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 analysis 、hypothetical extraction method 、risk disaster analysis 、economy disaster management 、spillover effects |
外文關鍵詞: | input-output analysis, hypothetical extraction method, risk disaster analysis, economy disaster management, spillover effects |
相關次數: | 點閱:178 下載:0 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
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.
A. Mukashov, Parameter uncertainty in policy planning models: Using portfolio management methods to choose optimal policies under world market volatility, Economic Analysis and Policy,Volume77,2023, Pages 187-202, ISSN 0313-5926, https://doi.org/10.1016/j.eap.2022.11.007.
Albala-Bertrand, Jose M. 2013. Disasters and the Networked Economy. Oxon, U.K.: Routledge.
Ali Y. 2015Measuring CO2 emission linkages with the hypothetical extraction method (HEM). Ecol. Indic. 54, 171–183. doi: doi:10.1016/j.ecolind.2015.02.021.
Annabi, Nabil & Cockburn, John & Decaluwe, Bernard. (2006). Functional Forms and Parametrization of CGE Models. SSRN Electronic Journal. 10.2139/ssrn.897758.
Arto, I., Andreoni, V., & Rueda Cantuche, J.M. (2015). Global Impacts of the Automotive Supply Chain Disruption Following the Japanese Earthquake of 2011. Economic Systems Research, 27, 306 - 323.
Baumol, William. 2000. “Leontief’s Great Leap Forward,” Economic Systems Research, 12, 141–152.
BNPB. (2010a). National Action Plan for Disaster Risk Reduction (NAP- DRR) 2010- 2012 Available from http://www.bnpb.go.id/website/file/pubnew/99.pdf
BNPB. (2017). Data Bencana Indonesia 2016. Center for Data, Information and Public Relations of the National Disaster Management Agency. (Indonesian)
Boisvert, R. (1992) Indirect losses from a catastrophic earthquake and local, regional, and national interest, in:Indirect Economic Consequences of a Catastrophic Earthquake, pp. 207 –265 (Washington, DC: National Earthquake Hazards Reduction Program, Federal Emergency Management Agency)
BPS. (2014). Statistik Indonesia [Statistical Yearbook of Indonesia] 2014. Jakarta, Badan Pusat Statistik. (Indonesian)
BPS. (2016). Indonesian Inter Regional Input-Output Table Domestic Transactions at Producer's Price By 6 Island Group and 17 Industrial Origin, 2016 (Million rupiah). Retrieved from: https://www.bps.go.id/statictable/2021/04/30/2124/tabel-inter-regional-input-output-indonesia-transaksi-domestik-atas-dasar-harga-produsen-menurut-6-kelompok-pulau-dan-17-lapangan-usaha-2016-juta-rupiah-.html
BPS. (2016a). Indonesian Inter Regional Input-Output Table Classification Concordance, 2016 (52 Industry - 17 Industrial Origin). Retrieved from: https://www.bps.go.id/statictable/2021/04/30/2119/konkordansi-klasifikasi-tabel-inter regional-input-output-indonesia-2016-52-industri-17-lapangan-usaha-.html
Cameron, M.J. (2003). The relationship between input-output (IO) analysis, social accounting matrices (SAM) and computable general equilibrium (CGE) models in a nutshell, Global Insight Southern Africa. (Unpublished).
Cochrane, H. C. (1997a) Economic Impact of a Midwest Earthquake. NCEER Bulletin, 11(1), pp 1-15.
Cochrane, H. C. (2004) Indirect Losses from Natural Disasters: Measurement and Myth, in: Y. Okuyama and S. E.Chang (eds) Modelling Spatial and Economic Impacts of Disasters, Springer-Verlag. Berlin Heidelberg New York.
Cochrane, H.C. (1974) Predicting the economic impacts of earthquakes, in: H.C. Cochrane, J.E. Haas and R.W.Kates (Eds) Social Science Perspectives on the Coming San Francisco Earthquakes—Economic Impact,Prediction, and Reconstruction, Natural Hazard Working Paper No.25 (Boulder, CO: University of Colorado, Institute of Behavioral Sciences).
Cole, S. (1998) Decision support for calamity preparedness: socioeconomic and interregional impacts, in:M. Shinozuka, A. Rose and R.T. Eguchi (Eds) Engineering and Socioeconomic Impacts of Earthquakes,pp. 125 –153 (Buffalo, NY: Multidisciplinary Center for Earthquake Engineering Research).
Dacy, D.C. and Kunreuther, H. (1969) The Economics of Natural Disasters (New York: The Free Press).
Dadek, T., Hermansyah, & Dinamika, Y. (2019). Rehabilitasi dan Rekonstruksi Gempa Pidie Jaya, Pidie, dan Bireuen. Aceh Government, Indonesian Disaster Managementand Authority. (Indonesian)
Dietzenbacher, Erik & Burken, Bob & Kondo, Yasushi. (2019). Hypothetical extractions from a global perspective. Economic Systems Research. 31.1-15.10.1080/09535314.2018.1564135.
Djohan, S., Hasid, Z., & Setyadi, D. (2016). Government Expenditure as Determinantsof Economic Growth and Income Inequality of Inter-Province of the Islands in Indonesia. Journal of economics and sustainable development, 7, 148-158.
