北京市居住用地出让价格的空间格局及影响因素

doi:10.11821/dlxb201706008

Abstract

Abstract:

In this paper, we take Beijing as a case study and employ the residential leasing parcel data from 2004 to 2015 within the Sixth Ring Road of Beijing metropolitan area. Also, we use the GIS data of Beijing's public facilities, such as bus stations, railway stations, park, hospital, primary school and so on. With the help of ArcGIS, GS+, Surfer and Geoda Software, we explore the spatial pattern of residential land parcels, residential land price and determinants of residential land price in Beijing. In the first place, we use the methods of Spatial Trend Analysis, Nearest Neighbor Index (NNI), Exploratory Spatial Data Analysis (ESDA) to explore the spatial pattern of residential land parcels and their price in Beijing. In the second place, we compare the spatial econometric models (SLM and SEM) with traditional OLS model to further explore the determinants of residential land price in Beijing. Based on the analysis, the main conclusions are drawn as follows. (1) The number of residential land leasing parcels is not balanced among years and ring roads. The residential land leasing parcels in the last 20 years are mainly concentrated between the fifth and the sixth ring roads in Beijing. (2) Residential land parcels are generally distributed along the main roads (such as Beijing-Shijiazhuang Expressway, Beijing-Kaifeng Expressway, Beijing-Shanghai Expressway and Beijing-Tibet Expressway) and the subway lines (such as Line 1, Line 5, Line 6, Line 15, Fangshan Line, Daxing Line and Yizhuang Line), which is more obvious in outer suburban areas. (3) Generally, there exists an inverted U-shaped curve trend, indicating that residential land price declines gradually from the city center to the city fringes as a whole, and spatial pattern of residential land price has turned from mono-centric structure to poly-centric structure. (4) Residential land price demonstrates a spatial cluster distribution pattern. There exists obvious spatial autocorrelation in residential land price and it is easy to distinguish "cold spots" from "hot spots". (5) In the model selection, we compare the spatial econometric model (SLM and SEM) with the traditional OLS model. The result shows that SLM is the best, followed by SEM, indicating that there indeed exist spatial spillover effects and spatial dependence in residential land price rather than error dependence. The residential land price is mainly affected by the surrounding residential land price, distance to bus station, distance to subway station, distance to key primary school, area of land parcel, FAR and the type of land leasing. However, in this paper, one drawback is that we fail to take macroeconomic policy factors into consideration, which may play a key role in the formation of residential land price. Also, we have not considered the subway's impact in different periods such as planning period, construction period and operation period on residential land price, which needs to be further studied.

Key words: residential land price, spatial pattern, exploratory spatial data analysis, spatial lag model, spatial error model, Beijing

Nana CUI, Changchun FENG, Yu SONG. Spatial pattern of residential land parcels and determinants of residential land price in Beijing since 2004[J].Acta Geographica Sinica, 2017, 72(6): 1049-1062.

