主管单位：中国科学技术协会
主办单位：中国地理学会
承办单位：华东师范大学
主办单位：中国地理学会
承办单位：华东师范大学
World Regional Studies ›› 2023, Vol. 32 ›› Issue (1): 117-129.DOI: 10.3969/j.issn.1004-9479.2023.01.2020680
Previous Articles Next Articles
Ruhong WEI1(
), Li JIN1, Da FANG1,2()
Received:2020-09-26
Revised:2020-12-24
Online:2023-01-01
Published:2023-01-01
Contact:
Da FANG
韦汝虹1(), 金李1, 方达1,2()
通讯作者:
方达
作者简介:韦汝虹（1984—），女，博士，中级经济师，主要研究方向为金融学、区域经济学，E-mail： 1395927096@qq.com。
基金资助:Ruhong WEI, Li JIN, Da FANG. The spatial spillover of housing price and its determinants: Case study in the Yangtze River Delta[J]. World Regional Studies, 2023, 32(1): 117-129.
韦汝虹, 金李, 方达. 商品住宅价格空间溢出效应测度及其影响 因素分析[J]. 世界地理研究, 2023, 32(1): 117-129.
Add to citation manager EndNote|Ris|BibTeX
URL: https://sjdlyj.ecnu.edu.cn/EN/10.3969/j.issn.1004-9479.2023.01.2020680
Fig.1 Study area
| 住宅类型 | 新住宅/ （万元/平方米） | 二手住宅/ （万元/平方米） | 租赁住宅/ （元/月·平方米） |
|---|---|---|---|
| 均值 | 1.16 | 1.31 | 26.02 |
| 最大值 | 6.13 | 5.41 | 86.30 |
| 最小值 | 0.45 | 0.59 | 13.80 |
| 标准差 | 0.93 | 0.87 | 14.56 |
Tab.1 Statistics analysis on housing price in the Yangtze River Delta
| 住宅类型 | 新住宅/ （万元/平方米） | 二手住宅/ （万元/平方米） | 租赁住宅/ （元/月·平方米） |
|---|---|---|---|
| 均值 | 1.16 | 1.31 | 26.02 |
| 最大值 | 6.13 | 5.41 | 86.30 |
| 最小值 | 0.45 | 0.59 | 13.80 |
| 标准差 | 0.93 | 0.87 | 14.56 |
Fig.2 Housing price from the perspective of 3D in the Yangtze River Delta
Fig.3 Spatial pattern of housing price in the Yangtze River Delta
| 指标 | 新住宅 | 二手住宅 | 租赁住宅 |
|---|---|---|---|
| Moran’s I 指数 | 0.330 3 | 0.315 4 | 0.242 2 |
| 预期指数 | -0.023 8 | -0.023 8 | -0.023 8 |
| 方差 | 0.007 7 | 0.008 7 | 0.009 2 |
| Z得分 | 4.023 8 | 3.646 7 | 2.772 6 |
| P值 | 0.000 1 | 0.000 3 | 0.005 5 |
Tab.2 Test on the spatial linkage of housing price by GSA Model in the Yangtze River Delta
| 指标 | 新住宅 | 二手住宅 | 租赁住宅 |
|---|---|---|---|
| Moran’s I 指数 | 0.330 3 | 0.315 4 | 0.242 2 |
| 预期指数 | -0.023 8 | -0.023 8 | -0.023 8 |
| 方差 | 0.007 7 | 0.008 7 | 0.009 2 |
| Z得分 | 4.023 8 | 3.646 7 | 2.772 6 |
| P值 | 0.000 1 | 0.000 3 | 0.005 5 |
Fig.4 Hot spot analysis on housing price in the Yangtze River Delta
Fig.5 Conceptual framework of spatial linkage of commercial housing price
| 变量类型 | 解释变量（符号） | 变量含义及单位 |
|---|---|---|
| 经济基础 | 经济产出（GDP1 ） | 人均地区生产总值 /万元 |
| 产业结构（GDP2） | 三产占地区生产总值比/% | |
| 购买需求 | 需求潜力（POP） | 户籍人口/万人 |
| 购买能力（DEP） | 人均居民储蓄存款余额 /万元 | |
| 收入水平（INC ） | 在岗职工平均工资/ 万元 | |
| 供给水平 | 投资额度（INV） | 住宅类地产投资完成额/ 亿元 |
| 社会资源 | 服务水平（EMP） | 房地产从业人数 /万人 |
| 中学教育资源（MID） | 普通中学 /个 | |
| 高校教育资源（UNI） | 普通高等学校 /个 | |
| 交通便利性 | 公路便利性（ROA） | 人均铺装道路面积 /平方米 |
