义务教育资源资本化相关研究进展与述评

doi:10.18306/dlkxjz.2021.10.013

Abstract

Abstract:

High quality public compulsory education resources have a strong capitalization effect on urban housing prices, which leads to the unique urban residential landscape and residential clustering. Such issue has become the focus in the field of public service provision. In the existing review studies, there is a lack of systematic discussion on the capitalization of educational resources. Based on the analysis of the concept and formation mechanism of the educational resources capitalization, we focused on the impact of school education quality and accessibility on housing prices, the measurement of educational resources capitalization, the residential clustering (segregation) caused by unbalanced distribution of educational resources, and coping strategies. First, from the perspective of the measurement of the quality of school education and its impact on housing prices and the measurement of the accessibility from dwelling places to schools and impact on housing prices, we summarized the relevant research on the impact of educational resources on housing prices. We introduced the mainstream methods to quantify the quality of school education and the impact of school education quality on housing prices. Then we commented on the limitations of traditional accessibility measurement methods, the advantages of the new comprehensive measurement methods, and the impact of school accessibility on housing prices. Second, we reviewed the four typical research methods (hedonic price method, fixed boundary method, instrumental variable approach, difference-in-difference method), some typical spatial econometric models, and geographically weighted regression model and their related applications, to examine the relevant literature on the measurement methods for educational resources capitalization. Finally, we summarized the research progress of educational clustering and coping strategies concerning the phenomenon of educational clustering (segregation) caused by school selection or school district policies and the policies on alleviating the problem. The following topics may be the direction of further discussion: tracking and evaluating the effect of enrollment policy, constructing a systematic research framework to alleviate the problem of education clustering, measuring the capitalization of educational resources covering the whole schooling period, designing more effective accessibility measurement methods for schools in each schooling period, assessing the impact of school accessibility on housing prices (especially rental prices) under the background of "school choice" policies, and following the dynamic changes of capitalization of educational resources under the policy of the same right of renters and owners in China.

Key words: capitalization of educational resources, quality of school education, accessibility to schools, residential clustering due to educational resources distribution

SONG Zhengna, HUA Fuli, LIU Shaoli. Research progress and review of capitalization of compulsory educational resources[J].PROGRESS IN GEOGRAPHY, 2021, 40(10): 1771-1787.

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References 103

[1]	Tiebout C M. A pure theory of local expenditures[J]. Journal of Political Economy, 1956, 64(5):416-424. doi: 10.1086/257839
[2]	Oates W E. The effects of property taxes and local public spending on property values: An empirical study of tax capitalisation and Tiebout hypojournal[J]. Journal of Political Economy, 1969, 77(6):957-971. doi: 10.1086/259584
[3]	郑磊, 王思檬. 学校选择、教育服务资本化与居住区分割: 对“就近入学”政策的一种反思[J]. 教育与经济, 2014(6):25-32.
	[ Zheng Lei, Wang Simeng. School choice, capitalization of educational services, and residential segmentation: A reflection on the policy of neighborhood-schooling. Education & Economy, 2014(6):25-32. ]
[4]	唐将伟. 公共服务供给水平对房价的影响研究: 基于国内286个地级及以上城市面板数据的实证[D]. 武汉: 华中师范大学, 2017.
	[ Tang Jiangwei. Research on the impact of public service supply level on housing price: An empirical study based on panel data of 286 cities above prefecture level in China. Wuhan, China: Central China Normal University, 2017. ]
[5]	高雅, 李秀婷, 董纪昌. 城市房价为何不同: 公共服务对房价的影响[J]. 系统工程理论与实践, 2019, 39(9):2255-2262.
	[ Gao Ya, Li Xiuting, Dong Jichang. Why do housing prices differ? The role of public service in housing market. Systems Engineering—Theory & Practice, 2019, 39(9):2255-2262. ]
[6]	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[J]. 世界经济, 2010, 33(12):89-104.
