恐怖袭击事件的时空差异特征分析及内生性VAR模型
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- 英文论文题名：Spatial-temporal Difference Analysis of Terrorist Attacks and Endogeneity based on VAR Model
- 论文作者：柴瑞瑞 ; 刘德海 ; 陈静锋
- 英文论文作者：CHAI Rui-rui ; LIU De-hai ; CHEN Jing-feng ; School of Management Science and Engineering ; Dongbei University of Finance and Economics ; Institute of Systems Engineering ; Dalian University of Technology
- 年：2016
- 作者机构：东北财经大学管理科学与工程学院;大连理工大学系统工程研究所;
- 论文关键词：恐怖袭击 ; 时空差异 ; 核密度估计 ; VAR模型 ; 脉冲响应
- 英文论文关键词：terrorist attacks ; spatial-temporal difference ; Kernel density ; VAR model ; impulse response
- 会议召开时间：2016-11-12
- 会议录名称：第十八届中国管理科学学术年会论文集
- 英文会议录名称：Proceedings of the 18th Chinese Annual Conference on Management Science
- 语种：中文
- 分类号：D815.5
- 学会代码：ZHYJ
- 会议名称：第十八届中国管理科学学术年会
- 会议地点：中国陕西西安
- 主办单位：中国优选法统筹法与经济数学研究会、西安交通大学、中国科学院科技战略咨询研究院、《中国管理科学》编辑部
- 学会名称：中国优选法统筹法与经济数学研究会
- 页数：8
- 文件大小：1144k
- 原文格式：O
- 会议级别：全国
摘要
当前恐怖主义已成为影响国家稳定和地区安全的首要威胁,并呈现出不断蔓延之势。以恐怖袭击次数为样本点,采用核密度估计对1989—2014年31个省份恐怖袭击事件分布进行时空格局演变分析,恐怖活动呈现出显著的时空差异特征。并考虑恐怖分子袭击行为策略、政府反恐行为策略及事件惨重性的动态关系,运用VAR模型,构建了政府反恐财政支出、恐怖分子袭击次数、恐怖分子袭击成功次数、死亡人数间相互内在联系系统,着重探讨恐怖分子行为策略波动、事件惨重性的波动对政府反恐财政支出的影响规律和政府反恐财政支出波动对恐怖分子行为策略、事件惨重性的影响规律。研究结果表明,恐怖袭击次数增加导致政府反恐财政支出增加;政府反恐财政支出增加对减小恐怖袭击次数存在滞后效应。通过分析政府和恐怖分子的策略选择内生性动态关系,可以为我国反恐战略的部署提供理论指导。
Current terrorism has become the primary threat to national stability and regional security,simultaneously presented a trend of constantly spread.Taking the number of terrorist attacks as sample points,the kernel density estimation is used and spatial-temporal pattern evolution of terrorist attacks of 31 provinces from 1989 to 2014 is analyzed.Terrorist activities show significant spatial-temporal difference.Considering the dynamic relationship among the terrorist attacks,the government anti-terrorist acts and event severity,the VAR model is applied to construct the endogenous relationship among the government anti-terrorism fiscal expenditure,the number of terrorist attacks,the number of terrorist successful attacks and number of fatality.Emphatically,the effect of terrorist acts fluctuation and number of fatality fluctuation on the government anti-terrorism fiscal expenditure and the impact of the government anti-terrorism fiscal expenditure fluctuation on terrorist acts and number of fatality are discussed.The results show that the increases in the number of terrorist attacks lead to an increase in the government anti-terrorism fiscal expenditure.Conversely,the government anti-terrorism fiscal expenditure has a lag effect on reducing the number of terrorist attacks.Through the analysis of dynamic relationship between the government and terrorist,it can provide theoretical guidance for the deployment of anti-terrorism strategy.
Current terrorism has become the primary threat to national stability and regional security,simultaneously presented a trend of constantly spread.Taking the number of terrorist attacks as sample points,the kernel density estimation is used and spatial-temporal pattern evolution of terrorist attacks of 31 provinces from 1989 to 2014 is analyzed.Terrorist activities show significant spatial-temporal difference.Considering the dynamic relationship among the terrorist attacks,the government anti-terrorist acts and event severity,the VAR model is applied to construct the endogenous relationship among the government anti-terrorism fiscal expenditure,the number of terrorist attacks,the number of terrorist successful attacks and number of fatality.Emphatically,the effect of terrorist acts fluctuation and number of fatality fluctuation on the government anti-terrorism fiscal expenditure and the impact of the government anti-terrorism fiscal expenditure fluctuation on terrorist acts and number of fatality are discussed.The results show that the increases in the number of terrorist attacks lead to an increase in the government anti-terrorism fiscal expenditure.Conversely,the government anti-terrorism fiscal expenditure has a lag effect on reducing the number of terrorist attacks.Through the analysis of dynamic relationship between the government and terrorist,it can provide theoretical guidance for the deployment of anti-terrorism strategy.
