摘要
为解决灾后重建资金在各产业间合理分配的问题,基于ARIO模型构建了灾后区域经济模拟模型,设置了均衡投入、高贡献产业优先、灾损弥补与高贡献产业优先相结合共3种重建资金分配方案,并以湖北省2016年洪灾为例,分析了重建资金分配对灾后区域经济恢复时间的影响。结果表明:区域经济从受到灾害冲击到恢复灾前平衡状态,历经生产骤减损失不断扩大、生产快速回到灾前生产水平、生产持续增加、生产回到灾前的平衡状态4个阶段;灾后区域经济恢复时间与重建资金呈指数关系,随着重建资金投入的增加,灾后经济恢复时间不断减少,但减少的幅度逐渐降低;将重建资金首先用于弥补灾害造成的经济损失,而后分配在对国民经济贡献较大的产业,能在保障民生的前提下提高灾后重建效率。
Allocation of reconstruction funds among various industrial sectors affects regional disaster economic recovery capacity.In this study,a post-disaster economic recovery simulation model based on Adaptive Regional Input Output Model(ARIO)was established.And then three reconstruction funds allocation plans were set:“balanced investment”,“high-contribution industry priority”,and“disaster damage and high contribution industry combined”.Finally,Hubei province was taken as an example,and the economic recovery period after flood disaster in 2016 was simulated.The results show that:After disaster,the production added value is reduced,the investment of the reconstruction fund make the production return back to pre-disaster level,and then the production continues to increase until the demand for reconstruction is completely satisfied,finally,the production is gradually declined,the economy is returned to the pre-disaster equilibrium.Post-disaster economic recovery time and reconstruction funds are index relationship,and the recovery time of floods is constantly shortened with increased increasing funds after the disaster,but the rate of economic recovery time is decreasing.The reconstruction fund should first used to compensate for the economic losses caused by disasters,and then allocate fund to high-contribution industries,which can improve post-disaster reconstruction efficiency under the premise of protecting people’s livelihood.
作者
刘高峰
宁思雨
王慧敏
LIU Gaofeng;NING Siyu;WANG Huimin(Business School,Hohai University,Nanjing 211100,China;Management Science Institute,Hohai University,Nanjing 211100,China)
出处
《水利经济》
2023年第4期82-87,101,105,106,共9页
Journal of Economics of Water Resources
基金
国家自然科学基金面上项目(72174054,42171081)
国家自然科学基金重大研究计划重点项目(9184620)。