| 机场便利性（AIR） | 是否有机场 | |
| 高铁便利性（HIG） | 是否有高铁站 |
Tab.3 Explanatory variables and their interpretation
| 变量类型 | 解释变量（符号） | 变量含义及单位 |
|---|---|---|
| 经济基础 | 经济产出（GDP1 ） | 人均地区生产总值 /万元 |
| 产业结构（GDP2） | 三产占地区生产总值比/% | |
| 购买需求 | 需求潜力（POP） | 户籍人口/万人 |
| 购买能力（DEP） | 人均居民储蓄存款余额 /万元 | |
| 收入水平（INC ） | 在岗职工平均工资/ 万元 | |
| 供给水平 | 投资额度（INV） | 住宅类地产投资完成额/ 亿元 |
| 社会资源 | 服务水平（EMP） | 房地产从业人数 /万人 |
| 中学教育资源（MID） | 普通中学 /个 | |
| 高校教育资源（UNI） | 普通高等学校 /个 | |
| 交通便利性 | 公路便利性（ROA） | 人均铺装道路面积 /平方米 |
| 机场便利性（AIR） | 是否有机场 | |
| 高铁便利性（HIG） | 是否有高铁站 |
| 变量 | 新住宅 | 二手住宅 | 租赁住宅 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 模型I | 模型II | 模型III | 模型I | 模型II | 模型III | 模型I | 模型II | 模型III | |
| LN(GDP2) | -0.08 (0.99) | -0.02 (1.05) | 1.57* (0.82) | 0.15 (1.03) | 0.38 (1.11) | 1.95** (0.89) | 0.17 (1.10) | -0.08 (1.09) | 1.99** (0.94) |
| Ln(ROA) | -0.00 (0.24) | -0.03 (0.22) | -0.18 (0.21) | -0.12 (0.25) | -0.14 (0.23) | -0.23 (0.22) | -0.10 (0.27) | -0.19 (0.23) | -0.25 (0.24) |
| AIR | -0.25 (0.21) | -0.23 (0.21) | -0.22 (0.21) | -0.22 (0.22) | -0.19 (0.22) | -0.15 (0.22) | -0.22 (0.23) | -0.24 (0.22) | -0.18 (0.24) |
| HIG | 0.09 (0.21) | -0.19 (0.25) | 0.06 (0.24) | 0.08 (0.22) | -0.24 (0.26) | 0.10 (0.25) | -0.01 (0.24) | -0.42 (0.26) | -0.01 (0.27) |
| LN(INC) | 2.16** (0.79) | 2.61** (0.83) | 2.32** (0.89) | ||||||
| LN(POP) | 0.44 (0.31) | 0.50 (0.32) | 0.39 (0.34) | ||||||
| LN(INV) | -0.02 (0.25) | -0.14 (0.26) | 0.04 (0.28) | ||||||
| LN(GDP1) | 0.02 (0.32) | 0.12 (0.34) | -0.09 (0.36) | ||||||
| LN(DEP) | 0.79** (0.33) | 0.99** (0.34) | 1.19** (0.36) | ||||||
| LN(EMP) | -0.02 (0.15) | -0.12 (0.16) | -0.09 (0.16) | ||||||
| LN(MID) | 0.52* (0.28) | 0.59** (0.30) | 0.71** (0.29) | ||||||
| LN(UNI) | 0.24** (0.12) | 0.17 (0.13) | 0.19 (0.14) | ||||||
| Constant | -6.30* (3.51) | -3.58 (4.09) | -6.06** (2.99) | -7.80** (3.69) | -5.56 (4.39) | -7.38** (3.27) | -7.17* (3.91) | -4.47 (4.31) | -7.43** (3.42) |
| 空间滞后项 | 0.77** (0.09) | 0.70** (0.11) | 0.83** (0.07) | 0.70** (0.10) | 0.62** (0.13) | 0.80** (0.08) | 0.67** (0.12) | 0.50** (0.15) | 0.74** (0.10) |
| R2 | 0.82 | 0.80 | 0.78 | 0.82 | 0.79 | 0.77 | 0.76 | 0.78 | 0.71 |
| N | 42 | 42 | 42 | 42 | 42 | 42 | 42 | 42 | 42 |
Tab.4 Results of Spatial Lag Model
| 变量 | 新住宅 | 二手住宅 | 租赁住宅 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 模型I | 模型II | 模型III | 模型I | 模型II | 模型III | 模型I | 模型II | 模型III | |
| LN(GDP2) | -0.08 (0.99) | -0.02 (1.05) | 1.57* (0.82) | 0.15 (1.03) | 0.38 (1.11) | 1.95** (0.89) | 0.17 (1.10) | -0.08 (1.09) | 1.99** (0.94) |