	[ Feng Hao, Lu Ming. Choosing a school by buying a house: Empirical evidence and policy implications of the impact of education on housing prices. The Journal of World Economy, 2010, 33(12):89-104. ]
[7]	王振坡, 梅林, 王丽艳. 基础教育资源资本化及均衡布局对策研究: 以天津为例[J]. 现代财经(天津财经大学学报), 2014, 34(7):92-102.
	[ Wang Zhenpo, Mei Lin, Wang Liyan. Research on the capitalization and countermeasures to equilibrium distribution of basic educational resources: A case study of Tianjin. Modern Finance and Economics (Journal of Tianjin University of Finance and Economics), 2014, 34(7):92-102. ]
[8]	Jayantha W M, Lam S O. Capitalization of secondary school education into property values: A case study in Hong Kong[J]. Habitat International, 2015, 50:12-22. doi: 10.1016/j.habitatint.2015.07.011
[9]	Wen H Z, Xiao Y, Hui E C M, et al. Education quality, accessibility, and housing price: Does spatial heterogeneity exist in education capitalization?[J]. Habitat International, 2018, 78:68-82. doi: 10.1016/j.habitatint.2018.05.012
[10]	Hu S J, Song W, Li C G, et al. School-gentrifying community in the making in China: Its formation mechanisms and socio-spatial consequences[J]. Habitat International, 2019, 93:102045. doi: 10.1016/j.habitatint.2019.102045. doi: 10.1016/j.habitatint.2019.102045
[11]	Xu Y, Song W X, Liu C H. Social-spatial accessibility to urban educational resources under the school district system: A case study of public primary schools in Nanjing, China[J]. Sustainability, 2018, 10(7):2305. doi: 10.3390/su10072305. doi: 10.3390/su10072305
[12]	Feng H, Lu M. School quality and housing prices: Empirical evidence from a natural experiment in Shanghai, China[J]. Journal of Housing Economics, 2013, 22(4):291-307. doi: 10.1016/j.jhe.2013.10.003
[13]	Wen H Z, Zhang Y, Zhang L. Do educational facilities affect housing price? An empirical study in Hangzhou, China[J]. Habitat International, 2014, 42:155-163. doi: 10.1016/j.habitatint.2013.12.004
[14]	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
[15]	李亚宁. 学区质量对房价影响分析中的边界固定法和空间计量法的对比研究: 以深圳数据为例[D]. 深圳: 深圳大学, 2016.
	[ Li Yaning. A comparative study of the boundary fixed method and spatial econometric method in the analysis of the impact of school district quality on housing price: By using the data of Shenzhen as an example. Shenzhen, China: Shenzhen University, 2016. ]
[16]	陆铭, 张爽. “人以群分”: 非市场互动和群分效应的文献评论[J]. 经济学(季刊), 2007, 6(3):991-1020.
	[ Lu Ming, Zhang Shuang. Non-market interaction and sorting: A literature review. China Economic Quarterly, 2007, 6(3):991-1020. ]
[17]	石霏, 何晓燕. 学校教育质量对房产价格的溢出效应: 一个文献综述[J]. 教育与经济, 2018(1):19-26.
	[ Shi Fei, He Xiaoyan. Premium effect of school quality on housing price: A literature review. Education & Economy, 2018(1):19-26. ]
[18]	王伟, 黄恒学. 教育质量在住房价值中的资本化效应研究综述[J]. 现代管理科学, 2019(2):97-99.
	[ Wang Wei, Huang Hengxue. A review on the capitalization effect of education quality in housing value. Modern Management Science, 2019(2):97-99. ]
[19]	单炜. 小学教育质量的房价资本化效应研究: 以南京主城区为例[D]. 南京: 南京财经大学, 2016.
