An Economic Loss Estimation On Agricultural Natural Disaster Based On Input-Output Model

Agricultural flood is an important natural constraint affecting the sustainable development of China’s agriculture. Agricultural disaster damage assessment can provide decision support conditions for the development of agriculture. Traditional agricultural damage assessment focuses on the direct economic loss assessment, but the indirect economic losses of agricultural disaster assessment is vacant. However, for major natural disasters, due to the rapid increase of the size of the economy, the correlation between the economic systems division enhances indirect economic loss, which is often more than the direct economic loss. Indirect losses grow in a non-linear growth path. Thus, the direct damage assessment for natural disaster losses. The loss estimation report can not summarize the entire contents of the losses caused by disasters and not be a scientific basis for disaster mitigation and preparedness policy formulation.This dissertation is built on the Inoperability Input-Output Model(IIM),which is an extension to the original Nobel-Prize winning Leontief Input-Output(I-O)model. The IIM transforms the I-O model to an inoperability form so that the ripple effects of an initial perturbation caused by disaster or perturbation caused by disaster or attacks can be calculated. A dynamic extension to the IIM is introduced in this dissertation. The Dynamic Inoperability Input-Output Model(DIIM)incorporates the concept of industry resilience coefficient to measure the pace of recovery for each industry sector on the event of an attack. With the DIIM, the recovery paths of the economic sectors are described as functions of time. Inoperability, economic loss, and cumulative economic loss of any sector can be calculated based on the DIIM. The conclusions are as following:(1)In terms of floods direct economic losses, relatively light or mild loss were in Northwest region, middle loss region appeared in Southeast Region and the Bohai Rim, more serious loss region was in the central region and the Northeast region.(2) Direct losses spatially correlated with indirect losses, there was a non-linear relationship between direct losses and indirect economic losses, the greater the direct economic losses, the greater the indirect economic losses. (3) Loss of sector distribution, chemical industry and electric power, steam and hot water, gas water production and supply special loss were different from the other part of the loss.(4) Disaster damage assessment considered both the loss of absolute and relative amount. Absolute loss was both interrelated and independent of the relative loss rate. The department suffered from larger relative loss rate was not those department suffered from larger the absolute loss values, vice versa.(5) Different economic sectors recovered as a various paths. Disaster recovery capabilities and disaster recovery time significantly affected the size of the post-disaster economic loss. The formulation of mitigation policies should consider increasing economic resilience and reduce disaster time.(6) Optimization path based on the final product loss minimization was different from that based on final demand minimization. Disaster mitigation strategies needed to be developed considering the different optimization goals.The main impact of the research is its contribution to the assessment of indirect economic loss from natural disasters through the creation and application of input-output model (IO model) and its extensions (ⅡM and DIIM).IO model and its extensive models can be used to compare the paradigm of relative economic and absolute economic loss, which can be the base of mitigation disaster establishment. The integration of LP and10can be used to optimize the total flood economic loss. The methodology can be extended to other natural disaster mitigation strategies formulation.