| Ln(ROA) | -0.00 (0.24) | -0.03 (0.22) | -0.18 (0.21) | -0.12 (0.25) | -0.14 (0.23) | -0.23 (0.22) | -0.10 (0.27) | -0.19 (0.23) | -0.25 (0.24) |
| AIR | -0.25 (0.21) | -0.23 (0.21) | -0.22 (0.21) | -0.22 (0.22) | -0.19 (0.22) | -0.15 (0.22) | -0.22 (0.23) | -0.24 (0.22) | -0.18 (0.24) |
| HIG | 0.09 (0.21) | -0.19 (0.25) | 0.06 (0.24) | 0.08 (0.22) | -0.24 (0.26) | 0.10 (0.25) | -0.01 (0.24) | -0.42 (0.26) | -0.01 (0.27) |
| LN(INC) | 2.16** (0.79) | 2.61** (0.83) | 2.32** (0.89) | ||||||
| LN(POP) | 0.44 (0.31) | 0.50 (0.32) | 0.39 (0.34) | ||||||
| LN(INV) | -0.02 (0.25) | -0.14 (0.26) | 0.04 (0.28) | ||||||
| LN(GDP1) | 0.02 (0.32) | 0.12 (0.34) | -0.09 (0.36) | ||||||
| LN(DEP) | 0.79** (0.33) | 0.99** (0.34) | 1.19** (0.36) | ||||||
| LN(EMP) | -0.02 (0.15) | -0.12 (0.16) | -0.09 (0.16) | ||||||
| LN(MID) | 0.52* (0.28) | 0.59** (0.30) | 0.71** (0.29) | ||||||
| LN(UNI) | 0.24** (0.12) | 0.17 (0.13) | 0.19 (0.14) | ||||||
| Constant | -6.30* (3.51) | -3.58 (4.09) | -6.06** (2.99) | -7.80** (3.69) | -5.56 (4.39) | -7.38** (3.27) | -7.17* (3.91) | -4.47 (4.31) | -7.43** (3.42) |
| 空间滞后项 | 0.77** (0.09) | 0.70** (0.11) | 0.83** (0.07) | 0.70** (0.10) | 0.62** (0.13) | 0.80** (0.08) | 0.67** (0.12) | 0.50** (0.15) | 0.74** (0.10) |
| R2 | 0.82 | 0.80 | 0.78 | 0.82 | 0.79 | 0.77 | 0.76 | 0.78 | 0.71 |
| N | 42 | 42 | 42 | 42 | 42 | 42 | 42 | 42 | 42 |
| 变量 | 新住宅 | 二手住宅 | 租赁住宅 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 模型I | 模型II | 模型III | 模型I | 模型II | 模型III | 模型I | 模型II | 模型III | |
| LN(GDP2) | -0.02 (0.99) | -0.01 (1.04) | 1.60* (0.82) | 0.16 (1.05) | 0.40 (1.13) | 1.99** (0.91) | 0.20 (1.07) | 0.08 (1.09) | 2.07** (0.93) |
| Ln(ROA) | -0.03 (0.24) | -0.07 (0.22) | -0.21 (0.21) | -0.11 (0.25) | -0.13 (0.24) | -0.22 (0.23) | -0.09 (0.26) | -0.12 (0.23) | -0.17 (0.23) |
| AIR | -0.24 (0.21) | -0.22 (0.21) | -0.21 (0.21) | -0.25 (0.22) | -0.21 (0.23) | -0.16 (0.23) | -0.24 (0.23) | -0.24 (0.22) | -0.20 (0.23) |
| HIG | 0.10 (0.21) | -0.19 (0.25) | 0.07 (0.24) | 0.11 (0.55) | -0.23 (0.27) | 0.13 (0.26) | 0.04 (0.23) | -0.33 (0.26) | 0.07 (0.26) |
| LN(INC) | 2.17** (0.82) | 2.71** (0.84) | 2.37** (0.86) | ||||||
| LN(POP) | 0.44 (0.31) | 0.54* (0.32) | 0.38 (0.33) | ||||||
| LN(INV) | -0.03 (0.26) | -0.17 (0.27) | -0.00 (0.28) | ||||||
| LN(GDP1) | 0.02 (0.33) | 0.15 (0.34) | 0.04 (0.35) | ||||||
| LN(DEP) | 0.82** (0.33) | 1.03** (0.37) | 1.12** (0.36) | ||||||
| LN(EMP) | -0.02 (0.15) | -0.13 (0.17) | -0.07 (0.16) | ||||||
