中国城市房价影响因素及贡献度研究——基于R^2的相对重要性分解  

Research on Influencing Factors and Contribution Degree of Urban Hous Prices in China——Based on R^2 Relative Importance Decomposition

作　　者：杨慧 李超[2] Yang Hui;Li Chao

机构地区：[1]北京信息科技大学,北京100192 [2]中国社会科学院,北京100028

出　　处：《经济问题探索》2019年第11期49-62,共14页Inquiry Into Economic Issues

基　　金：国家社会科学基金青年项目“新型城镇化与房地产市场协调发展及政策研究”(14CJY027)，项目负责人:杨慧;北京社科基金青年项目“京津冀基础设施一体化与金融支持协调发展及政策研究”(16YJ053)，项目负责人:杨慧

摘　　要：房价影响因素判断是政府调控房地产市场的重要理论依据。本文考察了35个大中城市供给、需求、土地和宏观环境因素对房价的影响,并探讨了四类因素下属的7个二级指标对房价影响的相对重要性。结果显示7个指标对房价回归的R^2达到了0.9673,其中地价和收入对R^2的贡献度分别达到46.02%和31.09%,影响作用最大;股价和利率对R^2的贡献度分别为11.05%和9.34%,影响作用也较强。考虑到房地产市场的区域性特征,本文将35个大中城市划分为东部城市和中西部城市进行分组样本的稳健性检验,我们的结论依然稳健。The judgment of influencing factors of house prices is an important theoretical basis for the government to regulate and control the real estate market. This paper examines the impact of supply,demand,land and macro-environmental factors on housing prices in 35 large and medium-sized cities,and explores the relative importance of the impact of seven secondary indicators under four category factors on housing prices. The results show that the contribution degree of land price and income to R^2 is 46. 02% and 31. 09% respectively,respectively. The contribution degree of stock price and interest rate to R^2 is 11. 05% and 9. 34%,respectively. Considering the regional characteristics of the real estate market,we divided 35 cities into eastern cities and central-western cities to test the robustness of the group samples,and the results are still robust.

关 键 词：城市房价 影响因素 贡献度 R^2分解 相对重要性 

分 类 号：F293[经济管理—国民经济]