广州中心城区住宅租金差异的核心影响因素

doi:10.11821/dlxb202108008

Abstract

Abstract:

This study constructs a theoretical framework of hedonic rent of urban housing and establishes the elements of housing characteristics suitable for rental housing. The elements include building, convenience, environment, and location characteristics. Based on the monthly data of 23126 houses available for rent in Guangzhou's urban district in March 2020, the spatial difference pattern and spatial correlation of housing rents in the district are analyzed through hierarchical spatial statistics and spatial autocorrelation. We established an index system of housing rent including 12 influencing factors. Through the comparison and selection of three models, the spatial error model is used to measure the influencing factors of housing rent, and the core influencing factors are identified. The results reveal that: (1) The theoretical framework and model of hedonic rent can be used to examine the influencing factors of urban housing rent. (2) Low- and middle-rent houses account for the largest proportion of rental housing in Guangzhou's urban district. Housing rent presents a spatial differentiation pattern that is higher in the core area and lower in the peripheral urban area and old city, with significant spatial agglomeration and correlation characteristics. (3) Four characteristics -- building (building area, orientation & floors, building age, elevator & property management), convenience (metro, office, education convenience), environment (park accessibility, industrial pollution), and location characteristics (distance from central business district (CBD)) -- including 10 factors, have a significant impact on the housing rent difference in Guangzhou's urban district. (4) Building area, building age, and distance from CBD are the three most important core influencing factors for housing rent, followed by elevator and property management and office convenience.

Key words: housing rent, hedonic rent theory, hedonic rent model, rent difference, core influencing factor, Guangzhou

WANG Yang, WU Kangmin, ZHANG Hong'ou. The core influencing factors of housing rent difference in Guangzhou's urban district[J].Acta Geographica Sinica, 2021, 76(8): 1924-1938.

Figures/Tables 9

Fig. 1

Tab. 1

Fig. 2

Tab. 2

The appraisal system of impact factors of housing rents in Guangzhou's urban district

特征租金因素视角	影响因素指标	计算方法(分数赋值标准)	预期影响方向
HR1建筑特征	F1 建筑面积	住宅的建筑面积数值	负向
	F2 朝向与楼层	好朝向且优越楼层(9分);好朝向且一般楼层,或者一般朝向且优越楼层(7分);一般朝向且一般楼层(5分);差朝向且优越楼层(3分),差朝向且一般楼层(1分)。对朝向定义：好朝向为南、东南、西南,差朝向为北,其他情况为一般朝向;对楼层定义：对于楼梯楼,处于低楼层为优越楼层,中高层为一般楼层;对于电梯楼,中高层为优越楼层,低层为一般楼层。	正向
	F3 房龄	2020年减去住房建成时的年份	负向
	F4 电梯与物业	有电梯且有物业公司管理(9分);有电梯且为业主自筹/私人承办/单位代管物业(7分);有电梯但无物业管理,或者无电梯但有物业公司管理(5分);无电梯且为业主自筹/私人承办/单位代管物业(3分);无电梯且无物业管理(1分)	正向
HR2 便利性特征	F5 地铁便利性	距地铁站200 m范围内(9分),距地铁站200~400 m范围内(7分),距地铁站400~800 m范围内(5分),距地铁站800~1500 m范围内(3分),距1500 m范围外(1分)	正向
	F6 办公便利性	将主要办公场所(写字楼、政府机关、事业单位、科技园)点数据生成核密度,并根据标准差均值面进行分级。住宅位于核密度3个标准差以上(含3个标准差)范围内(9分),位于2~3个标准差之间(7分),位于1~2个标准差之间(5分),位于0~1个标准差之间(3分),其他,即位于低于标准差均值的范围内(1分)	正向
	F7 基础教育便利性	将小学、中学的点数据生成核密度,并根据标准差均值面进行分级。赋分方式与办公便利性相同	正向
	F8 商业服务便利性	将主要商业服务网点(市场、超市、商场、餐饮场所、娱乐场所)的点数据生成核密度,并根据标准差均值面进行分级。赋分方式与办公便利性相同	正向
HR3环境特征	F9 公园可达性	位于公园边界100 m范围内(9分),位于公园边界100~200 m范围内(8分),…,距公园800m范围外(1分)	正向
	F10 厌恶型市政设施影响	各类交通或市政类厌恶型设施及其影响范围设定如下：机场(半径5000 m),火车站(半径500 m),长途汽车站(半径500 m),高速公路和高架路(单侧200 m),铁路(单侧80 m),加油站(半径80 m),殡仪馆(半径1000 m),污水处理厂(半径2000 m),垃圾处理场(半径4000 m),变电站(半径500 m),高压走廊(单侧100 m)。在此基础上,赋分如下：未受到厌恶型设施影响(1分),受到1种设施影响(3分),受到2种设施影响(5分),受到3种设施影响(7分),受到4种及4种以上设施影响(9分)	负向
	F11 工业污染影响	将工厂点数据生成核密度,并根据标准差均值面进行分级。赋分方式与办公便利性相同	负向
HR4区位特征	F12 距城市中心的距离	距广州国际金融中心大厦(珠江新城西塔)的距离	负向