| LN(MID) | 0.53* (0.28) | 0.62** (0.30) | 0.61** (0.29) | ||||||
| LN(UNI) | 0.24** (0.12) | 0.17 (0.13) | 0.17 (0.13) | ||||||
| Constant | -6.52* (3.52) | -3.66 (4.09) | -6.15** (3.00) | -8.14** (3.74) | -5.86 (4.46) | -7.55** (3.34) | -7.44* (3.83) | -4.70 (4.28) | -7.91** (3.38) |
| 空间滞后项 | 0.76** (0.09) | 0.69** (0.11) | 0.83** (0.08) | 0.68** (0.11) | 0.60** (0.13) | 0.79** (0.09) | 0.65** (0.12) | 0.51** (0.14) | 0.74** (0.10) |
| R2 | 0.81 | 0.80 | 0.78 | 0.81 | 0.80 | 0.76 | 0.78 | 0.78 | 0.72 |
| N | 42 | 42 | 42 | 42 | 42 | 42 | 42 | 42 | 42 |
Tab.5 Test of robustness（Spatial Lag Model）
| 变量 | 新住宅 | 二手住宅 | 租赁住宅 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 模型I | 模型II | 模型III | 模型I | 模型II | 模型III | 模型I | 模型II | 模型III | |
| LN(GDP2) | -0.02 (0.99) | -0.01 (1.04) | 1.60* (0.82) | 0.16 (1.05) | 0.40 (1.13) | 1.99** (0.91) | 0.20 (1.07) | 0.08 (1.09) | 2.07** (0.93) |
| Ln(ROA) | -0.03 (0.24) | -0.07 (0.22) | -0.21 (0.21) | -0.11 (0.25) | -0.13 (0.24) | -0.22 (0.23) | -0.09 (0.26) | -0.12 (0.23) | -0.17 (0.23) |
| AIR | -0.24 (0.21) | -0.22 (0.21) | -0.21 (0.21) | -0.25 (0.22) | -0.21 (0.23) | -0.16 (0.23) | -0.24 (0.23) | -0.24 (0.22) | -0.20 (0.23) |
| HIG | 0.10 (0.21) | -0.19 (0.25) | 0.07 (0.24) | 0.11 (0.55) | -0.23 (0.27) | 0.13 (0.26) | 0.04 (0.23) | -0.33 (0.26) | 0.07 (0.26) |
| LN(INC) | 2.17** (0.82) | 2.71** (0.84) | 2.37** (0.86) | ||||||
| LN(POP) | 0.44 (0.31) | 0.54* (0.32) | 0.38 (0.33) | ||||||
| LN(INV) | -0.03 (0.26) | -0.17 (0.27) | -0.00 (0.28) | ||||||
| LN(GDP1) | 0.02 (0.33) | 0.15 (0.34) | 0.04 (0.35) | ||||||
| LN(DEP) | 0.82** (0.33) | 1.03** (0.37) | 1.12** (0.36) | ||||||
| LN(EMP) | -0.02 (0.15) | -0.13 (0.17) | -0.07 (0.16) | ||||||
| LN(MID) | 0.53* (0.28) | 0.62** (0.30) | 0.61** (0.29) | ||||||
| LN(UNI) | 0.24** (0.12) | 0.17 (0.13) | 0.17 (0.13) | ||||||
| Constant | -6.52* (3.52) | -3.66 (4.09) | -6.15** (3.00) | -8.14** (3.74) | -5.86 (4.46) | -7.55** (3.34) | -7.44* (3.83) | -4.70 (4.28) | -7.91** (3.38) |
| 空间滞后项 | 0.76** (0.09) | 0.69** (0.11) | 0.83** (0.08) | 0.68** (0.11) | 0.60** (0.13) | 0.79** (0.09) | 0.65** (0.12) | 0.51** (0.14) | 0.74** (0.10) |
| R2 | 0.81 | 0.80 | 0.78 | 0.81 | 0.80 | 0.76 | 0.78 | 0.78 | 0.72 |
| N | 42 | 42 | 42 | 42 | 42 | 42 | 42 | 42 | 42 |
| 1 | 周晶, 郭明英. 我国 35 个大中城市住房市场泡沫水平测度. 统计与决策, 2020 (1): 48-52. |
| ZHOU J, GUO M. Measurement of real estate market bubble of 35 cities in China. Statistics and Decision, 2020 (1): 48-52. | |
| 2 | 韦汝虹,金李,方达. 基于GIS的中国城市房地产泡沫的空间传染性分析:以2006～2014年35个大中城市为例.长江流域资源与环境,2018,27(9):1967-1976. |
