中学学区对周边小区二手房房价的溢价分析——以深圳市为例
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摘要
选取深圳市3个主要城区185个居住小区的数据,从中学质量(省级或非省级中学)的维度进行量化建立特征价格模型,研究深圳市中学教育设施对房价资本化程度的影响。结果表明,在影响中学周边小区二手房房价的因素中,学校特征因素有显著的影响,其中升学率、本硕以上教师和重点学校有正向助推作用,而生师比有负向抑制作用。影响省级中学和非省级中学周边房价的学校特征因素存在差异,其中在非省级中学周边小区二手房房价中,主要是升学率和生师比等特征的影响,而在省级中学周边小区二手房房价中,主要是本硕以上教师人数和生师比等特征影响。与地铁和CBD的距离以及楼龄对中学周边房价表现为负影响,且与重大商业服务中心和地铁站距离每增加1 km,房价分别下降13.9%和28.7%,楼龄每增加1年,房价下降6.8%。研究结果揭示了中学教育质量特征对住宅价格的影响及程度,综合反映了深圳市中学学区房价格的影响机制。
This paper selects the data of 185 residential quarters in three major urban districts of Shenzhen, and establishes a characteristic price model by quantitatively analyzing the quality of secondary schools to study the impact of secondary education facilities in Shenzhen on the degree of capitalization of housing prices. The results show that among the factors affecting the second-hand housing prices in the surrounding areas of middle schools,the characteristics of the school have significant influences. Among them, the rate of higher education, teachers and key schools above the school are positively boosting the prices of second-hand houses, while the effect of the student-teacher ratio is negative. At the same time, there are differences in the characteristics of schools between provincial middle schools and non-provincial middle schools affecting the second-hand house prices. Among them,the prices of second-hand houses in non-provincial middle schools are mainly influenced by school characteristics such as the rate of enrollment and student-teacher ratio, while in the vicinity of provincial middle schools, the price is mainly influenced by the number of teachers and the student-teacher ratio. The distance from the subway, CBD and the age of the building have a negative impact on the housing prices around the middle school, and each additional 1 km from the major commercial service centers and subway stations, house prices fell by 13.9% and28.7% respectively. For every one year of building age, house prices fell by 6.8%. This study reveals the impact and extent of the quality characteristics of secondary education on residential prices, and more comprehensively reflects the impact mechanism of housing prices in Shenzhen secondary school districts.
This paper selects the data of 185 residential quarters in three major urban districts of Shenzhen, and establishes a characteristic price model by quantitatively analyzing the quality of secondary schools to study the impact of secondary education facilities in Shenzhen on the degree of capitalization of housing prices. The results show that among the factors affecting the second-hand housing prices in the surrounding areas of middle schools,the characteristics of the school have significant influences. Among them, the rate of higher education, teachers and key schools above the school are positively boosting the prices of second-hand houses, while the effect of the student-teacher ratio is negative. At the same time, there are differences in the characteristics of schools between provincial middle schools and non-provincial middle schools affecting the second-hand house prices. Among them,the prices of second-hand houses in non-provincial middle schools are mainly influenced by school characteristics such as the rate of enrollment and student-teacher ratio, while in the vicinity of provincial middle schools, the price is mainly influenced by the number of teachers and the student-teacher ratio. The distance from the subway, CBD and the age of the building have a negative impact on the housing prices around the middle school, and each additional 1 km from the major commercial service centers and subway stations, house prices fell by 13.9% and28.7% respectively. For every one year of building age, house prices fell by 6.8%. This study reveals the impact and extent of the quality characteristics of secondary education on residential prices, and more comprehensively reflects the impact mechanism of housing prices in Shenzhen secondary school districts.