引文
[1]吴合琴.中国国家安全蓝皮书引关注,全球面临反恐新形势[EB/OL].[2014-05-07].www.chinanews.com/hb/201 4/05-07/6142603.shtml.
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[3]Zhuang Jun.Bier V M.Balancing terrorism and natural disasters defensive strategy with endogenous attacker effort[J].Operational Research,2007,55(5):976-991.
[4]Zhuang Jun.Bier V M,Alagoz O.Modeling secrecy and deception in a multiple-period attacker-defender signaling game[J].European Journal of Operational Research,2009,203(2):409-418.
[5]Shan Xiaojun J,Zhuang Jun.Hybrid defensive resource allocations in the face of partially strategic attackers in a sequential defender-attacker game[J].European Journal of Operational Research,2013,228(1):262-272.
[6]Patterson S A,Apostolakis G E.Identification of critical locations across multiple infrastructures for terrorist actions[J].Reliability Engineering and System Safety,2006,92(9):1183-1023.
[7]柴瑞瑞,孙康,陈静锋,等.连续恐怖袭击下反恐设施选址与资源调度优化模型及其应用[J].系统工程理论与实践,2016,36(2):464-472.
[8]Bier V M,Oliveros S,Samuelson L.Choosing what to protect:Strategic defense allocation against an unknown attacker[J].Journal of Public Economic Theory,2007,9(4):563-587.
[9]刘德海,周婷婷,王维国.反恐国际合作双重标准问题的序贯互惠博弈模型[J].中国管理科学,2015,(S1):301-309.
[10]Ressler S.Social network analysis as an approach to combat terrorism:Past,present,and future research[J].Homeland Security Affairs,2006,2(2):1-10.
[11]Bohannon J.Counter-terrorism's new tool:'Metanetwork'analysis[J].Science,2009,325(405):409-411.
[12]付举磊,孙多勇,肖进,等.基于社会网络分析理论的恐怖组织网络研究综述[J].系统工程理论与实践,2013,33(9):2177-2186.
[13]刘德海,周婷婷.基于认知差异的恐怖主义袭击误对策分析[J].系统工程理论与实践,2015,35(10):2646-2655
[14]LaFree G,Dugan L,Xie Min,et al.Spatial and temporal patterns of terrorists attacks by ETA 1970 to 2007[J].Journal of Quantitative Criminology,2012,28(1):7-29.
[15]Wang X iaoyu,Miller E,Smarick K,et al.Investigative visual analysis of global terrorism[J].Computer Graphics Forum,2008,27(3):919-926.
[16]Krisztina K K,Helge L,G(u|¨)nther G S.On the origin of domestic and international terrorism[J].European Journal of Political Economy,2011,27(SI):S17-S36.
[17]Borooah V K.Terrorist incidents inlndia,1998 2004:A quantitative analysis of fatality rates[J].Terrorism&Political Violence,2009,21:476-498.
[18]蒋天颖.浙江省区域创新产出空间分异特征及成因[J].地理研究,2014,33(10):1825-1836.
[19]高铁梅.计量经济分析方法与建模Eviews应用及实例[M].北京:清华大学出版社,2006.
[20]吴振信,薛冰,王书平.基于VAR模型的油价波动对我国经济影响分析[J].中国管理科学,2011,19(1):21-28.
[21]谢赤,屈敏,王纲金.基于M-Coupula_GJR-VAR模型的黄金市场最优套期保值比率研究[J].管理科学,2013,26(2):90-99.
[22]Clauset A,Young M.Scale invariance in global terrorism[EB/OL].(2005-05-01)[2012-01-10].http://xxx.lanl.gov/abs/physics/0502014.
[23]庄呈展.中国并不是一个恐怖主义事件多发的国家[EB/OL].[2014-3-10].http://www.qstheory.cn/gj/gjsdfx/201403/t20140310_328751.htm.
