台风“艾云尼”动态间接经济损失评估
|
摘要
基于广东省2015年投入产出表,通过投入产出模型评估了2018年台风"艾云尼"对广东省造成的间接经济损失的动态变化及其对主要经济部门的影响。结果显示,台风"艾云尼"造成广东省间接经济损失为5. 51亿元,约占直接经济损失的22%,总经济损失达到31. 01亿元,占广东省2018年第二季度GDP的0. 12%。受台风影响的高敏感部门是①农林牧渔业、②水利、环境和公共设施管理业以及③交通运输、仓储和邮电业。虽然此次台风未对金融保险、房地产、商务和旅游业部门造成直接经济损失,但是由于广东省完善的产业链以及不断增强的集群效应,这些部门受到的间接经济损失的总额约为1. 28亿元。通过参数敏感性分析表明,灾后部门最大超额生产能力和灾后部门生产能力提高到最大值所需时间是影响灾后恢复重建进度的两个重要指标。综上所述,综合考虑直接和间接经济损失,根据不同部门灾后恢复的模拟结果,充分解析间接经济损失在灾害恢复过程中的动态变化。
Typhoon"Ewiniar"is the first typhoon that landed in China in 2018 and causes serious disasters in Guangdong,Fujian,Jiangxi,Hunan and Hainan. The direct economic loss of Guangdong was about 2550 million yuan,which exceeds the sum of other affected areas,and its indirect losses should be taken seriously. Based on the input-output table of Guangdong in 2015,this paper evaluates the dynamic changes of the indirect economic losses caused by Typhoon "Ewiniar"to Guangdong Province and its impact on major economic sectors through the inputoutput model. The results show that the typhoon "Ewiniar"causes an indirect economic loss of 551 million yuan in Guangdong,accounting for 22% of the direct economic losses,which means that the total economic loss reached3101 million yuan,accounting for 0. 12% of the second quarter GDP of Guangdong in 2018. The highly sensitive sectors affected by the typhoon are ①agriculture,forestry,animal husbandry and fishery,②water conservancy,environmental and public facilities management,and ③transportation,warehousing and post and telecommunications industries. Although this typhoon does not cause direct economic losses to the financial insurance,real estate,business and tourism sectors,due to the improved industrial chain and the increasing cluster effect in Guangdong,the total indirect economic losses of these sectors amounted to approximately 128 million. Through parameter sensitivity analysis,it is shown that the maximum overproduction capacity and the overproduction capacity characteristic times are two important indicators that affect the progress of post-disaster recovery and reconstruction. In summary,comprehensive consideration of direct and indirect economic losses is helpful to fully analyze the dynamic changes of indirect economic losses in the process of disaster recovery.
Typhoon"Ewiniar"is the first typhoon that landed in China in 2018 and causes serious disasters in Guangdong,Fujian,Jiangxi,Hunan and Hainan. The direct economic loss of Guangdong was about 2550 million yuan,which exceeds the sum of other affected areas,and its indirect losses should be taken seriously. Based on the input-output table of Guangdong in 2015,this paper evaluates the dynamic changes of the indirect economic losses caused by Typhoon "Ewiniar"to Guangdong Province and its impact on major economic sectors through the inputoutput model. The results show that the typhoon "Ewiniar"causes an indirect economic loss of 551 million yuan in Guangdong,accounting for 22% of the direct economic losses,which means that the total economic loss reached3101 million yuan,accounting for 0. 12% of the second quarter GDP of Guangdong in 2018. The highly sensitive sectors affected by the typhoon are ①agriculture,forestry,animal husbandry and fishery,②water conservancy,environmental and public facilities management,and ③transportation,warehousing and post and telecommunications industries. Although this typhoon does not cause direct economic losses to the financial insurance,real estate,business and tourism sectors,due to the improved industrial chain and the increasing cluster effect in Guangdong,the total indirect economic losses of these sectors amounted to approximately 128 million. Through parameter sensitivity analysis,it is shown that the maximum overproduction capacity and the overproduction capacity characteristic times are two important indicators that affect the progress of post-disaster recovery and reconstruction. In summary,comprehensive consideration of direct and indirect economic losses is helpful to fully analyze the dynamic changes of indirect economic losses in the process of disaster recovery.
引文
[1]中华人民共和国应急管理部. 2018年前三季度全国自然灾害基本情况[EB/OL].(2018-10-15)[2019-02-01].http://www. chinasafety. gov. cn/xxfbpt/zrzh/201901/t20190108_223847. shtml.
[2]中华人民共和国水利部. 2017中国水旱灾害公报[EB/OL].(2018-08-06)[2018-11-01]. http://www. mwr. gov. cn/sj/tjgb/zgshzhgb/201808/t20180806_1044770. html.
[3] Hallegatte S. An adaptive regional input-output model and its application to the assessment of the economic cost of Katrina[J].Risk Analysis,2008,28(3):779-799.
[4] ECLAC. Handbook for Estimating the Socio-economic and Environment Effects of Disaster[R]. Mexico City:ECLAC,2003.