Figures/Tables 12

Fig. 1

Tab. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Tab. 2

Tab. 3

Tab. 4

Tab. 5

References 46

[1]	Alonso W.Location and Land Use. Cambridge: Havard University Press, 1964.
[2]	Burgess E W.The growth of the city: An introduction to a research project//Park R E, Burgess E W, McKenzie R D. The City. Chicago: University of Chicago Press, 1925.
[3]	Hoyt H.The structure and growth of residential neighborhoods in American cities. Washington DC: Federal Housing Administration, 1939. doi: 10.1080/00420987020080351
[4]	Harris C D, Ullman E L.The nature of cities. The Annals of the American Academy of Political and Social Science, 1945, 242(4): 7-17.
[5]	Wu Wujie, Zhang Wenzhong, Liu Zhilin, et al.Tempo-spatial analysis of the residential land's spatial pattern in Beijing. Geographical Research, 2010, 29(4): 683-692. doi: 10.11821/yj2010040011
	[武文杰, 张文忠, 刘志林, 等. 北京市居住用地出让的时空格局演变. 地理研究, 2010, 29(4): 683-692.] doi: 10.11821/yj2010040011
[6]	Yu Wei, Song Jinping, Zhang Meng.Spatial distribution change of leased residential land in Beijing since 2001. China Land Sciences, 2012, 26(3): 86-90.
	[于伟, 宋金平, 张萌. 近十年来北京市住宅用地出让与空间演变研究. 中国土地科学, 2012, 26(3): 86-90.]
[7]	Li Ling, Zhu Daolin, Hu Kelin.Spatial-temporal change of remised land price in urban area of Beijing. Economic Geography, 2011, 31(4): 654-659.
	[李玲, 朱道林, 胡克林. 北京市城区住宅地价的时空变化规律. 经济地理, 2011, 31(4): 654-659.]
[8]	Deng Yu.Spatial pattern and bid rent of land price in Beijing. Journal of Natural Resources, 2015, 30(2): 218-225.
	[邓羽. 北京市土地出让价格的空间格局与竞租规律探讨. 自然资源学报, 2015, 30(2): 218-225.]
[9]	Ding C R.Urban spatial development in the land policy reform era: evidence from Beijing. Urban Studies, 2004, 41(10):1889-1907. doi: 10.1080/0042098042000256305
[10]	Wang Zhen, Guo Huaicheng, He Chengjie, et al.Driving force analysis of residential land price in Beijing based on statistical methods. Acta Geographica Sinica, 2009, 64(10): 1214-1220. doi: 10.3321/j.issn:0375-5444.2009.10.007
	[王真, 郭怀成, 何成杰, 等. 基于统计学的北京城市居住用地价格驱动力分析. 地理学报, 2009, 64(10): 1214-1220.] doi: 10.3321/j.issn:0375-5444.2009.10.007
[11]	Wu Wenjie, Liu Zhilin, Zhang Wenzhong.Determinants of residential land price: Structure equation model analysis using land-leasing parcel data in Beijing. Acta Geographica Sinica, 2010, 65(6): 676-684. doi: 10.11821/xb201006005
	[武文杰, 刘志林, 张文忠. 基于结构方程模型的北京居住用地价格影响因素评价. 地理学报, 2010, 65(6): 676-684.] doi: 10.11821/xb201006005
[12]	Dong Guanpeng, Zhang Wenzhong, Wu Wenjie, et al.Spatial heterogeneity in determinants of residential land price: simulation and prediction. Acta Geographica Sinica, 2011, 66(6): 750-760.
	[董冠鹏, 张文忠, 武文杰, 等. 北京市城市住宅土地市场空间异质性模拟与预测. 地理学报,2011, 66(6): 750-760.]
[13]	Walden M L.Magnet schools and the differential impact of quality on residential property values. Journal of Real Estate Research, 1990, 5(2): 221-230.
[14]	Wang Y M, Potoglou D, Orford S, et al.Bus stop, property price and land value tax: A multilevel hedonic analysis with quantile calibration. Land Use Policy, 2015, 42: 381-391. doi: 10.1016/j.landusepol.2014.07.017
[15]	Qin Bo, Sun Liang.The impacts of floor area ratio and transfer modes on land prices: Based on hedonic price model. China Land Science, 2010, 24(3): 70-74. doi: 10.3969/j.issn.1001-8158.2010.03.013
	[秦波, 孙亮. 容积率和出让方式对地价的影响: 基于特征价格模型. 中国土地科学, 2010, 24(3): 70-74.] doi: 10.3969/j.issn.1001-8158.2010.03.013
[16]	Liu Hongbin, Wang Qiubing.A study on the influence factors of land granting price of the urban residential land based on hedonic model. Economic Geography, 2011, 31(6): 1008-1013.
	[刘洪彬, 王秋兵. 基于特征价格模型的城市住宅用地出让价格影响因素研究. 经济地理, 2011, 31(6): 1008-1013.]
[17]	Can A.Specification and estimation of hedonic house price models. Regional Science and Urban Economics, 1992, 22(3): 453-474. doi: 10.1016/0166-0462(92)90039-4
[18]	Calhoun C A.Property valuation models and house price indexes for the provinces of Thailand: 1992-2000. Housing Finance International, 2003, 17(3): 31-41.
[19]	Li L H.Land price changes in the evolving land market in Beijing. Property Management, 2009, 27(2): 91-108. doi: 10.1108/02637470910946408
[20]	Kim H G, Hung K C, Park S Y.Determinants of housing prices in Hong Kong: A box-cox quantile regression approach. Journal of Real Estate Finance and Economics, 2015, 50(2): 270-287. doi: 10.1007/s11146-014-9456-1
[21]	Xu Jianhua.Mathematical Methods in Modern Geography. 2nd ed. Beijing: Higher Education Press, 2002.
	[徐建华. 现代地理学中的数学方法. 2版. 北京: 高等教育出版社, 2002.]
[22]	Wang Yang, Fang Chuanglin, Sheng Changyuan.Spatial differentiation and model evolution of housing prices in Yangzhou. Acta Geographica Sinica, 2013, 68(8): 1082-1096.
