教育资源差异对住房价格的影响——以武汉市江岸区为例

doi:10.18402/resci.2021.04.13

摘要/Abstract

摘要：

探讨教育资源差异对住房价格的影响对促进优质教育资源均衡发展、维持房地产市场稳定具有重要意义。本文以武汉市江岸区为研究区,基于研究区2016年6月—2018年5月的住房交易数据,从住房建筑特征、区位特征、邻里特征、学区特征等方面构建Hedonic模型,探索教育资源差异对住房价格的影响;同时引入政策公告期（T₁）、政策实施期（T₂）两个时间虚拟变量以及对口中小学质量和时间的交互项,研究学区制政策实行前后对学区房价格的影响。研究发现：①学校质量对学区房价格有着显著正向作用,且对口初中质量比小学的影响更加明显。具体而言,小学质量升高一级,住房价格将平均升高11.7%;初中质量升高一级,住房价格将平均升高27.6%。②在T₁期,学区制政策因素对小学学区和初中学区房价的影响系数S₁T₁和S₂T₁分别为0.049、0.074;在T₂期,学区制政策因素对小学学区和初中学区房价的影响系数S₁T₂和S₂T₂分别为0.060、0.089。分析发现,由于受到相关住房和入学政策落实实效与居民消费预期等影响,研究期内学区制改革政策的实施对江岸区优质教育的资本化效应为正效应,对促进优质教育资源均衡化发展的效果尚未突显。

关键词: 学区, 教育公平, 房价, 资本化, 影响因素, Hedonic模型, 武汉市

Abstract:

It is of great significance to explore the capitalization effect of educational resource difference on housing price to balance the development of high-quality educational resources and maintain the stability of real estate market. Taking Jiang’an District of Wuhan City as an example and based on the housing transaction data of the research area from June 2016 to May 2018, this study constructed a Hedonic price model from the areas, history, location, neighborhood, school-accessibility, and other aspects of housing to explore the capitalization effect of high-quality educational resources on housing price. Two dummy variables of policy announcement period (T₁) and policy implementation period (T₂) and the interaction between quality of primary and secondary schools and time were introduced to study the influence of school district system policy on school district housing price before and after its implementation. The research found that: (1) School quality has a positive effect on school district housing price, and the effect of the quality of middle school is more obvious than that of primary school. Specifically, one-level increase in primary school quality leads to an average 11.7% increase in housing prices; An increase in the quality of secondary schools by one level would increase housing prices by an average of 27.6%. (2) In phase T₁, the influence coefficient S₁T₁ and S₂T₁ on the housing prices of primary school district and middle school district were 0.049 and 0.074 respectively. In the T₂ period, the influence coefficient S₁T₂ and S₂T₂ on the housing prices of primary school district and middle school district were 0.060 and 0.089 respectively. The implementation of the school district system policy in the research period has a positive effect on the capitalization of the school district housing, and the impact on balancing the development of high-quality educational resources has not yet been shown due to the impact of the implementation of relevant housing and enrollment policies and residents’ habitual thinking.

Key words: school district, educational equality, housing price, capitalization, impact factors, Hedonic model, Wuhan City

杨剩富, 张鹏, 邹秋丽. 教育资源差异对住房价格的影响——以武汉市江岸区为例[J]. 资源科学, 2021, 43(4): 790-798.

YANG Shengfu, ZHANG Peng, ZOU Qiuli. Effect of educational resource difference on housing price in Jiang’an District, Wuhan City[J]. Resources Science, 2021, 43(4): 790-798.