引文
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[8]哈巍,吴红斌,余韧哲.学区房溢价新探--基于北京市城六区重复截面数据的实证分析.教育与经济,2015(5):3-10
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[13]梁军辉,林坚,吴佳雨.北京市公共服务设施配置对住房价格的影响.城市发展研究,2016,23(9):82-87
[14]John G,Nellis J G.“The price you pay”:the impact of state-funded secondary school performance on residential property values in England.Panoeconomicus,2010,57(4):405-428
[15]陈珧,刘师竹.大学对周边住宅价格影响研究--以浙江大学紫金港校区为例.浙江海洋大学学报(人文科学版),2010,27(3):148-151
[16]董藩,董文婷.学区房价格及其形成机制研究.社会科学战线,2017(1):43-51
[17]陈舜,陈建伟.“学区房”溢价持续扩大的原因与对策研究--来自北京市的经验分析.西部论坛,2015(5):28-36
[18]石忆邵,王伊婷.上海市学区房价格的影响机制.中国土地科学,2014,28(12):47-55
[19]杨雯婷,刘冰玉,王丽.经济学视角下学区房供需因素分析及其对策.财会研究,2012(16):69-71
(1)引自http://www.sz.gov.cn/zsksbgs/zkzz/zkkx/201807/t20180716_13682734.htm。依据深圳中考录取总分排名前10位,分别是深圳中学、深圳实验学校、深圳外国语学校、深圳高级中学、红岭中学、宝安中学、深大附中、育才中学、南山外国语中学和翠园中学。
[2]Oates W E.The effects of property taxes and local public spending on property values:an empirical study of tax capitalization and thetiebout hypothesis.Journal of Political Economy,1969,77(6):957-971
[3]Nguyen-Hoang P,Yinger J.The capitalization of school quality into house values:a review.Journal of Housing Economics,2011,20(1):30-48
[4]Shi Y S,Guo H N.The spatial effect of large park on housing price-use Huangxing park of Shanghai as a case.Geographical Research,2010,29(3):510-520
[5]彭保发,石忆邵,单玥,等.上海市三甲医院对周边地区住房价格的空间影响效应分析.地理科学,2015,35(7):860-866
[6]Bogart W T,Cromwell B A.How much more is a good school district worth?.National Tax Journal,1997,50(2):215-232
[7]毛丰付,罗刚飞,潘加顺.优质教育资源对杭州学区房价格影响研究.城市与环境研究,2014,1(2):53-64
[8]哈巍,吴红斌,余韧哲.学区房溢价新探--基于北京市城六区重复截面数据的实证分析.教育与经济,2015(5):3-10
[9]黄滨茹.中学教学质量对周边住宅价格的影响--以西安市碑林区的中学为例.中国商界(下半月),2010(3):156-158
[10]冯皓,陆铭.通过买房而择校:教育影响房价的经验证据与政策含义.世界经济,2010(12):89-104
[11]Kim H,Park S W,Lee S,et al.Determinants of house prices in Seoul:a quantile regression approach.Pacific Rim Property Research Journal,2015,21(2):91-113
[12]Cheshire P,Sheppard S.Capitalising the value of free schools:the impact of supply characteristics and uncertainty.Economic Journal,2004,114:F397-F424
[13]梁军辉,林坚,吴佳雨.北京市公共服务设施配置对住房价格的影响.城市发展研究,2016,23(9):82-87
[14]John G,Nellis J G.“The price you pay”:the impact of state-funded secondary school performance on residential property values in England.Panoeconomicus,2010,57(4):405-428
[15]陈珧,刘师竹.大学对周边住宅价格影响研究--以浙江大学紫金港校区为例.浙江海洋大学学报(人文科学版),2010,27(3):148-151
[16]董藩,董文婷.学区房价格及其形成机制研究.社会科学战线,2017(1):43-51
[17]陈舜,陈建伟.“学区房”溢价持续扩大的原因与对策研究--来自北京市的经验分析.西部论坛,2015(5):28-36
[18]石忆邵,王伊婷.上海市学区房价格的影响机制.中国土地科学,2014,28(12):47-55
[19]杨雯婷,刘冰玉,王丽.经济学视角下学区房供需因素分析及其对策.财会研究,2012(16):69-71
(1)引自http://www.sz.gov.cn/zsksbgs/zkzz/zkkx/201807/t20180716_13682734.htm。依据深圳中考录取总分排名前10位,分别是深圳中学、深圳实验学校、深圳外国语学校、深圳高级中学、红岭中学、宝安中学、深大附中、育才中学、南山外国语中学和翠园中学。