	[王洋, 方创琳, 盛长元. 扬州市住宅价格的空间分异与模式演变. 地理学报, 2013, 68(8): 1082-1096.]
[23]	Clark P J, Evans F C.Distance to nearest neighbor as a measure of spatial relationships in populations. Ecology, 1954, 35(4): 445-453. doi: 10.2307/1931034
[24]	Anselin L.Exploring spatial data with Geoda: A workbook. Center for Spatially Integrated Social Science, 2005.
[25]	Anselin L.Interactive techniques and exploratory spatial data analysis//Longley P A, Godchild M F, Maguire D J. Geographical Information System. 2nd ed. New York: John Wiley & Sons, 1999.
[26]	Liu Xiangnan, Huang Fang, Wang Ping, et al.Principles and Methods of GIS Spatial Analysis. Beijing: Science Press,2005.
	[刘湘南, 黄方, 王平, 等. GIS空间分析原理与方法. 北京: 科学出版社, 2005.]
[27]	Meng Bin, Zhang Jingqiu, Wang Jinfeng, et al.Application of spatial analysis to the research of real estate: Taking Beijing as a case. Geographical Research, 2005, 24(6): 956-964. doi: 10.3321/j.issn:1000-0585.2005.06.015
	[孟斌, 张景秋, 王劲峰, 等. 空间分析方法在房地产市场研究中的应用: 以北京市为例. 地理研究, 2005, 24(6): 956-964.] doi: 10.3321/j.issn:1000-0585.2005.06.015
[28]	Pu Yingxia, Ge Ying, Ma Ronghua.Analyzing regional economic disparities based on ESDA. Geographical Research, 2005, 24(6): 965-974.
	[蒲英霞, 葛莹, 马荣华. 基于ESDA的区域经济空间差异分析: 以江苏省为例. 地理研究, 2005, 24(6): 965-974.]
[29]	Gong Yunlong, Zhang Shaoliang, Zhang Lanlan.Spatial autocorrelation of urban land price: A case study of Suzhou. Economic Geography, 2011, 31(11): 1906-1911.
	[公云龙, 张绍良, 章兰兰. 城市地价空间自相关分析: 以宿州市为例. 经济地理, 2011, 31(11): 1906-1911.]
[30]	Getis A, Ord J K.The analysis of spatial association by use of distance statistics. Geographical Analysis, 1992, 24(3):189-206. doi: 10.1111/j.1538-4632.1992.tb00261.x
[31]	Anselin L.Local indicators of spatial association: LISA. Geographical Analysis, 1995, 27(2): 93-115.
[32]	Lesage J, Pace R K.Introduction to Spatial Econometrics. New York. CRC Press, 2009.
[33]	Fischer M M, Wang J F.Spatial Data Analysis: Models, Methods and Techniques. Heidelberg, Dordrecht, London, New York: Springer, 2011.
[34]	Anselin L.Spatial Econometrics: Methods and Models. Dordrecht: Kluwer Academic Publishers,1988. doi: 10.2307/143780
[35]	Anselin L, Bera A K, Florax R, et al.Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics, 1996, 26(1): 77-104. doi: 10.1016/0166-0462(95)02111-6
[36]	Lou Liming.Study on spatial analysis in urban land price information and its application [D]. Hangzhou: Zhejiang University, 2004.
	[楼立明. 城市地价信息的空间分析及其应用研究[D]. 杭州: 浙江大学, 2004.]
[37]	Atack J, Margo R A.Location, location, location! The price gradient for vacant urban land: New York, 1835 to 1900. Journal of Real Estate Finance and Economics, 1998, 16(2): 151-172. doi: 10.1023/A:1007703701062
[38]	Wang Y M, Potoglou D, Orford S, et al.Bus stop, property price and land value tax: A multilevel hedonic analysis with quantile calibration. Land Use Policy, 2015, 42: 381-391. doi: 10.1016/j.landusepol.2014.07.017
[39]	Machin S.Houses and schools: Valuation of school quality through the housing market. Labor Economics, 2011, 18(6): 723-729. doi: 10.1016/j.labeco.2011.05.005
[40]	Zheng S Q, Kahn M E.Land and residential property markets in a booming economy: New evidence from Beijing. Journal of Urban Economics, 2008, 63(2): 743-757. doi: 10.2139/ssrn.939535
[41]	Lv Ping, Zhen Hui.Affecting factors research of Beijing residential land price based on GWR model. Economic Geography, 2010, 30(3): 472-477.
	[吕萍, 甄辉. 基于GWR模型的北京市住宅用地价格影响因素及其空间规律研究. 经济地理, 2010, 30(3): 472-477.]
[42]	Bao Zhenhong, Li Chaokui.Progress on the study of urban architecture FAR. Progress in Geography, 2010, 29(4): 396-402. doi: 10.11820/dlkxjz.2010.04.002
	[鲍振洪, 李朝奎. 城市建筑容积率研究进展. 地理科学进展, 2010, 29(4): 396-402.] doi: 10.11820/dlkxjz.2010.04.002
[43]	Xie Hai, Hong Tao, Jin Jingjing.Impact of land transfer ways on land price. Journal of Engineering Management, 2015, 29(2): 132-136.
	[解海, 洪涛, 靳静静. 土地出让方式对住宅用地价格的差异性影响分析. 工程管理学报, 2015, 29(2): 132-136.]
[44]	Luo Ganghui, Wu Cifang, Zheng Juaner.The influence of parcel land area on housing land price. China Land Science, 2007, 21(5): 66-69. doi: 10.3969/j.issn.1001-8158.2007.05.011
	[罗罡辉, 吴次芳, 郑娟尔. 宗地面积对住宅地价的影响. 中国土地科学, 2007, 21(5): 66-69.] doi: 10.3969/j.issn.1001-8158.2007.05.011
[45]	Colwell P F, Sirmans C F.Area, time, centrality and the value of urban land. Land Economics, 1978, 54(4): 514-519. doi: 10.2307/3146175
[46]	Yang Z, Ren R R, Liu H Y.Land leasing and local government behavior in China: Evidence from Beijing. Urban Studies, 2015, 52(5): 841-856. doi: 10.1177/0042098014529342