| WEI R, JIN L, FANG D. Study on the spatial infection of real estate market bubble based on GIS in China: Case study of 35 metropolises in 2006~2014. Resources and Environment in the Yangtze Basin,2018,27(9):1967-1976. | |
| 3 | 张祚. 中国城市居民住房来源构成与省际差异:基于 "五普" 与 "六普" 数据的分析. 世界地理研究, 2014 (3): 52-63. |
| ZHANG Z. Housing supplying sources and provincial differences of Chinese urban residents: Based on 5th and 6th census data analysis. World Regional Studies, 2014 (3): 52-63. | |
| 4 | 曹春艳,曹志鹏.房产税对商品住宅价格的影响研究:基于重庆、上海房产税改革试点情况.价格月刊,2017(6):24-27. |
| CAO C, CAO Z. Research on the impact of real estate tax on price of commercial residential houses: Based on reform pilot situation in Chongqing and Shanghai. Prices Monthly,2017(6):24-27. | |
| 5 | 王宝令,李杰,马雪妍.沈阳市区域集聚行为对商品住宅价格的影响.沈阳建筑大学学报:社会科学版,2017(5): 493-497. |
| WANG B, LI J, MA X. The impact of regional agglomeration behavior on commercial housing price in Shenyang. Journal of Shenyang Jianzhu University:Social Science edition, 2017(5): 493-497. | |
| 6 | 宋宏,张璐.商业投资与房地产价格影响因素分析:以西安市为例.商业经济研究,2018(11):185-187. |
| SONG H, ZHANG L. Influential factors of commercial investment and housing price: A case study of Xi'an city. Journal of Commercial Economics,2018(11):185-187. | |
| 7 | 胡丽媛,罗小芳,许长新.人民币汇率对房地产价格的作用机制:基于FDI中介效应.商业经济研究,2019(2):157-160. |
| HU L, LUO X, XU C. The impact of RMB exchange rate of housing price: On the medicating role of FDI. Journal of Commercial Economics, 2019(2):157-160. | |
| 8 | 侯春灯,侯智勇.城市商品住宅价格经济影响因素计量分析.现代城市研究,2017(4):45-50. |
| HOU C, HOU Z. Econometric analysis on the economic factors of urban commercialized residential buildings price. Modern Urban Research,2017(4):45-50. | |
| 9 | 王岱, 刘宽斌, 张涛. 基于网民关注行为大数据实现对房地产价格的预测研究:以北京市房价为例. 数量经济研究, 2019(10): 154-166. |
| WANG D, LIU K, ZHANG T. Prediction of house price based on internet users' behavioral big data: Take housing price in Beijing. The Journal of Quantitative Economics, 2019(10): 154-166. | |
| 10 | 张立新,姜吉坤,温海珍.基于特征价格模型的商品住宅价格评估方法应用.统计与决策,2010(21):157-159. |
| ZHANG L, JIANG J, WEN H. The application of hedonic pricing models for the estimation of housing price. Statistics and Decision,2010(21):157-159. | |
| 11 | 石振武,袁甜甜.基于系统动力学的商品住宅价格宏观调控政策研究: 以哈尔滨市为例.价格月刊,2016(10):5-10. |
| SHI Z, YUAN T. System dynamics analysis and application on the impact of macro-control on commercial housing price: Taking Harbin as an example. Prices Monthly, 2016(10):5-10. | |
| 12 | 吴振华,王亚蓓.商品住宅价格系统动力学仿真与政策实验: 深圳与桂林数据比较.数学的实践与认识,2015(9):139-145. |