图/表 6

图1

表1

表2

表3

图2

表4

参考文献 30

[1]	刘延东. 深入学习贯彻党的十九大精神全面开创教育改革发展新局面[J]. 求是, 2018, ( 6):14-20.
	[ Liu Y D. Studying and implementing the spirit of the 19th CPC National Congress to open up new prospects for educational reform and development[J]. Qiu Shi, 2018, ( 6):14-20.]
[2]	孙伟增, 林嘉瑜. 教育资源供给能够降低学区房溢价吗? 来自北京市新建小学的证据[J]. 经济学(季刊), 2020,19(2):499-520.
	[ Sun W Z, Lin J Y. Does school supply reduce school district housing price premium? Evidence from newly-built primary schools in Beijing[J]. China Economic Quarterly, 2020,19(2):499-520.]
[3]	哈巍, 余韧哲. 学校改革价值几何? 基于北京市义务教育综合改革的“学区房”溢价估计[J]. 北京大学教育评论, 2017,15(3):137-153.
	[ Ha W, Yu R Z. How much is an improved school worth? Evidence from the comprehensive reform in compulsory education in Beijing[J]. Peking University Education Review, 2017,15(3):137-153.]
[4]	尹上岗, 胡信, 马志飞, 等. 基于教育公平视角的城市学区房价格时空效应: 以南京主城区公办小学为例[J]. 经济地理, 2019,39(9):82-93.
	[ Yin S G, Hu X, Ma Z F, et al. Spatial and temporal effects of housing price in urban school districts based on education equity: A case study of public primary school in the main urban area of Nanjing[J]. Economic Geography, 2019,39(9):82-93.]
[5]	涂唐奇, 闫东升, 陈江龙, 等. 南京城市义务教育设施空间演化[J]. 地理科学, 2019,39(3):433-441. doi: 10.13249/j.cnki.sgs.2019.03.009 pmid: 085F5A10-7D11-4DE9-9BC9-A998F124E028
	[ Tu T Q, Yan D S, Chen J L, et al. Evolution of compulsory educational facilities in urban Nanjing[J]. Scientia Geographica Sinica, 2019,39(3):433-441.] pmid: 085F5A10-7D11-4DE9-9BC9-A998F124E028
[6]	戴特奇, 廖聪, 胡科, 等. 公平导向的学校分配空间优化: 以北京石景山区为例[J]. 地理学报, 2017,72(8):1476-1485. doi: 10.11821/dlxb201708011 pmid: 70031190-DA4D-4037-9593-2541DECA703B
	[ Dai T Q, Liao C, Hu K, et al. Secondary school allocation optimization towards equal access: A case study on Shijingshan District, Beijing[J]. Acta Grographica Sinica, 2017,72(8):1476-1485.] pmid: 70031190-DA4D-4037-9593-2541DECA703B
[7]	Hu L R, He S J, Luo Y, et al. A social-media-based approach to assessing the effectiveness of equitable housing policy in mitigating education accessibility induced social inequalities in Shanghai, China[J]. Land Use Policy, 2020, DOI: 10.1016/j.landusepol.2020.104513. doi: 10.1016/j.landusepol.2020.104513
[8]	戴特奇, 赵韶雅, 廖聪. 概率分布相似最大化的“就近-随机”入学机会公平优化: 以北京市西城区为例[J]. 经济地理, 2019,39(11):18-24.
	[ Dai T Q, Zhao S Y, Liao C. Maximum spatial equality of educational opportunity based on the proximity-random system: A case study of Xicheng District, Beijing[J]. Economic Geography, 2019,39(11):18-24.]
[9]	Oates W E. The effects of property taxes and local public spending on property values: An empirical study of tax capitalization and the Tiebout hypojournal[J]. Journal of Political Economy, 1969,77(6):957-971. doi: 10.1086/259584
[10]	戴其文, 姚意旗, 张晓奇, 等. 环境对城市房价影响研究述评与展望[J]. 资源科学, 2019,41(4):627-642.
	[ Dai Q W, Yao Y Q, Zhang X Q, et al. Review and prospect of research on the influence of the environment on spatial disparity of urban housing prices[J]. Resources Science, 2019,41(4):627-642.]
[11]	梁立雨, 郭志强, 李军祥, 等. 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[J]. 北京大学学报(自然科学版), 2019,55(3):537-542.
	[ Liang L Y, Guo Z Q, Li J X, et al. Analysis of the premium of second-hand housing prices in surrounding communities in middle school districts: Taking Shenzhen as an example[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2019,55(3):537-542.]
[12]	Bogart W T, Cromwell B A. How much more is a good school district worth?[J]. National Tax Journal, 1997,50(2):215-232. doi: 10.1086/NTJ41789254
[13]	温海珍, 贾生华. 住宅的特征与特征的价格: 基于特征价格模型的分析[J]. 浙江大学学报(工学版), 2004,38(10):1338-1342.
	[ Wen H Z, Jia S H. Housing characteristics and hedonic price: Analysis based on hedonic price model[J]. Journal of Zhejiang University (Engineering Science), 2004,38(10):1338-1342.]
[14]	Nguyen-Hoang P, Yinger J. The capitalization of school quality into house values: A review[J]. Journal of Housing Economics, 2011,20(1):30-48. doi: 10.1016/j.jhe.2011.02.001
[15]	Yang S F, Hu S G, Wang S L, et al. Effects of rapid urban land expansion on the spatial direction of residential land price[J]. Habitat International, 2020, DOI: 10.1016/j.habitatint.2020.102186 doi: 10.1016/j.habitatint.2020.102186
[16]	杨剩富, 胡守庚, 徐枫, 等. 特殊自然地物对城市住宅地价和房价的影响: 以武汉市为例[J]. 资源科学, 2016,38(4):738-749.
	[ Yang S F, Hu S G, Xu F, et al. Influence on urban residential land and housing prices by special natural features in Wuhan[J]. Resources Science, 2016,38(4):738-749.]
[17]	He S. A hierarchical estimation of school quality capitalization in house prices in Orange County, California[J]. Urban Studies, 2017, DOI: 10.1177/0042098016669473. doi: 10.1177/0042098016669473
[18]	刘润秋, 孙潇雅. 教育质量“资本化”对住房价格的影响: 基于成都市武侯区小学学区房的实证分析[J]. 财经科学, 2015, ( 8):91-99.
	[ Liu R Q, Sun X Y. The effect of education quality capitalization on housing prices based on empirical analysis of elementary school district of Wuhou District in Chengdu[J]. Finance & Economics, 2015, ( 8):91-99.]
[19]	石忆邵, 王伊婷. 上海市学区房价格的影响机制[J]. 中国土地科学, 2014,28(12):47-55.
	[ Shi Y S, Wang Y T. The impacting mechanism of housing prices in the school districts in Shanghai City[J]. China Land Sciences, 2014,28(12):47-55.]
[20]	胡婉旸, 郑思齐, 王锐. 学区房的溢价究竟有多大: 利用“租买不同权”和配对回归的实证估计[J]. 经济学(季刊), 2014,13(3):1195-1214.
	[ Hu W Y, Zheng S Q, Wang R. The capitalization of school quality in home value: A matching regression approach with housing price rent comparison[J]. China Economic Quarterly, 2014,13(3):1195-1214.]
[21]	张骥. 学区房溢价的再估计: 以北京市为例[J]. 经济问题探索, 2017, ( 8):57-63.
	[ Zhang J. Re-estimation of the premium of school district housing: A case study of Beijing[J]. Inquiry into Economic Issues, 2017, ( 8):57-63.]
[22]	Jayantha W M, Lam S O. Capitalization of secondary school education into property values: A case study in Hong Kong, China[J]. Habitat International, 2015,50:12-22. doi: 10.1016/j.habitatint.2015.07.011
[23]	王永超, 王光宇, 董丽晶. 教育资本化背景下学区房溢价水平和价格空间集聚特征研究: 以沈阳市中心城区为例[J]. 人口与发展, 2020,26(1):108-117.
	[ Wang Y C, Wang G Y, Dong L J, et al. Research on premium level and price spatial agglomeration characteristics of school district housing under the background of education capitalization: Taking the downtown area of Shenyang as an example[J]. Population & Development, 2020,26(1):108-117.]
[24]	Wen H Z, Xiao Y, Zhang L. School district, education quality, and housing price: Evidence from a natural experiment in Hangzhou, China[J]. Cities, 2017,66:72-80.] doi: 10.1016/j.cities.2017.03.008
[26]	Wen H Z, Xiao Y, Hui E C M. Quantile effect of educational facilities on housing price: Do homebuyers of higher-priced housing pay more for educational resources?[J]. Cities, 2019,90:100-112. doi: 10.1016/j.cities.2019.01.019
[27]	王望珍, 杨笑然. 租售同权对武汉学区房价格的影响[J]. 武汉理工大学学报(信息与管理工程版), 2019,41(4):422-426.
	[ Wang W Z, Yang X R. Influence of coequality for owners and tenants on the housing price in the school district of Wuhan City[J]. Journal of Wuhan University of Technology (Information & Management Engineering), 2019,41(4):422-426.]
[28]	宋伟轩, 涂唐奇, 尹上岗, 等. 南京义务教育资源的社会-空间可达性差异及效应研究[J]. 地理研究, 2019,38(8):2008-2026. doi: 10.11821/dlyj020180575 pmid: 1283022f-186d-400c-98a9-7d80ff034892
	[ Song W X, Tu T Q, Yin S G, et al. The differentiation and effects of social-spatial accessibility in compulsory education resources in Nanjing[J]. Geographical Research, 2019,38(8):2008-2026.] pmid: 1283022f-186d-400c-98a9-7d80ff034892
[29]	李瑶瑶, 朱道林, 赵江萌, 等. 政府短期干预行为对住宅地价周期波动的影响[J]. 资源科学, 2019,41(6):1059-1069.
	[ Li Y Y, Zhu D L, Zhao J M, et al. Impact of short-term government intervention on the periodic fluctuation of residential land price[J]. Resources Science, 2019,41(6):1059-1069.]
[30]	许浩, 周子康, 孔德莉, 等. 武汉市基础教育资源与居民点空间耦合分析[J]. 经济地理, 2019,39(8):87-94.
	[ Xu H, Zhou Z K, Kong D L, et al. Spatial pattern of basic education resources in Wuhan based on spatial coupling algorithm[J]. Economic Geography, 2019,39(8):87-94.]

