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

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

在教育资本化的背景下,学区房成为房地产紧缩调控中的特例,政策管控效果不明显。选取沈阳市中心城区53所重点中小学所对应的321处学区房,以82处非学区房作为对照组,利用价格特征模型得出学区房教育因素起根本作用,其它房价影响因素在学区房上被弱化的基本结论。研究表明,控制其它因素,单纯教育因素所导致的学区房溢价明显,单学区溢价18%,双学区溢价44%,且教育质量与学区房溢价成正比。通过空间自相关分析单学区、双学区、全部学区、非学区价格的空间"冷点-热点",得出学区房与非学区房价格空间集聚上具有差异性和关联性,学区房与非学区房的空间偏好呈交叉影响的结论。提出学区政策与旧区改造结合,学区房投资向教育投资转变,实施动态学区划分的学区政策改善建议。

Corresponding to 53 key primary and secondary schools,321 school district housing( communities) in the downtown area of Shenyang were selected with 82 non-school districts taken as the control group. The hedonic price model was used to conclude that educational factors played an instrumental role in affecting the prices of school-nearby houses,while other influential factors were less important. Controlling other factors,the premium of school-nearby housing caused by simple educational factors was significant;the premium of single school district was 18%,and that of double school district is 44%. Moreover,the higher the education quality was,the higher the premium was. Furthermore,through spatial autocorrelation analysis of the spatial agglomeration characteristics of housing prices in school districts,the spatial "cold spot-hot spot"of single school district,double school district,all school district and non-school district was conducted separately. It has been concluded that prices of school-nearby houses and non-school-nearby houses,in terms of spatial agglomeration,had difference and relevance. Finally,a comprehensive and in-depth study of school-nearby housing is carried out from the price level and price spatial characteristics. Based on the empirical research,it is proposed that the implementation of district policy should be combined with the transformation of old districts. Investment in school district housing should be transformed into education,and the policy of dynamically dividing school districts are suggested.