Tab. 2

Tab. 3

Fig. 3

Tab. 4

Tab. 5

Fig. 4

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要素	细分特征领域	涉及的主要因素
建筑特征	单户住宅特有特征	建筑面积、所在楼层、朝向、装修程度、视野、通风、采光、住宅设施、户型格局
建筑特征	整栋住宅(或小区)共有特征	房龄、是否有电梯、物业管理水平、楼盘(或小区)档次、绿化水平、容积率、小区设施配套、停车位、开发商品牌、社会文化特征
便利性特征	交通出行便利性	地铁便利性、公交站点便利性、道路交通便利性
	就业便利性	主要就业地点的可达性
	就学便利性	幼儿园、小学、中学、大学的可达性
	商业服务便利性	商场、购物中心、超市、餐饮、娱乐、市场等商业服务场所的可达性
	公共服务与休闲游憩便利性	文化、体育、医疗等各类公共服务设施可达性、各类休闲游憩场所可达性
环境特征	优质环境或景观	公园、水域、自然景区可达性,位于或亲近优质的建成环境或社会环境区域
环境特征	消极环境或景观	受到工厂、物流中心、批发中心、厌恶型交通设施(例如飞机场、港口、火车站、汽车站、高速公路或高架路、加油站)、厌恶型市政设施(例如污水处理厂、垃圾处理场、燃气站、发电厂、变电站、高压走廊、殡仪馆、墓地、信号发射塔)的影响程度,受到环境污染、较差的建成环境、不安全的社会环境影响
区位特征	地理位置	距市中心距离、所处圈层、板块、区域、方位

租金等级	租金区间 (元/(m²·月))	研究区全部		旧城		核心区		外围城区
租金等级	租金区间 (元/(m²·月))	数量(套)	占比(%)	数量(套)	占比(%)	数量(套)	占比(%)	数量(套)	占比(%)
高房租	>100.00	2834	12.25	306	11.42	2254	25.21	274	2.38
中高房租	80.01~100.00	3199	13.83	513	19.14	1889	21.13	797	6.93
中等房租	60.01~80.00	5898	25.50	923	34.44	2903	32.47	2072	18.01
中低房租	40.01~60.00	8424	36.43	835	31.16	1735	19.41	5854	50.88
低房租	≤ 40.00	2771	11.98	103	3.84	159	1.78	2509	21.81
总计	全部	23126	100.00	2680	100.00	8940	100.00	11506	100.00

模型	R²	调整R²	AIC	对数似然数
普通最小二乘法回归模型(OLS)	0.4324	0.4321	10734.50	-5354.27
空间滞后模型(SLM)	0.4864	0.4862	8485.33	-4228.67
空间误差模型(SEM)	0.7356	0.7354	-4040.23	2033.11

因素类别(自变量)	回归系数	标准差	z统计值	P值
F1建筑面积	-0.3494^**	0.0034	-101.4040	0.0000
F2朝向与楼层	0.0196^**	0.0029	6.8631	0.0000
F3房龄	-0.2807^**	0.0126	-22.2924	0.0000
F4电梯与物业	0.1191^**	0.0094	12.6365	0.0000
F5地铁便利性	0.0484^**	0.0092	5.2342	0.0000
F6办公便利性	0.0983^**	0.0174	5.6511	0.0000
F7基础教育便利性	0.0391^*	0.0157	2.4926	0.0127
F8商业服务便利性	-0.0246	0.0131	-1.8787	0.0603
F9公园可达性	0.0240^**	0.0057	4.2099	0.0000
F10厌恶型市政设施影响	0.0130	0.0070	1.8574	0.0633
F11工业污染影响	-0.0555^**	0.0070	-7.9185	0.0000
F12距城市中心的距离	-0.2060^**	0.0088	-23.3809	0.0000
CONSTANT	7.7150^**	0.0974	79.2189	0.0000
LAMBDA	0.7314^**	0.0041	176.5310	0.0000
R²：0.7356;调整R²：0.7354;AIC：-4040.23;对数似然数：2033.11

The core influencing factors of housing rent difference in Guangzhou's urban district

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