特征类别	变量	定义变量及量化	预期符号	极小值	极大值	均值	标准差
因变量	房价（P）	指二手房交易价格/（元/ m²）		7000.00	62643.37	18770.64	6267.88
建筑特征	建筑面积（Ar）	指住房的建筑面积/m²	+	11.50	264.49	92.57	36.61
建筑特征	房龄（Ag）	指住房的房龄/年	-	0.00	32.00	10.43	6.09
邻里特征	物业费（F）	指小区的物业费/（元/月·m²）	+	0.20	4.80	1.48	0.77
	容积率（R₁）	指小区总建筑面积与用地面积的比值	-	0.12	13.60	3.31	1.90
	绿化率（R₂）	指小区的绿化率水平/%	+	8.10	55.00	34.50	7.30
	公园绿地（G）	小区1 km内有公园绿地记1,无记0	+	0.00	1.00	0.83	0.38
	商店超市（M）	小区1 km内有商店超市记1,无记0	+	1.00	1.00	1.00	0.00
区位特征	到江汉路商圈的距离（D₁）	指从小区中心到江岸区CBD的直线距离/km	-	0.20	11.10	5.51	2.75
	到最近地铁站的距离（D₂）	指从小区中心到最近地铁站的直线距离/km	-	0.07	1.31	0.58	0.25
	到对口小学的距离（D₃）	指从小区中心到对口小学的直线距离/km	-	0.04	2.24	0.62	0.46
	到对口初中的距离（D₄）	指从小区中心到对口中学的直线距离/km	-	0.06	6.76	1.24	1.45
学区特征	小学质量（S₁）	省级示范小学记3,市级示范小学记2,普通小学记1	+	1.00	3.00	1.22	0.51
学区特征	初中质量（S₂）	重点初中记2,普通初中记1	+	1.00	2.00	1.08	0.27