解释变量	变量描述	数据来源	均值	标准差
居住地块单价(land_price)	每平方米出让居住地块的成交价格(元/m²)	样本交易数据	25458	19145
天安门(Tiananmen)	地块到天安门距离(m)	实测距离	18242	6459
公交站(Bus)	地块到最近公交站的距离(m)	实测距离	388	261
地铁站(Subway)	地块到出让年份开通运营的最近地铁站距离(m)	实测距离	5112	5450
公园(Park)	地块到最近公园的距离(m)	实测距离	1860	1380
三甲医院(Hospital)	地块到最近三甲医院的距离(m)	实测距离	6573	4732
重点小学(Pschool)	地块到最近重点小学的距离(m)	实测距离	10103	6284
地块面积(Area)	居住地块面积(万m²)	样本交易数据	8.47	6.7
地块面积的平方(Area²）	居住地块面积的平方(万m²×万m²)	样本交易数据	116.42	204.76
容积率(FAR）	地块出让的容积率(%)	样本交易数据	2.27	0.75
出让方式(Leasing)	挂牌=1,招标=0	样本交易数据	0.68	0.47

变量	系数	标准差	t统计量	P值
Intercept	12.99	0.887	14.637	0.000
Ln Tiananmen	-0.28^***	0.119	-2.302	0.022
Ln Bus	0.10^**	0.042	2.329	0.020
Ln Subway	-0.12^***	0.027	-4.389	0.000
Ln Park	0.05	0.044	1.138	0.256
Ln Hospital	0.04	0.045	0.880	0.379
Ln Pschool	-0.20^***	0.058	-3.449	0.001
Area	0.03^**	0.012	2.231	0.026
Area²	-0.001^**	0.000	-2.602	0.010
FAR	0.32^***	0.042	7.569	0.000
Leasing	0.32^***	0.064	5.064	0.000
R²	0.432
调整R²	0.418
LogL	-360.4
AIC	742.8
SC	787.3

检验统计量	统计量	P值
Breusch-Pagan	10.386	0.407
Koenker-Bassett	14.261	0.161
Moran's I(error)	4.856	0.000
LMLAG	15.854	0.000
R-LMLAG	4.624	0.032
LMERR	11.251	0.001
R-LMERR	0.0207	0.886

变量	空间滞后模型(SLM)				空间误差模型(SEM)
变量	系数		标准差	P值	系数	标准差	P值
ρ/λ	0.441^***	0.1	0.000		0.511^***	0.107	0.000
Intercept	6.382	1.687	0.000		12.712	1.248	0.000
Ln Tiananmen	-0.097	0.12	0.420		-0.243	0.169	0.420
Ln Bus	0.087^**	0.04	0.031		0.085^**	0.04	0.031
Ln Subway	-0.121^***	0.027	0.000		-0.144^***	0.028	0.000
Ln Park	0.046	0.043	0.282		0.039	0.046	0.282
Ln Hospital	0.024	0.043	0.575		0.018	0.057	0.575
Ln Pschool	-0.121^**	0.059	0.040		-0.146^**	0.074	0.040
Area	0.025^**	0.012	0.035		0.021^*	0.011	0.035
Area²	-0.001^**	0.000	0.013		-0.001^**	0.000	0.013
FAR	0.328^***	0.041	0.000		0.334^***	0.041	0.000
Leasing	0.336^***	0.062	0.000		0.307^***	0.061	0.000
R²	0.458				0.461
LogL	-352.48				-352.09
AIC	728.96				726.19
SC	777.5				770.68

