经济快速发展背景下中国民用汽车拥有量变化的时空特征

doi:10.13249/j.cnki.sgs.2019.04.015

地理科学 ›› 2019, Vol. 39 ›› Issue (4): 654-662.doi: 10.13249/j.cnki.sgs.2019.04.015

经济快速发展背景下中国民用汽车拥有量变化的时空特征

杨昆¹(), 时燕¹(), 罗毅¹, 夏典²

1. 云南师范大学信息学院/西部资源环境地理信息技术教育部工程研究中心, 云南昆明 650500
2. 云南师范大学数学学院, 云南昆明 650500

收稿日期:2018-01-15 修回日期:2018-04-12 出版日期:2019-04-10 发布日期:2019-04-10
作者简介:
作者简介：杨昆（1963-）,男,云南曲靖人,教授,博导,研究方向为地理信息系统。E-mail: yangkun@ynnu.edu.cn
基金资助:
国家自然科学基金项目（41761084）、云南省自然科学基金青年项目（2016FD020）、云南师范大学研究生科研创新基金(yjs2018127)资助

Spatial-temporal Characteristics of Ownership Change of Civil Car in China

Kun Yang¹(), Yan Shi¹(), Yi Luo¹, Dian Xia²

1. School of Information Science and Technology, GIS Technology Engineering Research Centre for West-China Resources and Environment of Educational Ministry, Yunnan Normal University, Kunming 650500, Yunnan, China
2. School of Mathematics, Yunnan Normal University, Kunming 650500, Yunnan, China

Received:2018-01-15 Revised:2018-04-12 Online:2019-04-10 Published:2019-04-10
Supported by:
National Natural Science Foundation of China (41761084), Youth Project Supported by the Natural Science Foundation of Yunnan (2016FD020), The Graduate Research Innovation Foundation of Yunnan Normal University (yjs2018127)

摘要/Abstract

摘要：

基于统计数据,采用Theil指数、线性倾向率、Mann-Kendall（M-K）检验、面板数据模型,从中国、八大经济区域、各省3个尺度分析中国民用汽车拥有量的时空变化特征及其与地区生产总值、居民消费水平、公路里程的关系。结果表明：① 中国民用汽车拥有量的增长分两个阶段： 1996~2005年为缓慢增长期,2005~2015年为快速增长期;② 2000~2015年中国民用汽车拥有量地区分布差异显著下降,2000~2005年区域内总差异是总差异的主要成分,北部沿海地区区域内差异是区域内总差异的主要原因,2006~2015年区域间差异是总差异的主要成分;③ 在不同的时间阶段及空间尺度各因素对民用汽车拥有量发展的作用方向和作用强度呈现一定的差异性。

关键词: 民用汽车, 时空特征, 经济因素, 中国

Abstract:

With the rapid development of economy, the number of China's motor vehicle rises sharply. The rapid development of the auto industry promotes the social civilization, and drives the sustained economic growth. Cars improve the efficiency of people’s traveling, at the same time, they bring some problems such as traffic congestion, environmental pollution, energy consumption, which directly threat to human health and the sustainable development of social economy. To explore the temporal variation characteristics of civilian cars under the background of China’s rapid economic growth ownership is the basis to solve the problem such as traffic congestion, traffic accidents, car exhaust, it is also the premise of auto industry development and applicable policy. This article reveal the temporal variation characteristics of Chinese civil car ownership and differences, explore the relationship between the civil car ownership change and economic development. With the the number of civil car ownership, gross regional product, household consumption level, highway mileage and provinces population data in 31 provincial level administrative region in mainland China from 1996 to 2015, the empirical research is conducted by adopting Theil index, the linear trend estimation indicates, Mann - Kendall test and panel data mode, respectively, based on the national, the eight economic regions, and 31 provinces three spatial dimensions. The preliminary results shows that: 1) The scope of research and the continuous growth of China's car ownership can be divided into two stages: the first stage, 1996-2005, for the slow growth; The second stage, from 2005 to 2015, is for rapid growth; 2) From 2000 to 2015, China's civil car ownership regional differences declined obviously in 2000-2005, the differences of China’s civil car ownership in 31 provinces regions are determined by differences of within-region, and differences in Northern coastal areas are the main cause of regional differences; The differences of between-region were greater than the differences of within-region in 2006-2015; 3) In the research time range, the gross regional product, residents' consumption level, and highway mileage can improve the number of civil car ownership, and there are significant differences in the influence of three factors on the civil car ownership.