	[ Shan Wei. The research of primary school education qualities on housing price capitalization effect: Take Nanjing main urban area for example. Nanjing, China: Nanjing University of Finance & Economics, 2016. ]
[20]	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 Runqiu, Sun Xiaoya. The effect of education quality capitalization on housing prices based on empirical analysis of elementary school district of Wuhou District in Chengdu. Finance and Economics, 2015(8):91-99. ]
[21]	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 Yongchao, Wang Guangyu, Dong Lijing. 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. Population and Development, 2020, 26(1):108-117. ]
[22]	Barrow L. School choice through relocation: Evidence from the Washington, D.C. area[J]. Journal of Public Economics, 2002, 86(2):155-189. doi: 10.1016/S0047-2727(01)00141-4
[23]	Caetano G. Neighborhood sorting and the value of public school quality[J]. Journal of Urban Economics, 2019, 114:103193. doi: 10.1016/j.jue.2019.103193. doi: 10.1016/j.jue.2019.103193
[24]	Brasington D. Which measures of school quality does the housing market value?[J]. Journal of Real Estate Research, 1999, 18(3):395-413. doi: 10.1080/10835547.1999.12091004
[25]	Brasington D M, Haurin D R. Parents, peers, or school inputs: Which components of school outcomes are capitalized into house value?[J]. Regional Science and Urban Economics, 2009, 39(5):523-529. doi: 10.1016/j.regsciurbeco.2009.05.002
[26]	Hu W Y, Wang R. Segregation in urban education: Evidence from public schools in Shanghai, China[J]. Cities, 2019, 87:106-113. doi: 10.1016/j.cities.2018.12.031
[27]	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
[28]	Brasington D M. The supply of public school quality[J]. Economics of Education Review, 2003, 22(4):367-377. doi: 10.1016/S0272-7757(02)00074-2
[29]	Dills A K. Do parents value changes in test scores? High stakes testing in Texas[J]. Contributions in Economic Analysis & Policy, 2004, 3(1):1-32.
[30]	Seo Y, Simons R. The Effect of school quality on residential sales price[J]. Journal of Real Estate Research, 2009, 31(3):307-328. doi: 10.1080/10835547.2009.12091255
[31]	Hayes K, Taylor L. Neighborhood school characteristics: What signals quality to homebuyers?[J]. Economic and Financial Policy Review, 1996(4):2-9.
[32]	Imberman S A, Lovenheim M F. Does the market value value-added? Evidence from housing prices after a public release of school and teacher value-added[J]. Journal of Urban Economics, 2016, 91:104-121. doi: 10.1016/j.jue.2015.06.001
[33]	宋正娜, 陈雯, 张桂香, 等. 公共服务设施空间可达性及其度量方法[J]. 地理科学进展, 2010, 29(10):1217-1224. doi: 10.11820/dlkxjz.2010.10.009
	[ Song Zhengna, Chen Wen, Zhang Guixiang, et al. Spatial accessibility to public service facilities and its measurement approaches. Progress in Geography, 2010, 29(10):1217-1224. ]
[34]	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
	[ Song Weixuan, Tu Tangqi, Yin Shanggang, et al. The differentiation and effects of social-spatial accessibility in compulsory education resources in Nanjing. Geographical Research, 2019, 38(8):2008-2026. ]
[35]	Lee Y S. School districting and the origins of residential land price inequality[J]. Journal of Housing Economics, 2015, 28:1-17. doi: 10.1016/j.jhe.2014.12.002
[36]	Xiang L L, Stillwell J, Burns L, et al. A geodemographic classification of sub-districts to identify education inequality in Central Beijing[J]. Computers, Environment and Urban Systems, 2018, 70:59-70. doi: 10.1016/j.compenvurbsys.2018.02.002
[37]	Song Z N, Yan T G, Ge Y J. Spatial equilibrium allocation of urban large public general hospitals based on the welfare maximization principle: A case study of Nanjing, China[J]. Sustainability, 2018, 10(9):3024. doi: 10.3390/su10093024. doi: 10.3390/su10093024
[38]	Li H, Wei Y D, Wu Y Y, et al. Analyzing housing prices in Shanghai with open data: Amenity, accessibility and urban structure[J]. Cities, 2019, 91:165-179. doi: 10.1016/j.cities.2018.11.016
[39]	Yuan F, Wu J W, Wei Y D, et al. Policy change, amenity, and spatiotemporal dynamics of housing prices in Nanjing, China[J]. Land Use Policy, 2018, 75:225-236. doi: 10.1016/j.landusepol.2018.03.045
[40]	汤鹏飞, 向京京, 罗静, 等. 基于改进潜能模型的县域小学空间可达性研究: 以湖北省仙桃市为例[J]. 地理科学进展, 2017, 36(6):697-708. doi: 10.18306/dlkxjz.2017.06.005
	[ Tang Pengfei, Xiang Jingjing, Luo Jing, et al. Spatial accessibility analysis of primary schools at the county level based on the improved potential model: A case study of Xiantao City, Hubei Province. Progress in Geography, 2017, 36(6):697-708. ]
[41]	江文政, 乔观民, 邵黎霞, 等. 基于改进潜能模型的城市居民就学可达性研究: 以宁波市海曙区为例[J]. 生产力研究, 2015(5):67-71.