Spatial pattern of residential land parcels and determinants of residential land price in Beijing since 2004

RichHTML

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

Figures/Tables 12

References 46

Related Articles 15

Metrics

Comments

[1]	CAO Guangzhong, CHEN Sichuang, LIU Tao. Changing spatial patterns of internal migration to five major urban agglomerations in China [J]. Acta Geographica Sinica, 2021, 76(6): 1334-1349.
[2]	LIN Liyue, ZHU Yu, LIN Kun, KE Wenqian. Spatial pattern and determinants of migrants' urban housing purchase intention under the binary-locational household arrangements [J]. Acta Geographica Sinica, 2021, 76(6): 1350-1365.
[3]	MENG Bin, GAO Liping, LI Ruoqian. Spatial correlation analysis of residential and employment elements in Beijing based on collaborative location quotient [J]. Acta Geographica Sinica, 2021, 76(6): 1380-1393.
[4]	GU Hengyu, SHEN Tiyan. Spatial evolution characteristics and driving forces of Chinese highly educated talents [J]. Acta Geographica Sinica, 2021, 76(2): 326-340.
[5]	ZHANG Xuebo, SONG Jinping, YU Wei, WANG Zhenbo. Formation mechanism of Beijing's jobs-housing spatial relationship based on residents' perception [J]. Acta Geographica Sinica, 2021, 76(2): 383-397.
[6]	ZHOU Kan, LI Hui, SHEN Yuming. Spatiotemporal patterns and driving factors of environmental stress in Beijing-Tianjin-Hebei region: A county-level analysis [J]. Acta Geographica Sinica, 2020, 75(9): 1934-1947.
[7]	GAO Xiaolu, WU Danxian, YAN Bingqiu. Measure and distribution of urban elderly in poverty: An empirical study in Beijing [J]. Acta Geographica Sinica, 2020, 75(8): 1557-1571.
[8]	WANG De, LI Dan, FU Yingzi. Employment space of residential quarters in Shanghai: An exploration based on mobile signaling data [J]. Acta Geographica Sinica, 2020, 75(8): 1585-1602.
[9]	CAO Zhi, LIU Yansui, LI Yurui, WANG Yongsheng. Spatial pattern and its influencing factors of specialized villages and towns in China [J]. Acta Geographica Sinica, 2020, 75(8): 1647-1666.
[10]	QU Shijin, HU Shougeng, LI Quanfeng. Stages and spatial patterns of urban built-up land transition in China [J]. Acta Geographica Sinica, 2020, 75(7): 1539-1553.
[11]	REN Mengyao, XIAO Zuopeng, James J. WANG. Spatial pattern of intercity less-than-truckload logistics networks in China [J]. Acta Geographica Sinica, 2020, 75(4): 820-832.
[12]	MA Ning, HE Liye, LIANG Sujie, GUO Jun. Low-frequency characteristics of winter-time cold air activity in the Beijing-Tianjin-Hebei region and the impacts of low-frequency variation of the Siberian High [J]. Acta Geographica Sinica, 2020, 75(3): 485-496.
[13]	WU Yaqun, LI Shuangshuang, YAN Junping, WANG Chengbo. Universities and geographical research development in China based on the bibliometrics analysis [J]. Acta Geographica Sinica, 2020, 75(2): 302-317.
[14]	ZHANG Jie, SHI Peijun, YANG Jing, GONG Daoyi. The impact of the urbanization process on rainfall in Beijing:A case study of 7.21 rainstorm [J]. Acta Geographica Sinica, 2020, 75(1): 113-125.
[15]	JU Hongrun, ZUO Lijun, ZHANG Zengxiang, ZHAO Xiaoli, WANG Xiao, WEN Qingke, LIU Fang, XU Jinyong, LIU Bin, YI Ling, HU Shunguang, SUN Feifei, TANG Zhanzhong. Methods research on describing the spatial pattern of land use types in China [J]. Acta Geographica Sinica, 2020, 75(1): 143-159.