Key words: civil car ownership, spatial-temporal characteristics, economic factors, China

中图分类号:

F129.9

杨昆, 时燕, 罗毅, 夏典. 经济快速发展背景下中国民用汽车拥有量变化的时空特征[J]. 地理科学, 2019, 39(4): 654-662.

Kun Yang, Yan Shi, Yi Luo, Dian Xia. Spatial-temporal Characteristics of Ownership Change of Civil Car in China[J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(4): 654-662.

图/表 8

图1

图2

表1

表2

图3

表3

表4

图4

参考文献 25

[1]	佚名. 中国汽车工业协会2016年1月信息发布会在京举行[J].汽车与安全,2016(1):104.
	[Anon. January 2016 China Association of Automobile Manufactures held an information release in Beijing[J]. Automobile & Safety,2016(1):104.]
[2]	佚名. 二〇一六年中国机动车环境管理年报发布[J].中国环境科学,2016,36(6):1793.
	[Anon. The 2016 China Vehicle Environmental Management Annual Report has been released. China Environmental Science, 2016,36(6):1793]
[3]	Wu T, Zhao H, Ou X.Vehicle ownership analysis based on GDP per capita in China: 1963-2050[J]. Sustainability, 2014, 6(8):4877-4899. doi: 10.3390/su6084877
[4]	孙斌栋, 尹春. 人口密度对居民通勤时耗的影响及条件效应——来自上海证据[J]. 地理科学, 2018, 38(1): 41-48.
	[Sun Bindong, Yin Chun.Impacts and conditional effects of population density on commuting duration: Evidence from Shanghai. Scientia Geographica Sinica, 2018, 38(1): 41-48.]
[5]	Alimi A M, Jamoussi A, Masmoudi I et al. Multi agent parking lots modelling for anomalies detection while parking[J]. IET Computer Vision, 2016, 10(5): 407-414. doi: 10.1049/iet-cvi.2015.0227
[6]	Bharadwaj S, Ballare S, Rohit et al. Impact of congestion on greenhouse gas emissions for road transport in Mumbai metropolitan region[J]. Transportation Research Procedia, 2017, 25:3542-3555.
[7]	王旖旎. 中国汽车需求预测:基于Gompertz模型的分析[J]. 财经问题研究,2005(11):43-50.
	[Wang Yini.Car ownership forecast in China—An analysis based on gompertz equation. Research on Financial & Economic Issues, 2005(11):43-50. ]
[8]	孙璐,郁烨,顾文钧.基于PCA和HMM的汽车保有量预测方法[J].交通运输工程学报,2013,13(2):92-98.
	[Sun Lu, Yu Ye, Gu Wenjun.Car ownership prediction method based on principal component analysis and hidden Markov model. Journal of Traffic & Transportation Engineering, 2013,13(2):92-98.]
[9]	鲍叶静. 我国城镇居民汽车拥有率组合预测——基于收入等级[J].技术经济,2011,30(3):87-90.
	[Bao Yejing.Integrated forecast on car ownership rate of urban dwellers in China:Based on different income levels. Technology Economics, 2011,30(3):87-90.]
[10]	He S Y, Thøgersen J.The impact of attitudes and perceptions on travel mode choice and car ownership in a Chinese megacity: The case of Guangzhou[J]. Research in Transportation Economics, 2017, 62: 57-67. doi: 10.1016/j.retrec.2017.03.004
[11]	蒋艳梅,赵文平.Logistic模型在我国私人汽车保有量预测中的应用研究[J].工业技术经济,2010,29(11):99-104.
	[Jiang Yanmei, Zhao Wenping.Application research of logistic model in private car ownership prediction in China. Journal of Industrial Technological Economics, 2010,29(11):99-104.]
[12]	Li J, Walker J L, Inivasan S et al. Modeling private car ownership in China[J]. Transportation Research Record Journal of the Transportation Research Board, 2010, 2193(1):76-84. doi: 10.3141/2193-10
[13]	Páez A, Scott D M, Potoglou D et al. Elderly mobility: Demographic and spatial analysis of trip making in the hamilton CMA[J]. Urban Studies, 2007, 44(1):123-146. doi: 10.1080/00420980601023885
[14]	Zhang Z, Jin W, Jiang H et al. Modeling heterogeneous vehicle ownership in China: A case study based on the Chinese national survey[J]. Transport Policy, 2017, 54:11-20. doi: 10.1016/j.tranpol.2016.10.005
[15]	Le Vine S, Wu C, Polak J.A nationwide study of factors associated with household car ownership in China[J]. IATSS Research, 2018,42(3):128-137. doi: 10.1016/j.iatssr.2017.10.001
[16]	Shen Q, Chen P, Pan H.Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city[J]. Transportation Research Part A Policy & Practice, 2016, 94:31-44.
[17]	黄晓燕, 曹小曙, 李涛. 中国城市私人汽车发展的时空特征及影响因素[J]. 地理学报, 2012, 67(6):745-757.
	[Huang Xiaoyan,Cao Xiaoshu,Li Tao.The spatio-temporal variations of urban private car ownership in China and their influencing factors. Acta Geographica Sinica, 2012, 67(6): 745-757.]
[18]	Wu N, Zhao S, Zhang Q.A study on the determinants of private car ownership in China: Findings from the panel data[J]. Transportation Research Part A, 2016, 85:186-195.
[19]	Yang Z, Jia P, Liu W et al. Car ownership and urban development in Chinese cities: A panel data analysis[J]. Journal of Transport Geography, 2017, 58:127-134. doi: 10.1016/j.jtrangeo.2016.11.015
[20]	蒋艳梅,赵文平.Logistic模型在我国私人汽车保有量预测中的应用研究[J].工业技术经济,2010,29(11):99-104.
	[Jiang Yanmei, Zhao Wenping.Application research of logistic model in private car ownership prediction in China. Journal of Industrial Technological Economics, 2010,29(11):99-104.]
[21]	王景才, 郭佳香, 徐蛟,等. 近55年淮河上中游流域气候要素多时间尺度演变特征及关联性分析[J]. 地理科学, 2017, 37(4):611-619.
	[Wang Jingcai, Guo Jiaxiang, Xu Jiao et al. Multi-time scales change characteristics and relationship of meteorological variables in the upper and middle regions of the Huaihe River basin in recent 55 years. Scientia Geographica Sinica, 2017, 37(4): 611-619.]
[22]	何云玲, 鲁枝海. 近60年昆明市气候变化特征分析[J]. 地理科学, 2012, 32(9): 1119-1124.
	[He Yunling, Lu Zhihai .Climate change trends and characteristics of Kunming in recent 60 years. Scientia Geographica Sinica, 2012, 32(9): 1119-1124.]
[23]	高翯, 王士君, 谭亮. 东北振兴以来吉林省区域经济差异的时空演变研究[J]. 地理科学, 2017, 37(11): 1712-1719.
	[Gao He, Wang Shijun, Tan Liang.Regional economic disparities and spatio-temporal evolution in Jilin Province since 2003. Scientia Geographica Sinica, 2017, 37(11): 1712-1719.]
[24]	姜会明, 孙雨, 王健,等 . 中国农民收入区域差异及影响因素分析[J]. 地理科学, 2017, 37(10): 1546-1551.
	[Jiang Huiming, Sun Yu, Wang Jian et al. Regional differences of farmers’ income in China and analysis of influencing factors. Scientia Geographica Sinica, 2017, 37(10): 1546-1551.]
[25]	陈妍, 梅林. 东北地区资源型城市经济转型发展波动特征与影响因素——基于面板数据模型的分析[J]. 地理科学, 2017, 37(7): 1080-1086.
	[Chen Yan, Mei Lin.Cyclical characteristics and influential factors of resource-based cities’ economy in Northeast China—Based on panel data model. Scientia Geographica Sinica, 2017, 37(7): 1080-1086.]

