引用本文:孙丽璐, 陈甜, 赵娟, 吴奇, 赵辉.我国交通事故损失影响因素及地区特征分析——基于全国31个省市自治区2004-2015年面板数据[J].西南大学学报(自然科学版),2019,41(8):114~123
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我国交通事故损失影响因素及地区特征分析——基于全国31个省市自治区2004-2015年面板数据
孙丽璐, 陈甜, 赵娟, 吴奇, 赵辉1,2,3
1. 重庆理工大学 管理学院, 重庆 400054;2. 重庆理工大学 经济金融学院, 重庆 400054;3. 陆军军医大学 第三附属医院交通医学研究所, 重庆 400042
摘要:
近年来机动车总量和驾驶人员数量激增,人口流动频率加剧,人、车、路和环境矛盾凸显,而交通安全管理不足、事故应急系统不健全等问题,致使事故造成巨大经济损失,交通事故成为亟待解决的重大社会问题.此研究通过整理分析2004-2015年全国31个省市自治区交通相关指标面板数据,以汽车拥有量、交通投资、城市人口和交通事故死亡人数作为解释变量,进行回归和统计分析,探索各变量变化规律及其对交通事故直接财产损失的影响.结果表明:汽车拥有量、交通事故死亡人数、交通投资、城市人口与交通事故直接财产损失有显著相关性,其中汽车拥有量和城市人口与交通事故直接财产损失呈正相关,而交通死亡人数和交通投资呈负相关.我国不同地区的城市交通事故情况差异大,其中华东和中南地区交通事故情况复杂且更具特殊性,需要针对性进行预防和管理.
关键词:  交通事故  直接财产损失  面板数据  计量经济模型  地区性失衡
DOI:10.13718/j.cnki.xdzk.2019.08.017
分类号:U491.3
基金项目:国家重点研发计划项目(2016YFC0800702);国家自然科学基金项目(31470913);国家社会科学基金项目(2015XSH021);重庆市教委项目(16SKJD35,183065,yjg183113).
Analysis of the Influencing Factors of Traffic Accident Losses and Their Regional Features in China——A Study Based on the Panel Data of 31 Provinces from 2004 to 2015
SUN Li-lu, CHEN Tian, ZHAO Juan, WU Qi, ZHAO Hui1,2,3
1. School of Management, Chongqing University of Technology, Chongqing 400054, China;2. School of Economy and Finance, Chongqing University of Technology, Chongqing 400054, China;3. Institute of Traffic Medicine, the Third Affiliated Hospital of Army Medical University, Chongqing 400042, China
Abstract:
In recent years, the number of motor vehicles and drivers has surged, the frequency of population movements has intensified, and contradictions among people, cars, roads and the environment have become prominent. However, regional traffic safety management is inadequate and the accident emergency system is not perfect, resulting in huge economic losses. Traffic accidents have become a major social problem that needs to be solved urgently. This paper analyzes the panel data of traffic-related indicators of 31 provinces/municipalities in China from 2004 to 2015. taking car ownership, traffic investment, urban population and traffic accident deaths as the explanatory variables. Regression and statistical analyses are carried out to explore the changing laws of factors and their impact on the direct property losses of traffic accidents. The results show that direct property loss from traffic accidents is in a significant correlation with car ownership, death toll from traffic accidents, traffic investment and urban population. Car ownership and urban population are positively correlated with direct property loss from traffic accidents, while traffic death toll is negatively correlated with traffic investment. Urban traffic accidents vary greatly in different regions. Traffic accidents in East China and Central and South China are complicated and more special, which requires targeted prevention and management.
Key words:  traffic accident  direct property loss  panel data  econometric model  regional imbalance
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