	[ Jiang Wenzheng, Qiao Guanmin, Shao Lixia, et al. Study on the accessibility of urban residents to school based on the improved potential model: A case study of Haishu District, Ningbo City. Productivity Research, 2015(5):67-71. ]
[42]	江海燕, 朱雪梅, 吴玲玲, 等. 城市公共设施公平评价: 物理可达性与时空可达性测度方法的比较[J]. 国际城市规划, 2014, 29(5):70-75.
	[ Jiang Haiyan, Zhu Xuemei, Wu Lingling, et al. Comparison of physical accessibility and space-time accessibility measures in the equity of urban public facilities. Urban Planning International, 2014, 29(5):70-75. ]
[43]	吕毅. 城市小学校可达性评价: 以长沙市雨花区为例[D]. 武汉: 武汉大学, 2005.
	[ Lv Yi. Evaluation of accessibility to primary schools: The case of Yuhua, Changsha, China. Wuhan, China: Wuhan University, 2005. ]
[44]	张玉婷, 孙建国, 杜立钊, 等. 六盘山地区中学教育资源空间可达性分析[J]. 测绘科学, 2019, 44(11):52-58, 87.
	[ Zhang Yuting, Sun Jianguo, Du Lizhao, et al. Analyzing spatial accessibility to secondary education resources in Liupanshan area. Science of Surveying and Mapping, 2019, 44(11):52-58, 87. ]
[45]	Chin H C, Foong K W. Influence of school accessibility on housing values[J]. Journal of Urban Planning and Development, 2006, 132(3):120-129. doi: 10.1061/(ASCE)0733-9488(2006)132:3(120)
[46]	Machin S. Houses and schools: Valuation of school quality through the housing market[J]. Labour Economics, 2011, 18(6):723-729. doi: 10.1016/j.labeco.2011.05.005
[47]	Zhang M Y, Chen J. Unequal school enrollment rights, rent yields gap, and increased inequality: The case of Shanghai[J]. China Economic Review, 2018, 49:229-240. doi: 10.1016/j.chieco.2017.04.007
[48]	Goodman A C, Thibodeau T G. Housing market segmentation[J]. Journal of Housing Economics, 1998, 7(2):121-143. doi: 10.1006/jhec.1998.0229
[49]	Lancaster K J. A new approach to consumer theory[J]. Journal of Political Economy, 1966, 74(2):132-157. doi: 10.1086/259131
[50]	Rosen S. Hedonic prices and implicit markets: Product differentiation in pure competition[J]. Journal of Political Economy, 1974, 82(1):34-55. doi: 10.1086/260169
[51]	Olsen E O. The demand and supply of housing service: A critical survey of the empirical literature[M]// Mills E S. Handbook of regional and urban economics. Amsterdam, Netherlands: Elsevier, 1987: 989-1022.