区域	省份	突变时间	线性回归方程	R²
北部沿海	山东	2005~2006	y = 71.629x-268.900	0.836
	河北	2005~2006	y = 48.68x- 157.210	0.840
	北京市	2005~2006	y = 28.558x-28.703	0.952
	天津市	2005~2006	y = 13.39x-27.413	0.854
东部沿海	江苏	2005~2006	y = 58.641x-235.590	0.840
	浙江	2005~2006	y = 55.337x-216.610	0.869
	上海市	2005~2006	y = 12.97x-14.588	0.936
黄河中游	河南	2005~2006	y = 43.877x-160.410	0.789
	山西	2005~2006	y = 22.067x- 61.320	0.874
	陕西	2005~2006	y = 19.795x-71.686	0.805
	内蒙	2005~2006	y = 18.035x- 60.807	0.853
西南	四川	2005~2006	y = 33.979x-106.200	0.827
	云南	2005~2006	y = 21.493x-56.431	0.841
	广西	2005~2006	y = 16.128x-57.086	0.803
	贵州	2005~2006	y = 12.337x-44.612	0.788
	重庆	2005~2006	y = 11.968x-42.849	0.809
南部沿海	广东	2005~2006	y = 69.319x-181.410	0.897
	福建	2005~2006	y = 20.412x-76.640	0.844
	海南	2008~2009	y = 3.6674x-9.8428	0.814
长江中游	安徽	2005~2006	y = 22.006x-79.384	0.821
	湖南	2005~2006	y = 21.823x-73.186	0.796
	湖北	2005~2006	y = 20.988x-64.700	0.803
	山西	2005~2006	y = 14.945x-57.502	0.800
东北	辽宁	2006~2007	y = 25.821x-56.724	0.848
	黑龙江	2006~2007	y = 15.974x-31.290	0.859
	吉林	2005~2006	y = 14.011x-36.674	0.836
西北	新疆	2005~2006	y = 13.009x-35.861	0.797
	甘肃	2006~2007	y = 9.3993x-32.537	0.742
	宁夏	2005~2006	y = 4.6055x-17.397	0.792
	青海	2006~2007	y = 3.3268x-10.517	0.767
	西藏	2005~2006	y = 1.4932x-3.2315	0.882