变量	标准系数	标准误差	t	共线性统计
变量	标准系数	标准误差	t	容差	VIF
lnAg	-0.066**	0.029	-2.293	0.373	2.679
lnF	0.358***	0.028	12.765	0.388	2.578
lnR₂	0.114***	0.020	5.735	0.767	1.304
G	0.108***	0.019	5.629	0.834	1.199
lnD₁	-0.145***	0.024	-6.128	0.542	1.844
lnD₂	-0.091***	0.018	-4.96	0.909	1.100
lnD₄	-0.104***	0.022	-4.815	0.659	1.518
S₁	0.111***	0.022	5.032	0.625	1.599
S₂	0.244***	0.021	11.533	0.682	1.466
R²	0.378
调整R²	0.375

模型	模型2	模型3	模型4
（常量）	9.586***	9.755***	9.591***
lnAg	-0.082***	-0.039**	-0.053***
lnF	0.154***	0.118***	0.139***
lnR₂	0.092***	0.088***	0.098***
G	0.085***	0.057**	0.071***
lnD₁	-0.091**	-0.088***	-0.081***
lnD₂	-0.055**	-0.061***	-0.056***
S₁	0.031***	0.051**	0.024***
S₂	0.211***	0.206***	0.189***
lnD₄	-0.042***	-0.024***	-0.035***
T₁	0.096**	-	0.072***
T₂	-	0.019***	0.107***
S₁T₁	0.050***	-	0.049**
S₁T₂	-	0.016***	0.060***
S₂T₁	-0.080***	-	0.074***
S₂T₂	-	0.026***	0.089***

	T₀	T₁	T₂
S₁	0.024	0.073（0.024+0.049）	0.084（0.024+0.060）
S₂	0.189	0.263（0.189+0.074）	0.278（0.189+0.089）