[52]	贾生华, 温海珍. 房地产特征价格模型的理论发展及其应用[J]. 外国经济与管理, 2004, 26(5):42-44, 49.
	[ Jia Shenghua, Wen Haizhen. The theoretical development and application of Hedonic Price Model of real estate. Foreign Economies and Management, 2004, 26(5):42-44, 49. ]
[53]	王轶军, 郑思齐, 龙奋杰. 城市公共服务的价值估计、受益者分析和融资模式探讨[J]. 城市发展研究, 2007, 14(4):46-53.
	[ Wang Yijun, Zheng Siqi, Long Fenjie. Who benefit from and who pay for the local public services in Chinese cities some policy implications. Urban Studies, 2007, 14(4):46-53. ]
[54]	孙斌艺. 住宅市场的微观结构: 关于教育因素对上海住宅价格影响的计量经济分析[J]. 财贸经济, 2008(9):114-118.
	[ Sun Binyi. The micro structure of housing market: Econometric analysis on the influence of educational factors on housing price in Shanghai. Finance & Trade Economics, 2008(9):114-118. ]
[55]	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[J]. 城市与环境研究, 2014, 1(2):53-64.
	[ Mao Fengfu, Luo Gangfei, Pan Jiashun. The effect of elementary education on the price of Hangzhou school district housing. Urban and Environmental Studies, 2014, 1(2):53-64. ]
[56]	Black S E, Machin S. Housing valuations of school performance[M]// Hanushek E, Machin S, Woessmann L. Handbook of the economics of education. Amsterdam, Netherlands: Elsevier, 2011: 485-519.
[57]	Black S E. Do better schools matter? Parental valuation of elementary education[J]. The Quarterly Journal of Economics, 1999, 114(2):577-599. doi: 10.1162/003355399556070
[58]	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 Wanyang, Zheng Siqi, Wang Rui. The capitalization of school quality in home value: A matching regression approach with housing price-rent comparison. China Economic Quarterly, 2014, 13(3):1195-1214. ]
[59]	Mathur S. The myth of "free" public education: Impact of school quality on house prices in the Fremont unified school district, California[J]. Journal of Planning Education and Research, 2017, 37(2):176-194. doi: 10.1177/0739456X16654546
[60]	Clapp J M, Nanda A, Ross S L. Which school attributes matter? The influence of school district performance and demographic composition on property values[J]. Journal of Urban Economics, 2008, 63(2):451-466. doi: 10.1016/j.jue.2007.03.004
[61]	Brasington D M, Hite D, Jauregui A. House price impacts of racial, income, education, and age neighborhood segregation[J]. Journal of Regional Science, 2015, 55(3):442-467. doi: 10.1111/jors.12173
[62]	Weimer D L, Wolkoff M J. School performance and housing values: Using non-contiguous district and incorporation boundaries to identify school effects[J]. National Tax Journal, 2001, 54(2):231-253. doi: 10.17310/ntj.2001.2.03
[63]	Fack G, Grenet J. When do better schools raise housing prices? Evidence from Paris public and private schools[J]. Journal of Public Economics, 2010, 94(1/2):59-77. doi: 10.1016/j.jpubeco.2009.10.009
[64]	Dhar P, Ross S L. School district quality and property values: Examining differences along school district boundaries[J]. Journal of Urban Economics, 2012, 71(1):18-25. doi: 10.1016/j.jue.2011.08.003
[65]	Gibbons S, Machin S, Silva O. Valuing school quality using boundary discontinuities[J]. Journal of Urban Economics, 2013, 75:15-28. doi: 10.1016/j.jue.2012.11.001
[66]	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, 191.
