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Probabilistic Modeling of the Economic Impact of Earthquakes at the Regional Level

Pakizeh, Amir Hossein | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52762 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Haj Kazem Kashani, Hamed
  7. Abstract:
  8. Earthquakes can cause significant economic damage to society. These damages include direct economic damage, ie, the cost incurred by the community to rebuild damaged infrastructure. In addition, damaging the infrastructure, the earthquake reduces the level of infrastructure service, and thus, disrupts the businesses that rely on it. The consequences of such disruptions, such as a decline in the level of productivity and efficiency of firms, or an increase in the rate of unemployment and migration from the community, can cause indirect economic damage to society. The costs incurred to society by disasters can be reduced by adopting appropriate solutions. In many cases, however, the incentives to reduce the vulnerability of the community to earthquakes fail against the non-working option. The reason for this is disregarding the great benefits of reducing indirect economic losses against the cost of vulnerability mitigation. In this study, a probabilistic framework is presented to investigate the economic consequences imposed on a community by earthquake. In this framework, regional input-output tables and the amount of initial damages to the structural, non-structural and inventory parts of infrastructures utilized in businesses are used as input into the model. In addition, non-survey methods have been used to regionalize the input-output tables by considering the number of jobs and population of each economic sector. To this end, as an alternative approach where data on the input-output table is available in at least one region of the nation, the application of machine learning algorithms for regionalization of national tables is proposed. The results of this approach showed better accuracy compared to the output of non-survey methods in studying the nine regions of Japan. On the other hand, the extent of damage to community infrastructure is probabilistically estimated using a risk analysis model, considering the magnitude of the potential earthquakes in the future. The proposed economic model simulates the interaction between economic sectors during the post-earthquake recovery period using information on input-output tables and damages to infrastructure, as well as considering the production capacity and adaptive behavior of different economic sectors. One of the most important sectors of the economy is the construction industry. Responding the post-earthquake demand surge properly, this industry can recover the economic activities of the society by rebuilding its infrastructure. Using the framework presented, the impact of construction industry on the recovery of economic activities can be examined. To evaluate the capabilities of the proposed framework, the economic consequences of the earthquake in a virtual community are investigated using the proposed framework. In this study, sensitivity analysis was performed on different magnitudes of earthquakes. The modeling results show that the amount of indirect costs caused by the earthquake is directly and nonlinearly associated with increasing magnitude of the earthquake. In general, the proposed framework can be used in evaluating and selecting policies to reduce vulnerability and increase earthquake preparedness, as well as resource allocation policies to recover from the earthquake
  9. Keywords:
  10. Risk Analysis ; Damage ; Earthquake ; Machine Learning ; Economic Modeling Framework ; Input-Output Tables

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