index. The THAI among households with cars, households without cars and all households are compared and analyzed later on. Later in this paper, we further compare and analyze the indices for households with cars, households without cars and all households.
The result shows that the average THAI of the households with cars is 59.30%,while that of the households without cars is 48.58% and that of all the households is 52.18% (10% more than the traditional Housing Affordability Index HAI). The THAI of home owners with cars does not change significantly while the distance between the block and the urban centre changes,and housing costs and transportation costs are comparable in importance; The THAI of home owners without cars declines significantly while the distance between the block and the urban centre increases,and housing costs are more important; The THAI of households who live in market rental housing shows obvious positive gradient while the distance between the block and the urban centre changes, and transportation costs are more important.
The result of this thesis helps housing policy makers assess comprehensively housing and transportation affordability, and lends support to traffic planning, housing policy, urban planning and land supply. In the end, suggestions on how to comprehensively appraise housing affordability of low-income household are provided.
引文
[1]郑思齐.住房需求的微观经济分析.北京:中国建筑工业出版社,2006. 91~104
[2]郑思齐,张文忠.住房成本与通勤成本的空间互动关系——来自北京市场的微观证据及其宏观含义.地理科学进展,2007,3: 35-42
[3] Center for Housing Policy. A Heavy Load: The Combined Housing and Transportation Burdens of Working Families. 2006 (10)
[4] Siqi Zheng and Zhenpeng Yang. Housing Price Gradient with Respect to True Commuting Time in Beijing: Emp irical Estimation and Its Implications. Proceedings of 2007 ICM Conference, Wuhan, 2007
[5]郑思齐,丁文捷,陆化普.住房、交通与城市空间规划.城市问题,2009, 1: 29-33
[6]王方,陈金川,陈艳艳.交通SP调查的均匀设计方法.城市交通. 2005, 8: 69-72
[7]王方,陈金川,张德欣. SP调查在交通方式选择模型中的应用.交通运输系统工程与信息. 2007, 10: 90-95
[8]北京市房地产交易管理网http://bjfdc.bjjs.gov.cn
[9]搜房网http://esf.soufun.com
[10]我爱我家http://bj.5i5j.com
[11]链家http://bjfdc.bjjs.gov.cn
[12]郝前进,周仁.住房可支付性的多维评判标准.中国房地产. 2008, 9: 13-15
[13]赵丹.北京市二手房住房可支付性研究.现代经济信息. 2009, 14: 56
[14]陈杰,郝前进,郑麓漪.动态房价收入比——判断中国居民住房可支付性的新思路.中国房地产. 2008, 1: 25-28
[15]李进涛,谭术魁,汪文雄.国外住房可支付性研究概要.城市问题. 2009, 5: 7-13
[16]周仁.住房可支付性的判断和城市政府住房政策的选择:[硕士学位论文].上海:复旦大学经济学院. 2009
[17]刘中显.北京市居民住房可支付性浅探.北京物价,1998,8:10~13
[18]夏刚,任宏,杨莉琼.城市不同收入家庭住房可支付性研究.建筑经济,2008,8:50~54
[19]吴刚.城市居民住房可支付性研究——基于2000—2008我国10城市的经验数据.城市发展研究,2009,9:20~25
[20]刘朝马.国际住房可支付性现状启示与我国的政策选择.统计研究,2007,10:88~90
[21]戚文举,叶荣德.基于不同视角的国外住房可支付性测度研究述评.华东经济管理,2009,10:137~140
[22]余凌志,屠梅曾.基于收入余额指标的城镇低收入家庭住房可支付性评价模型.上海交通大学学报,2008,9:1506~1510
[23]刘蕾,王珊珊,王强.基于住房可支付性的经济适用房价格预测探讨——以河北省为例.现代商贸工业,2009,13:120~121
[24]战友,王伟.经济基本面、住宅价格与居民住房可支付性——以区域差异为视角的面板数据模型估计.经济问题探索,2008,9:171~175
[25]刘琳,郑思齐.居民住房可支付性评价指标比较与分析.宏观经济研究,2005,2:35~37
[26] Mark Duda,郑思齐.利率和收入差距如何左右住房可支付性.城市开发,2006,10:53~55
[27]刘琳.如何度量城镇居民家庭住房可支付性.中国投资,2007,5:14
[28]陈洪艳.天津市城镇家庭住房可支付性测量及分析.商场现代化,2008,4:289~291
[29]张丽.我国城市居民住房可支付性研究:[硕士学位论文].大连:东北财经大学. 2005
[30]黄顺英.我国居民住房可支付性与住房问题研究.建筑经济,2009,10:39~41
[31]向肃一,龙奋杰.中国城市居民住房可支付性研究.城市发展研究,2007,2:29~33
[32]张智.住房可支付性的概念辨析.住宅产业,2009,4:86~87
[33]刘洪玉,耿媛元.住宅可支付性分析.建筑经济,1999,7:39~41
[34]张清勇.中国城镇居民的住房可支付性:1991—2005.财贸经济,2007,4:79~85
[35] Center for Transit Oriented Development and Center for Neighborhood Technology. (2006)“The Affordability Index: A New Tool for Measuring the True Affordability of a Housing Choice”Brookings Institute. (www.brookings.edu/metro/umi/20060127_affindex.pdf).
[36] Lynn Fisher, Henry Pollakowski and Jeffrey Zabel.“Amenity-Based Housing Affordability Indexes”. Real Estate Economics. 2009: 37(4), 705-746(42).
[37]郑思齐,曹洋.居住与就业空间关系的决定机理和影响因素——对北京市通勤时间和通勤流量的实证研究,城市发展研究, 2009, 6: 29-35