	[ Ha Wei, Yu Renzhe. How much is an improved school worth? Evidence from the comprehensive reform in compulsory education in Beijing. Peking University Education Review, 2017, 15(3):137-153, 191. ]
[67]	Downes T A, Zabel J E. The impact of school characteristics on house prices: Chicago 1987-1991[J]. Journal of Urban Economics, 2002, 52(1):1-25. doi: 10.1016/S0094-1190(02)00010-4
[68]	Rosenthal L. The value of secondary school quality[J]. Oxford Bulletin of Economics and Statistics, 2003, 65(3):329-355. doi: 10.1111/obes.2003.65.issue-3
[69]	Angrist J D, Steffen P J. Mastering metrics: The path from cause to effect[M]. New York, USA: Princeton University Press, 2014: 98-142.
[70]	Reback R. House prices and the provision of local public services: Capitalization under school choice programs[J]. Journal of Urban Economics, 2005, 57(2):275-301. doi: 10.1016/j.jue.2004.10.005
[71]	Ries J, Somerville T. School quality and residential property values: Evidence from vancouver rezoning[J]. Review of Economics and Statistics, 2010, 92(4):928-944. doi: 10.1162/REST_a_00038
[72]	Orford S. The capitalisation of school choice into property prices: A case study of grammar and all ability state schools in Buckinghamshire, UK[J]. Geoforum, 2018, 97:231-241. doi: 10.1016/j.geoforum.2018.09.009
[73]	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 Shanggang, Hu Xin, Ma Zhifei, et al. Spatial and temporal effects of housing price in urban school districts based on education equity: A case study of public pimary school in the main urban area of Nanjing. Economic Geography, 2019, 39(9):82-93. ]
[74]	Anselin L. Spatial econometrics: Methods and models[M]. Springer, 1988: 16-26.
[75]	Anselin L, Lozano-Gracia N. Spatial hedonic models[M]// Mills T C, Patterson K. Palgrave handbook of econometrics. London, UK: Palgrave Macmillan, 2009: 1213-1250.
[76]	Zhang Y, Cromley R G, Hanink D M. A spatial hedonic model application of variance function regression to residential property prices in Beijing[J]. Letters in Spatial and Resource Sciences, 2016, 9(1):93-101. doi: 10.1007/s12076-015-0142-6
[77]	温海珍, 张之礼, 张凌. 基于空间计量模型的住宅价格空间效应实证分析: 以杭州市为例[J]. 系统工程理论与实践, 2011, 31(9):1661-1667.
	[ Wen Haizhen, Zhang Zhili, Zhang Ling. An empirical analysis on spatial effects of the housing price based on spatial econometric models: Evidence from Hangzhou City. Systems Engineering—Theory & Practice, 2011, 31(9):1661-1667. ]
[78]	Watkins C A. The definition and identification of housing submarkets[J]. Environment and Planning A: Economy and Space, 2001, 33(12):2235-2253. doi: 10.1068/a34162
[79]	Brunsdon C, Fotheringham A S, Charlton M E. Geographically weighted regression: A method for exploring spatial nonstationarity[J]. Geographical Analysis, 1996, 28(4):281-298. doi: 10.1111/gean.1996.28.issue-4
[80]	Shatkin G. Global cities of the South: Emerging perspectives on growth and inequality[J]. Cities, 2007, 24(1):1-15. doi: 10.1016/j.cities.2006.10.002
[81]	Millimet D L, Rangaprasad V. Strategic competition amongst public schools[J]. Regional Science and Urban Economics, 2007, 37(2):199-219. doi: 10.1016/j.regsciurbeco.2006.08.006
[82]	Chumacero R A, Gómez D, Paredes R D. I would walk 500 miles (if it paid): Vouchers and school choice in Chile[J]. Economics of Education Review, 2011, 30(5):1103-1114. doi: 10.1016/j.econedurev.2011.05.015
[83]	Alves F, Elacqua G, Koslinki M, et al. Winners and losers of school choice: Evidence from Rio de Janeiro, Brazil and Santiago, Chile[J]. International Journal of Educational Development, 2015, 41:25-34. doi: 10.1016/j.ijedudev.2014.12.004
[84]	Posey-Maddox L, Kimelberg S M, Cucchiara M. Middle-class parents and urban public schools: Current research and future directions[J]. Sociology Compass, 2014, 8(4):446-456. doi: 10.1111/soc4.v8.4
[85]	陈培阳. 中国城市学区绅士化及其社会空间效应[J]. 城市发展研究, 2015, 22(8):55-60.