| WU Z, WANG Y. System dynamics simulation and policy experiments of urban commodity residence price-data comparison of Shenzhen and Guilin. Mathematics in Practice and Theory, 2015(9):139-145. | |
| 13 | 吴振华,王亚蓓,唐芹.深圳市商品住宅价格系统动力学模型仿真与政策实验.工程管理学报,2015,(3):136-141. |
| WU Z, WANG Y, TANG Q. The simulation and policy experiments of system dynamics model on the commercial housing price in Shenzhen. Journal of Engineering Management, 2015(3):136-141. | |
| 14 | 杨海娟,高二龙,赵新正, 等.西安市商品住宅价格空间格局的演化研究.测绘科学,2017(3):86-92. |
| YANG H, GAO E, ZHAO X, et al. Research on the evolution of the spatial pattern of commodity housing price in Xi'an city. Science of Surveying and Mapping,2017(3):86-92. | |
| 15 | 李文慧,韩惠.兰州市商品住宅价格的空间分异规律.测绘科学,2018(2):45-50. |
| LI W, HAN H. Characteristics of commercial residential price spatial differentiation in Lanzhou City. Science of Surveying and Mapping,2018(2):45-50. | |
| 16 | 石忆邵,李木秀.上海市住房价格梯度及其影响因素分析.地理学报,2006(6):604-612. |
| SHI Y, LI M. The analysis of the housing price gradient and its impact factors of Shanghai city. Acta Geographica Sinica, 2006(6):604-612. | |
| 17 | 王林林,左登华,董立峰.基于地统计分析的商品住宅价格空间分布研究.测绘地理信息,2015(5):52-54. |
| WANG L, ZUO D, DONG L. Spatial distribution of housing price based on geostatistics. Journal of Geomatics,2015(5):52-54. | |
| 18 | 尹上岗, 宋伟轩, 马志飞, 等.南京市住宅价格时空分异格局及影响因素分析:基于地理加权回归模型的实证研究.人文地理, 2018,33(3): 68-77. |
| YIN S, SONG W, MA Z, et al. Spatial differentiation and influencing factors analysis of housing prices in Nanjing: Based on Geographically Weighted Regression Model. Human Geography, 2018,33(3): 68-77. | |
| 19 | 陈多长,洪丹萍. 中国商品住宅价格省际差异的决定因素: 基于货币数量论的实证研究.浙江工业大学学报(社会科学版),2013,12(3):268-274. |
| CHEN D, HONG D. Determinants of the spatial difference of Chinese commodity housing price: An empirical study based on the quantity theory of money. Journal of Zhejiang University of Technology: Social Science edition,2013,12(3):268-274. | |
| 20 | ROEHNER B. Spatial analysis of real estate price bubbles: Paris, 1984-1993. Regional Science & Urban Economics, 1999, 29(1):73-88. |
| 21 | CAMERON G, MUELLBAUER J, MURPHY A. Was There a British House Price Bubble? Evidence from a Regional Panel. Oxford: University of Oxford, 2006. |
| 22 | 朱吉.中国城市房地产泡沫的时空特征分析.商业经济研究,2017(2):186-188. |
| ZHU J. A study on the spatial-temporal characteristics of real estate bubble of city in China. Journal of Commercial Economics,2017(2):186-188. | |
| 23 | 曾祥渭,刘志东,刘雯宇.我国城市群商品住宅价格传导与波动性外溢研究.管理评论,2015(9):3-13. |