差异类型		泰尔指数均值	泰尔指数的M-K检验					2015年			贡献率M-K检验
差异类型		泰尔指数均值	倾向率	统计量	突变时间	趋势		泰尔指数	贡献率（%）		倾向率	统计量
T		0.0591	-0.0084	-4.72^***	2009~2015	↓		0.044	100		-	-
T_W		0.0516	-0.0025	-2.92^***	2013~2014	↓		0.034	57.1		0.0247	5.35^***
T_b		0.1106	-0.0057	-5.26^***	2008~2014	↓		0.010	42.9		-0.0247	3.67^***
T_k	东北	0.0104	0.0001	0.85	2007~2011	-		0.010	2.1		-0.00141	-1.39^*
	北部沿海	0.1432	-0.0174	-5.17^***	2008~2014	↓	0.143		7.0	-0.0203		-5.08^***
	东部沿海	0.0329	-0.0040	-4.00^***	2005~2015	↓	0.033		5.9	0.000565		2.74^***
	南部沿海	0.0265	-0.0032	-4.81^***	2009~2015	↓	0.026		1.5	-0.00232		-4.18^***
	黄河中游	0.0312	-0.0019	-2.56^***	2012~2015	↓	0.031		3.2	0.000419		0.85
	长江中游	0.0045	-0.0006	-4.27^***	2007~2008	↓	0.005		0.4	-0.00023		-2.83^***
	西南	0.0224	-0.0026	-4.90^***	2008~2009	↓	0.022		1.5	-0.0015		-4.45^***
	西北	0.0527	-0.0029	-4.45^***	2008~2009	↓	0.053		1.6	0.0001		0.49

单位根检验		1996~2005年				2006~2015年
	变量			检验方法
	变量	LLC	IPS	ADF-Fisher	PP-Fisher	LLC	IPS	ADF-Fisher	PP-Fisher
	lnX₁	4.23	5.18	11.82	16.46	1.88	4.93	10.78	7.55
	lnX₂	-8.15^***	0.40	65.24	28.24	-2.91^***	2.18	34.36	23.44
	lnX₃	-21.64^***	0.42	80.58^***	78.53^*	17.04	0.62	2.59	0.15
	lnY	8.66	5.14	5.14	6.37	2.44	3.06	29.44	33.11
	ΔlnX₁	-12.52^***	-1.41^*	99.78^***	240.85^***	-13.99^***	-0.96	85.45^**	131.09^***
	ΔlnX₂	-20.42^***	-2.89^***	139.54^***	213.77^***	-18.05^***	-1.91^**	107.16^***	135.30^***
	ΔlnX₃	-12.27^***	-1.02	88.80^**	161.36^***	-32.40^***	-3.56^***	141.17^***	173.82^***
	ΔlnY	-10.48^***	-5.58^***	157.35^***	204.70^***	-29.89^***	-4.27^***	162.89^***	83.85^**
协整检验		pedroni检验							Kao检验
	统计量时间	Panel v -Statistic	Panel rho -Statistic	Panel PP -Statistic	Panel ADF -Statistic	Group rho -Statistic	Group PP -Statistic	Group ADF Statistic	ADF
	1996~2005年	-3.91	3.39	-15.03^***	1.19	6.14	-20.95^***	-4.89^***	-2.88^***
	2006~2015年	-1.54	5.83	-5.06^***	-5.15^***	7.40	-13.53^***	-7.37^***	-4.48^***