[5]中华人民共和国民政部国家减灾委员会办公室.特别重大自然灾害损失统计制度[EB/OL].(2016-07-11)[2018-11-1].http://www. gdqy. gov. cn/0107/200/201607/90b0b57b346b46c096 49c7784617d4f9. shtml.
[6] ECLAC and IDB(Inter-America Development Bank). A matter of Development:How to Reduce Vulnerability in the Face of Natural Disasters[R]. Mexico:ECLAC-IDB,2000.
[7] Leontief W.“The dynamic inverse,”in Carter A. P. and Brody A. eds. Contributions to Input-Output Analysis[M]. Amsterdam:North-Holland Publishing,1970:17-46.
[8] Cochrane H. Economic loss:myth and measurement[J]. Disaster Prevention&Management,2004,13(4):290-296.
[9] Okuyama Y,Hewings G J D,Sonis M. Measuring economic impacts of disasters:Interregional input-output analysis using sequential interindustry model[J]. Advance in Spatial Science,2004,77-101.
[10]张正涛,李宁,冯介玲,等.从重建资金与效率角度定量评估灾后经济恢复力的变化[J].灾害学,2018,33(4):211-216.
[11] Rose A. Input-output economics and computable general equilibrium models[J]. Structural Change&Economic Dynamics,1995,6(3):295-304.
[12]吴吉东.基于适应投入产出模型的四川省汶川地震间接经济损失评估[D].北京:北京师范大学. 2012
[13]国家统计局国民经济核算司. 2015年广东省投入产出延长表[M].北京:中国统计出版社,2015.
[14] Hall R E,Jones C I. Why do some countries produce so much more output per worker than others?[J]. Quarterly Journal of Economics,1991,114(1):83-115.
[15]谢群,潘玉君.中国内地各省区1952-2009年实物资本存量估算[J].当代经济,2011(1):122-128.
[16]广东省统计局.广东统计年鉴-2016[M].北京:中国统计出版社,2017.
[17]广东省人民政府.广东省供给侧结构性改革总体方案(2016-2018年)[EB/OL].(2016-6-28)[2018-11-01]. http://zwgk. gd. gov. cn/006939748/201707/t20170711_712 865. html
[2]中华人民共和国水利部. 2017中国水旱灾害公报[EB/OL].(2018-08-06)[2018-11-01]. http://www. mwr. gov. cn/sj/tjgb/zgshzhgb/201808/t20180806_1044770. html.
[3] Hallegatte S. An adaptive regional input-output model and its application to the assessment of the economic cost of Katrina[J].Risk Analysis,2008,28(3):779-799.
[4] ECLAC. Handbook for Estimating the Socio-economic and Environment Effects of Disaster[R]. Mexico City:ECLAC,2003.
[5]中华人民共和国民政部国家减灾委员会办公室.特别重大自然灾害损失统计制度[EB/OL].(2016-07-11)[2018-11-1].http://www. gdqy. gov. cn/0107/200/201607/90b0b57b346b46c096 49c7784617d4f9. shtml.
[6] ECLAC and IDB(Inter-America Development Bank). A matter of Development:How to Reduce Vulnerability in the Face of Natural Disasters[R]. Mexico:ECLAC-IDB,2000.
[7] Leontief W.“The dynamic inverse,”in Carter A. P. and Brody A. eds. Contributions to Input-Output Analysis[M]. Amsterdam:North-Holland Publishing,1970:17-46.
[8] Cochrane H. Economic loss:myth and measurement[J]. Disaster Prevention&Management,2004,13(4):290-296.
[9] Okuyama Y,Hewings G J D,Sonis M. Measuring economic impacts of disasters:Interregional input-output analysis using sequential interindustry model[J]. Advance in Spatial Science,2004,77-101.
[10]张正涛,李宁,冯介玲,等.从重建资金与效率角度定量评估灾后经济恢复力的变化[J].灾害学,2018,33(4):211-216.
[11] Rose A. Input-output economics and computable general equilibrium models[J]. Structural Change&Economic Dynamics,1995,6(3):295-304.
[12]吴吉东.基于适应投入产出模型的四川省汶川地震间接经济损失评估[D].北京:北京师范大学. 2012
[13]国家统计局国民经济核算司. 2015年广东省投入产出延长表[M].北京:中国统计出版社,2015.
[14] Hall R E,Jones C I. Why do some countries produce so much more output per worker than others?[J]. Quarterly Journal of Economics,1991,114(1):83-115.
[15]谢群,潘玉君.中国内地各省区1952-2009年实物资本存量估算[J].当代经济,2011(1):122-128.
[16]广东省统计局.广东统计年鉴-2016[M].北京:中国统计出版社,2017.
[17]广东省人民政府.广东省供给侧结构性改革总体方案(2016-2018年)[EB/OL].(2016-6-28)[2018-11-01]. http://zwgk. gd. gov. cn/006939748/201707/t20170711_712 865. html