	[ Chen Peiyang. Jiaoyufication and its socio-spatial consequences in urban China. Urban Development Studies, 2015, 22(8):55-60. ]
[86]	Wu Q Y, Zhang X L, Waley P. Jiaoyufication: When gentrification goes to school in the Chinese inner city[J]. Urban Studies, 2016, 53(16):3510-3526. doi: 10.1177/0042098015613234
[87]	Bischoff K. School district fragmentation and racial residential segregation: How do boundaries matter?[J]. Urban Affairs Review, 2008, 44(2):182-217. doi: 10.1177/1078087408320651
[88]	Pearman F A II, Swain W A. School choice, gentrification, and the variable significance of racial stratification in urban neighborhoods[J]. Sociology of Education, 2017, 90(3):213-235. doi: 10.1177/0038040717710494
[89]	Sipple J W, Francis J D, Fiduccia P C. Exploring the gradient: The economic benefits of 'nearby' schools on rural communities[J]. Journal of Rural Studies, 2019, 68:251-263. doi: 10.1016/j.jrurstud.2019.02.018
[90]	Yang Z S, Hao P, Wu D. Children's education or parents' employment: How do people choose their place of residence in Beijing[J]. Cities, 2019, 93:197-205. doi: 10.1016/j.cities.2019.05.008
[91]	Mok K H, Wat K Y. Merging of the public and private boundary: Education and the market place in China[J]. International Journal of Educational Development, 1998, 18(3):255-267. doi: 10.1016/S0738-0593(98)00012-1
[92]	Glewwe P, Patrinos H A. The role of the private sector in education in Vietnam: Evidence from the Vietnam living standards survey[J]. World Development, 1999, 27(5):887-902. doi: 10.1016/S0305-750X(99)00027-3
[93]	孔云峰, 朱艳芳, 王玉璟. 学校分区问题混合元启发算法研究[J]. 地理学报, 2017, 72(2):256-268. doi: 10.11821/dlxb201702006
	[ Kong Yunfeng, Zhu Yanfang, Wang Yujing. A hybrid metaheuristic algorithm for the school districting problem. Acta Geographica Sinica, 2017, 72(2):256-268. ]
[94]	Kuroda Y. The effect of school quality on housing rents: Evidence from Matsue City in Japan[J]. Journal of the Japanese and International Economies, 2018, 50:16-25. doi: 10.1016/j.jjie.2018.05.002
[95]	Zheng S Q, Hu W Y, Wang R. How much is a good school worth in Beijing? Identifying price premium with paired resale and rental data[J]. The Journal of Real Estate Finance and Economics, 2016, 53(2):184-199. doi: 10.1007/s11146-015-9513-4
[96]	许晨曦. 租售同权政策对于房地产市场的影响: 以杭州市西湖区学区房为例[D]. 杭州: 浙江大学, 2018.
	[ Xu Chenxi. The anti-discrimination policy for the rental housing market: A case study in Hangzhou on the key school districts. Hangzhou, China: Zhejiang University, 2018. ]
[97]	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, 94:104513. doi: 10.1016/j.landusepol.2020.104513. doi: 10.1016/j.landusepol.2020.104513
[98]	张协奎, 刘绍涛. 租购同权、房价租金变动与住房市场发展: 基于广州“租购同权”政策效应的研究[J]. 广西大学学报(哲学社会科学版), 2020, 42(3):56-67.
