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研究生: Junita Dian Angelina
Junita Dian Angelina
論文名稱: 多區域投入產出分析探究天然災害的經濟衝擊: 以印尼地震及淹水事件為例
Measuring Economic Impacts of Disasters with Multi-regional Input-output Analysis: Comparison of Disasters in Indonesia
指導教授: 洪嫦闈
Chang-Wei Hung
口試委員: 詹瀅潔
Ying-Chieh Chan
楊亦東
I-Tung Yang
鄭明淵
Min-Yuan Cheng
學位類別: 碩士
Master
系所名稱: 工程學院 - 營建工程系
Department of Civil and Construction Engineering
論文出版年: 2023
畢業學年度: 111
語文別: 英文
論文頁數: 104
中文關鍵詞: input-output analysishypothetical extraction methodrisk disaster analysiseconomy disaster managementspillover effects
外文關鍵詞: input-output analysis, hypothetical extraction method, risk disaster analysis, economy disaster management, spillover effects
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  • Indonesia is the biggest archipelago country located in the Pacific Ocean that consists of more than 17,000 islands around the equator lines. However, the unintegrated infrastructure built in the entire region in Indonesia caused a huge economic gap that led to 60% of the entire country’s economy relying on production in Java island. Not only that, Indonesia is situated on the ring of fire. As a combined result of the imbalanced economic structure and its geographical location, the country is prone to both natural and man-made disasters, which result in significant financial and non-financial damages. The economic loss reported in journals and news reflect the amount of money worth the damage due to the disaster, but did not portray indirect loss or spillover to the rest of the non-directly affected regions due to supply chain activity. The identification of both direct and indirect loss are critical since there are economic transactions in between all regions and are linked together as documented in the Multi Regional Input Output table. In this research, data of production loss caused by the disaster were processed into an Input Output table through the partial Hypothetical Extraction Method to quantify the entire loss experienced after the disaster. Further research will include the total loss after substitution through import between regions. The result shows that total loss in each case presented was higher than the official report due to supply chain loss. Due to the findings, recommendations of policy were raised to help the government disburse the rehabilitation funding to areas outside originated disaster region and create efficient measures to minimize financial loss of disaster in the future.


    Indonesia is the biggest archipelago country located in the Pacific Ocean that consists of more than 17,000 islands around the equator lines. However, the unintegrated infrastructure built in the entire region in Indonesia caused a huge economic gap that led to 60% of the entire country’s economy relying on production in Java island. Not only that, Indonesia is situated on the ring of fire. As a combined result of the imbalanced economic structure and its geographical location, the country is prone to both natural and man-made disasters, which result in significant financial and non-financial damages. The economic loss reported in journals and news reflect the amount of money worth the damage due to the disaster, but did not portray indirect loss or spillover to the rest of the non-directly affected regions due to supply chain activity. The identification of both direct and indirect loss are critical since there are economic transactions in between all regions and are linked together as documented in the Multi Regional Input Output table. In this research, data of production loss caused by the disaster were processed into an Input Output table through the partial Hypothetical Extraction Method to quantify the entire loss experienced after the disaster. Further research will include the total loss after substitution through import between regions. The result shows that total loss in each case presented was higher than the official report due to supply chain loss. Due to the findings, recommendations of policy were raised to help the government disburse the rehabilitation funding to areas outside originated disaster region and create efficient measures to minimize financial loss of disaster in the future.

    ABSTRACT i ACKNOWLEDGEMENT ii TABLE OF CONTENTS iii LIST OF TABLES vii LIST OF FIGURES viii ABBREVIATIONS AND SYMBOLS xi CHAPTER 1 INTRODUCTION 1 1.1. Research Background 1 1.2. Research Objectives 5 1.3. Importance of Study 5 1.4. Scope of Study 6 CHAPTER 2 LITERATURE REVIEW 8 2.1. History of Disaster EIA 8 2.2. Disaster Impact Modelling 10 2.3. Common Disaster Economic Impact Analysis 11 2.3.1. IO Analysis 11 2.3.2 Computational General Equilibrium (CGE) 15 2.3.3 Social Accounting Matrix (SAM) 17 2.4. Summary of Literature Review  18 CHAPTER 3 METHODOLOGY 19 3.1. Introduction 19 3.1.1. Economic Structure of Aceh 20 3.1.2. Economic Structure of West Java 25 3.2. Flow Chart of the Study 30 3.3. Data Acquisition 30 3.4. Data Acquisition 32 3.4.1. Initial Post Disaster Economic Loss 32 3.4.2. MRIO Mix Model of Standard Impact after Initial Output Reduction 35 3.4.3. MRIO Models for Backward Impact due to Supply Chain 40 Finally, the total output loss for the whole sectors in different regions will be computed as the total loss due to direct and indirect loss. 42 3.4.4. MRIO Models for Substitution 42 CHAPTER 4 RESULT AND DISCUSSION 45 4.1. Case 1: Aceh Earthquake 45 4.1.1. Standard Backward Impact after Aceh Earthquake 47 4.1.2. Supply Chain Disruption Impact after Aceh Earthquake 50 4.2. Case 2: West Java Flash Floods 52 4.2.1. Standard Backward Impact after West Java Flash Flood 54 4.2.2. Supply Chain Disruption Impact after West Java Flash Flood 57 4.3. Comparison Between 2 Regions 59 4.3.1. Standard Backward Impact Comparison after Disaster 59 4.3.2. Supply Chain Disruption Impact after Disaster 61 4.4. Production Layer Decomposition 64 4.4.1. Regional Spillover 65 4.4.2. Sectoral Spillover 67 4.5. Economic condition after substitutions 70 4.5.1. Aceh earthquake substitutions 70 4.5.2. West Java flash flood substitutions 72 4.6. Value Added loss (Change in GDP) 74 4.6.1. Value added changes before substitution 74 4.6.2. Value added changes after substitutions 76 4.7. Comparison with previous studies 78 4.8. Construction sector economic condition 79 4.8.1. Importance of construction sector to the economy 79 4.8.2. After substitutions 81 4.9. Policy recommendation 83 CHAPTER 5 CONCLUCION 85 5.1. Conclusion 85 5.2. Limitations and Future Work 87  REFERENCES 89 APPENDIX 94 A. Concordance of regions and sectors 94 A.1 List of regions (Based on Indonesia Bureau Statistics) – according to 6 Big Islands 94 A.2 List of Regions – (Based on Indonesia Bureau Statistics) – according to 34 Province 94 A.3 List of sectors (Based on Indonesia Bureau Statistics) – according to 17 business fields 95 A.4 List of sectors (Based on Indonesia Bureau Statistics) – according to 52 goods and products 95 B. Before Substitution 97 B.1 Production loss before substitution (in million US$) 97 B.1.1 Production loss due to Aceh earthquake before substitution (in million US$) 97 B.1.2 Production loss due to West Java flash flood before substitution (in million US$) 98 B.2 Value added loss before substitution (in million US$) 99 B.2.2 Value added loss due to West Java flash flood before substitution (in million US$) 100 B.2.3 Loss due to partially shutted construction sector after Aceh earthquake 2016 before substitution (in million US$) 101 C. After Substitution 103 C.1 Overall loss due to Aceh earthquake before substitution (in million US$) 103 C.2 Overall loss due to West Java flash flood after substitution (in million US$) 104

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