[24]危黎黎,向书坚.我国工业增加值季节波动非线性研究—基于SEATV-STAR模型[J].中国管理科学,2016,24(4):10-18.
[25]姚登宝,刘晓星,张旭.市场流动性与市场预期的动态相关结构研究[J].中国管理科学,2016,24(2):1-10.
[2]李健和,王存奎,梅建明,等.当代恐怖主义的特征与发展趋势[J].中国人民公安大学学报(社会科学版),2008,(3):1-7.
[3]Zhuang Jun.Bier V M.Balancing terrorism and natural disasters defensive strategy with endogenous attacker effort[J].Operational Research,2007,55(5):976-991.
[4]Zhuang Jun.Bier V M,Alagoz O.Modeling secrecy and deception in a multiple-period attacker-defender signaling game[J].European Journal of Operational Research,2009,203(2):409-418.
[5]Shan Xiaojun J,Zhuang Jun.Hybrid defensive resource allocations in the face of partially strategic attackers in a sequential defender-attacker game[J].European Journal of Operational Research,2013,228(1):262-272.
[6]Patterson S A,Apostolakis G E.Identification of critical locations across multiple infrastructures for terrorist actions[J].Reliability Engineering and System Safety,2006,92(9):1183-1023.
[7]柴瑞瑞,孙康,陈静锋,等.连续恐怖袭击下反恐设施选址与资源调度优化模型及其应用[J].系统工程理论与实践,2016,36(2):464-472.
[8]Bier V M,Oliveros S,Samuelson L.Choosing what to protect:Strategic defense allocation against an unknown attacker[J].Journal of Public Economic Theory,2007,9(4):563-587.
[9]刘德海,周婷婷,王维国.反恐国际合作双重标准问题的序贯互惠博弈模型[J].中国管理科学,2015,(S1):301-309.
[10]Ressler S.Social network analysis as an approach to combat terrorism:Past,present,and future research[J].Homeland Security Affairs,2006,2(2):1-10.
[11]Bohannon J.Counter-terrorism's new tool:'Metanetwork'analysis[J].Science,2009,325(405):409-411.
[12]付举磊,孙多勇,肖进,等.基于社会网络分析理论的恐怖组织网络研究综述[J].系统工程理论与实践,2013,33(9):2177-2186.
[13]刘德海,周婷婷.基于认知差异的恐怖主义袭击误对策分析[J].系统工程理论与实践,2015,35(10):2646-2655
[14]LaFree G,Dugan L,Xie Min,et al.Spatial and temporal patterns of terrorists attacks by ETA 1970 to 2007[J].Journal of Quantitative Criminology,2012,28(1):7-29.
[15]Wang X iaoyu,Miller E,Smarick K,et al.Investigative visual analysis of global terrorism[J].Computer Graphics Forum,2008,27(3):919-926.
[16]Krisztina K K,Helge L,G(u|¨)nther G S.On the origin of domestic and international terrorism[J].European Journal of Political Economy,2011,27(SI):S17-S36.
[17]Borooah V K.Terrorist incidents inlndia,1998 2004:A quantitative analysis of fatality rates[J].Terrorism&Political Violence,2009,21:476-498.
[18]蒋天颖.浙江省区域创新产出空间分异特征及成因[J].地理研究,2014,33(10):1825-1836.
[19]高铁梅.计量经济分析方法与建模Eviews应用及实例[M].北京:清华大学出版社,2006.
[20]吴振信,薛冰,王书平.基于VAR模型的油价波动对我国经济影响分析[J].中国管理科学,2011,19(1):21-28.
[21]谢赤,屈敏,王纲金.基于M-Coupula_GJR-VAR模型的黄金市场最优套期保值比率研究[J].管理科学,2013,26(2):90-99.
[22]Clauset A,Young M.Scale invariance in global terrorism[EB/OL].(2005-05-01)[2012-01-10].http://xxx.lanl.gov/abs/physics/0502014.
[23]庄呈展.中国并不是一个恐怖主义事件多发的国家[EB/OL].[2014-3-10].http://www.qstheory.cn/gj/gjsdfx/201403/t20140310_328751.htm.
[24]危黎黎,向书坚.我国工业增加值季节波动非线性研究—基于SEATV-STAR模型[J].中国管理科学,2016,24(4):10-18.
[25]姚登宝,刘晓星,张旭.市场流动性与市场预期的动态相关结构研究[J].中国管理科学,2016,24(2):1-10.
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