台风灾害间接损失评估模型中劳动力参数研究

A Study of the Labor Parameter in the Model of Indirect Economic Loss in Typhoon Disaster

为进一步研究自然灾害间接损失模型中受灾劳动力参数问题,调查了“山竹”台风严重影响的广州市和深圳市的劳动力受灾情况.基于实地调研的845份问卷调查数据,分析了受灾劳动力部门分布、影响时长以及恢复路径的实际情况,并与灾害间接损失前沿评估模型(AMIL模型)中的理论假设参数进行对比.研究结果表明:(1)从受灾劳动力所属部门来看,信息传输、软件和信息技术服务业、制造业、金融业、建筑业、批发零售业5个部门的实际受灾劳动力较多,而AMIL模型假设低估了信息传输、软件和信息技术服务业、金融业、建筑业等14个部门的劳动力受灾情况;(2)从恢复时间来看,所有劳动力实际恢复工作的时间是台风过后的第4天,远少于AMIL模型设置的时间;(3)从恢复路径来看,综合劳动力恢复路径呈先快后慢的趋势,幂函数对该路径的拟合效果较好,与AMIL模型假设的双曲正切函数曲线不符;(4)广州市劳动力受台风影响情况比深圳市的更加严重,且恢复速度较慢.研究表明:AMIL模型中对劳动力所属部门假设和劳动力灾后动态恢复路径的函数设置与选择方面存在进一步调整修正的空间.

A survey on labor force losses in Guangzhou and Shenzhen during the typhoon Mangkhut was conducted in order to study the parameter of the affected labor force in the indirect loss model of natural disasters.Based on the data of 845 questionnaires,the three parameters of sector of the affected labor,recovery time and recovery path were analyzed.They were also compared with the assumed parameters in the AMIL model,a model for frontier assessment of indirect disaster loss.The following results were obtained.First,in terms of the sector of labor force affected by the disaster,five sectors(information transmission,software and information technology services,manufacturing,finance,construction,and wholesale and retail)had the most labor force affected.The AMIL model’s assumptions understated the impact on the workforce in 14 sectors,such as information transmission,software and information technology services,finance and construction.Second,on the 4th day after the typhoon,all labor had recovered,and the recovery time was far less than the assumed time of the AMIL model.Third,the labor recovery path showed a trend of being first fast and then slow.The power function had a good fitting effect on the recovery path,which was different from the hyperbolic tangent function curve assumed by the AMIL model.Fourth,the labor force in Guangzhou was more seriously affected by typhoon disaster than that in Shenzhen and the labor force reco-very rate was slower.The AMIL model still has room for improvement in the function setting and selection of the dynamic recovery path of labor force after a disaster.