| ZENG X, LIU Z, LIU W. Study on transmission and volatility spillover of housing prices in China's urban agglomerations. Management Review,2015(9):3-13. | |
| 24 | 陈雪楚, 彭建刚, 吴梦吟. 城市间房价相关性与系统性金融风险防范. 上海金融, 2012(8):16-20. |
| CHEN X, PENG J, WU M. Correlation of house price among cities and systematic financial risk prevention. Shanghai Finance, 2012(8):16-20. | |
| 25 | 张攀红. 中国房地产价格波动、泡沫测度及区域空间传染研究. 武汉:华中科技大学, 2016. |
| ZHANG P. Research on fluctuation of housing price, housing bubble's detection and its spatial contagion in China. Wuhan: Huazhong University of Science and Technology, 2016 | |
| 26 | 郭燕. 我国房地产泡沫的空间分布和传染机制研究. 长沙: 湖南大学, 2007. |
| GUO Y. The research on spatial distribution and infection mechanism of real estate bubble in China. Changsha: Hunan University, 2007. | |
| 27 | 苑德宇, 宋小宁. 中国区域房价泡沫测度及空间传染性研究: 基于2001-2005年35个大中城市面板数据的实证分析. 上海财经大学学报, 2008, 10(3):78-85. |
| YUAN D, SONG X. The research on measurement of bubble and spatial infection of regional real estate price in China: Empirical analysis based on 35 metropolises from 2001 to 2005. Journal of Shanghai University of Finance and Economics, 2008, 10(3):78-85. | |
| 28 | NNEJI O, BROOKS C, WARD C. Speculative bubble spillovers across regional housing markets. Ssrn Electronic Journal, 2015, 91(3):516-535. |
| 29 | 李影影. 经济联系视角下泛长三角网络结构研究. 世界地理研究, 2019, 28(1): 68-78. |
| LI Y. Research on spatial network structure of Pan-Yangtze River Delta. World Regional Studies, 2019, 28(1): 68-78. | |
| 30 | 王霜. 我国房地产投资影响因素实证研究.重庆: 重庆理工大学, 2017. |
| WANG S. Real estate investment influencing factors of the empirical research in China. Chongqing: Chongqing University of Technology, 2017 | |
| 31 | 郭敬禹,卢东斌.我国房地产价格波动机制研究:基于房地产投资需求的分析.价格理论与实践,2011(6):38-39. |
| GUO J, LU D. The mechanism of real estate price in China: Based on the analysis of investment demand for real estate industry. Price: Theory & Practice,2011(6):38-39. | |
| 32 | 任晓红. 交通基础设施、要素流动与制造业区位.重庆: 重庆大学, 2010. |
| REN X. Transportation infrastructure, factor mobility and manufacturing location. Chongqing: Chongqing University, 2010. | |
| 33 | 马光荣,程小萌,杨恩艳.交通基础设施如何促进资本流动:基于高铁开通和上市公司异地投资的研究.中国工业经济,2020(6):5-23. |
| MA G, CHENG X, YANG E. How does transportation infrastructure affect capital flows: A study from high-speed rail and cross-region investment of listed companies. China Industrial Economics, ,2020(6):5-23. | |
| 34 | ANSELIN L. Exploring Spatial Data with GeoDaTM: A Workbook. USA: Center for Spatially Integrated Science, 2005. |
| Viewed | ||||||
|
Full text |
|
|||||
|
Abstract |
|
|||||