时间	变量	全国及各省尺度	八大经济区域尺度
时间	变量	全国及各省尺度	Z₁	Z₂	Z₃	Z₄	Z₅	Z₆	Z₇	Z₈
1996~2005	R²	0.988	0.987	0.991	0.988	0.983	0.995	0.974	0.956	0.976
	F检验	74.27^***	19.75^***	55.18^***	92.46^***	7.73^***	165.32^***	46.21^***	3.62^**	2.86^*
	Huasman检验	10.22^***	89.87^***	10.30^***	277.38^***	23.19^***	-	138.63^***	-	-
	结论	①	①	①	①	①	①	①	②	②
	样本数	310	50	50	40	40	30	40	30	30
2006~2015	R²	0.994	0.980	0.991	0.989	0.990	0.999	0.983	0.995	0.985
	F检验	233.07^***	19.75^***	55.18^***	103.05^***	5.32^***	99.69^***	40.16^***	15.50^***	1.26
	Huasman检验	14.38^***	12.26^***	10.30^**	346.61^***	35.31^***	-	135.11^***	-	-
	结论	①	①	①	①	①	①	①	①	②
	样本数	310	50	50	40	40	30	40	30	30

经济快速发展背景下中国民用汽车拥有量变化的时空特征

Spatial-temporal Characteristics of Ownership Change of Civil Car in China

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 25

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	张子昂, 保继刚. 多重距离对中国入境与出境旅游流的影响:基于组态的视角[J]. 地理科学, 2021, 41(1): 13-21.
[2]	刘云刚, 刘玄宇, 张争胜. 渔民视角下中国南海的领域构建[J]. 地理科学, 2020, 40(7): 1062-1071.
[3]	夏函, 张万顺, 彭虹, 李琳, 黄攀攀, 夏晶晶. 基于主体功能区规划的中国城市化地区生态功能评估[J]. 地理科学, 2020, 40(6): 882-889.
[4]	罗小龙, 曹姝君, 顾宗倪. 回流城镇化：中部地区城镇化开启新路径[J]. 地理科学, 2020, 40(5): 685-690.
[5]	吴媛媛, 宋玉祥. 中国人口老龄化空间格局演变及其驱动因素[J]. 地理科学, 2020, 40(5): 768-775.
[6]	张新林, 仇方道, 谭俊涛, 王长建. 中国工业生态效率时空分异特征及其影响因素解析[J]. 地理科学, 2020, 40(3): 335-343.
[7]	姜洪强, 梅林, 杨立青. 中国淘宝店铺服务质量空间分异及影响因素[J]. 地理科学, 2020, 40(3): 428-436.
[8]	谭俊涛, 赵宏波, 刘文新, 张平宇, 仇方道. 中国区域经济韧性特征与影响因素分析[J]. 地理科学, 2020, 40(2): 173-181.
[9]	张向敏, 罗燊, 李星明, 李卓凡, 樊勇, 孙健武. 中国空气质量时空变化特征[J]. 地理科学, 2020, 40(2): 190-199.
[10]	汪凡, 汪明峰. 基于格网的淘宝村集聚特征及影响因素分析[J]. 地理科学, 2020, 40(2): 229-237.
[11]	湛东升, 虞晓芬, 吴倩倩, 金浩然, 张文忠. 中国租赁住房发展的区域差异与影响因素[J]. 地理科学, 2020, 40(12): 1990-1999.
[12]	李在军, 姜友雪, 秦兴方. 地方品质驱动新时期中国城市创新力时空演化[J]. 地理科学, 2020, 40(11): 1812-1821.
[13]	邹辉, 段学军. 中国化工产业布局演变与影响机理研究[J]. 地理科学, 2020, 40(10): 1646-1653.
[14]	张静, 吴洁, 秦公伟, 冯俊霄, 郑博, 赵文博. 秦巴山区地表太阳辐射的时空动态及农业气候区划研究[J]. 地理科学, 2020, 40(10): 1742-1752.
[15]	钟业喜, 郭卫东. 中国高铁网络结构特征及其组织模式[J]. 地理科学, 2020, 40(1): 79-88.