Impact estimation of flooding in Manila: An inoperability input-output approach

Natural disasters cause unexpected disruptions to the flow of goods and services in an economy. These disruptions may affect production in a single sector but sector interdependence guarantees that this will trickle down to other sectors, leading to increased damages. This study seeks to provide an...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Yu, Krista Danielle S., Tan, Raymond Girard R., Santos, Joost R.
التنسيق: text
منشور في: Animo Repository 2013
الموضوعات:
الوصول للمادة أونلاين:https://animorepository.dlsu.edu.ph/faculty_research/141
https://animorepository.dlsu.edu.ph/context/faculty_research/article/1140/type/native/viewcontent
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المؤسسة: De La Salle University
الوصف
الملخص:Natural disasters cause unexpected disruptions to the flow of goods and services in an economy. These disruptions may affect production in a single sector but sector interdependence guarantees that this will trickle down to other sectors, leading to increased damages. This study seeks to provide an estimate of the impact of a disruption in the transportation sector in the largest island in the Philippines and its ripple effects. Through the inoperability input-output model (IIM), the degree of failure in a system can be quantified on a scale from 0 (normal state) to 1 (complete failure). Inoperability is initially measured for the transportation sector based on estimates from the World Bank coupled with region-specific input-output data to forecast the ripple effects to other sectors in the economy. Aside from inoperability, economic loss is also assessed. Sensitivity analysis is implemented to capture the uncertainties relating to varying magnitudes of transportation disruptions and associated recovery horizons. Results show that the sectors that were strongly affected, both in terms of inoperability and economic loss are mainly manufacturing, agriculture and private services. Nevertheless, slight divergence in other sectors may be observed. While this study focuses on a static estimation, dynamic extensions introducing time-varying perturbations on the transportation, and multi-sector disruptions may be explored. © 2013 IEEE.