	[ Zhang Xiekui, Liu Shaotao. Equal rights between buyer and tenant, the change of housing price and rent and the development of housing market: Research on the effect of guangzhou's "equal rights between buyer and tenant" policy. Journal of Guangxi University (Philosophy and Social Sciences), 2020, 42(3):56-67. ]
[99]	Makarewicz C. Balancing education opportunities with sustainable travel and development[M]// Deakin E. Transportation, land use, and environmental planning. Amsterdam, Netherlands: Elsevier, 2020: 299-331.
[100]	Downes T A. Does fiscal dependency matter? Aid elasticities for dependent and independent school districts[J]. Economics of Education Review, 2000, 19(4):417-429. doi: 10.1016/S0272-7757(00)00007-8
[101]	Brasington D M. House prices and the structure of local government: An application of spatial statistics[J]. The Journal of Real Estate Finance and Economics, 2004, 29(2):211-231. doi: 10.1023/B:REAL.0000035311.59920.74
[102]	Bradley S, Johnes G, Millington J. The effect of competition on the efficiency of secondary schools in England[J]. European Journal of Operational Research, 2001, 135(3):545-568. doi: 10.1016/S0377-2217(00)00328-3
[103]	温海珍, 杨尚, 秦中伏. 城市教育配套对住宅价格的影响: 基于公共品资本化视角的实证分析[J]. 中国土地科学, 2013, 27(1):34-40.
	[ Wen Haizhen, Yang Shang, Qin Zhongfu. The impact of educational facilities on housing price: An empirical analysis from the perspective of the capitalization for public goods. China Land Sciences, 2013, 27(1):34-40. ]

方法类别	基本特点	部分相关研究文献
特征价格法	通过构建反映商品各特征因素(建筑结构、区位、教育等)与价格之间关系的特征价格方程,采用现实数据并运用一定的计量方法对该函数关系进行回归分析,以揭示各特征因素对房价的影响传统特征价格法的主要局限见表2	孙斌艺^[54]、毛丰付等^[55]、Black等^[56]、Clapp等^[60]、Brasington等^[61]
边界固定法	在2个相邻学区交界处,选取距交界处较近的住房样本,所选样本分别位于不同学区,控制这些样本所包含的特征中,除了教育特征外,其他特征基本相同可以解决遗漏变量问题,一定程度上控制潜在的内生性偏差、剥离邻里效应,但数据获得性难度较大,应用不广泛	冯皓等^[6]、Black^[57]、胡婉旸等^[58]、Clapp 等^[60]、Weimer等^[62]、Fack等^[63]、Dhar等^[64]、Gibbons等^[65]、哈巍等^[66]
工具变量法	使用工具变量将主要解释变量变异中那部分与残值不相关的(外生)变异提取出来,将其用于回归即可得到无偏的估计可剥离邻里效应,但选择一个合适工具变量较为困难,其解释能力仍存争议	Weimer等^[62]、Downes等^[67]、Rosenthal^[68]、 Angrist等^[69]
双重差分法	对设有对照的干预项目、没有进行随机化分组干预项目或者随机化失败的干预项目的效果进行评估可一定程度上控制潜在的内生性偏差,一定程度上消除邻里效应,但消除效果较空间经济计量模型要弱	Wen等^[14]、Imberma等^[32]、Fack等^[63]、Reback^[70]、Ries等^[71]

弊端	解决方法及部分相关文献
潜在的内生性偏差	自然实验^[12];边界固定法和双重差分法^[56];重复销售方法^[72]
遗漏变量,如忽略(遗漏)部分邻里变量(邻里效应)	边界固定法^[35,57-59];工具变量、双重差分法和空间经济计量模型等^[13-15,27]
忽略房价的空间依赖性、可能得到有偏的结果	空间经济计量模型^[9,15,38-39],如空间滞后模型(SLM)和空间误差模型(SEM)
无法处理住房市场数据的非平稳性	地理加权回归模型^[39]
只能得到教育特征在房价中的平均隐含值,无法揭示教育特征的资本化效应在空间上的异质性	地理加权回归模型^[9,73]

Research progress and review of capitalization of compulsory educational resources

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