Edmiston, K.D. & Thomas, M.X.(2004). The commercial musicindustry in Atlanta and the State of Georgia: an economic impact study,MEIEA Journal, 4(1): 61-82.
Faturay, Futu & Sun, Ya-Yen & Dietzenbacher, Erik & Malik, Arunima & Geschke, Arne & Lenzen, Manfred. (2019). Using virtual laboratories for disaster analysis – a case study of Taiwan. Economic Systems Research. 32. 1-26.10.1080/09535314.2019.1617677.
Felix K. Rioja. Productiveness and welfare implications of public infrastructure: a dynamic two-sector general equilibrium analysis. Journal of Development Economics, Volume58, Issue 2, 1999, Pages 387-404. ISSN 0304-3878, doi: https://doi.org/10.1016/S0304-3878(98)00118-7.
Gary R Webb, Kathleen J Tierney, and James M Dahlhamer. Predicting long-term business recovery from disaster: A comparison of the loma prieta earthquake and hurricane andrew. Global Environmental Change Part B: Environmental Hazards, 4(2):45–58, 2002
Ge and Lei Ge, Jianping & Lei, Yalin. (2017). Policy options for non-grain bioethanol in China: Insights from an economy-energy-environment CGE model. Energy Policy. 105. 502-511. 10.1016/j.enpol.2017.03.012.
Gordon, P. and Richardson, H.W. (1996). The Business Interruption Effects of the Northridge Earthquake (LuskCenter Research Institute, University of Southern California, Los Angeles, CA).
Hallegatte, S., 2008. An adaptive regional input–output model and its application to the assess-ment of the economic cost of Katrina, Risk Analysis 28, 779–799.
Han et al, 2022: Han, J.; Tan, Z.; Chen, M.; Zhao, L.; Yang, L.; Chen, S. Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis. Int. J. Environ. Res. Public Health 2022, 19, 11343. doi: https://doi.org/10.3390/ijerph191811343.
Hewings, G.J.D. and R. Mahidhara (1996) Economic Impacts: Lost Income, Ripple Effects, and Recovery. In: S.Changnon (ed.) The Great Flood of 1993. Boulder, CO, West View Press, 205–217.
Huang, R., Malik, A., Lenzen, M., Jin, Y., Wang, Y., Faturay, F., & Zhu, Z. (2021). Supply-chain impacts of Sichuan earthquake: a case study using disaster input– output analysis. Natural Hazards, 110, 2227-2248.
Huseyin, 1996. Retrieved from: https://www.staff.ncl.ac.uk/david.harvey/AEF873/Development/SAM.pdf (Unpublished paper).
Jim Lee. Business recovery from hurricane harvey. International Journal of Disaster Risk Reduction, 34:305–315, 2019.
Koks EE, Bočkarjova M, de Moel H, Aerts JCJH (2015a) Integrated direct and indirect flood risk modeling: development and sensitivity analysis. RISK ANAL 35:882–900.
Koks EE, Carrera L, Jonkeren O, Aerts JCJH, Husby TG, Thissen M, Standardi G, Mysiak J (2015b) Regional disaster impact analysis: comparing input-output and computable general equilibrium models. Natural Hazards and Earth System Sciences Discussions 3:7053–7088.
Koks, E. E. (2016). Economic modelling for flood risk assessment. [PhD-Thesis - Research and graduation internal, Vrije Universiteit Amsterdam].
Kondo and Nakamura (2004): Kondo, Y. and Nakamura, S. (2004) Evaluating alternative life-cycle strategies for electrical appliances by thewaste input–output model, International Journal of Life Cycle Assessment, 9, pp. 236–246.
Kowalewski, Julia (2009) : Methodology of the input-output analysis, HWWI Research Paper, No. 1-25.
Lenzen, Manfred & Malik, Arunima & Kenway, Steven & Daniels, Peter & Lam, Ka Leung & Geschke, Arne. (2018). Economic damage and spill-overs from a tropical cyclone. Natural Hazards and Earth System Sciences Discussions. 1-28.10.5194/nhess-2017-440.
Leontief, W. Input-output economics, Oxford University Press, USA, 1966.
Leontief, W. Quantitative input and output relations in the economic system of the United States, Review of Economics and Statistics, 18, 105-125, 1936.
Maik Budzinski, Alberto Bezama, Daniela Thrän. Estimating the potentials for reducing the impacts on climate change by increasing the cascade use and extending the lifetime of wood products in Germany, Resources, Conservation & Recycling: X, Volume 6, 2020, 100034, ISSN 2590-289X, doi: https://doi.org/10.1016/j.rcrx.2020.100034.
Mantell, N.H. (2005) Book Review of ‘Modeling Spatial and Economic Impacts of Disasters’, Journal ofRegional Science, 45, pp. 633– 635.
Maria I Marshall, Linda S Niehm, Sandra B Sydnor, and Holly L Schrank. Predicting small business demise after a natural disaster: an analysis of pre-existing conditions. Natural Hazards, 79(1):331–354, 2015.
Okuyama, Y. and Chang, S.E. (Eds) (2004a) Modeling Spatial and Economic Impacts of Disasters (New York:Springer).
Okuyama, Y., & Santos, J. R. (2014). DISASTER IMPACT AND INPUT–OUTPUT ANALYSIS.Economic Systems Research, 26(1), 1–12. https://doi.org/10.1080/09535314.2013.871505.
Okuyama, Yasuhide & Sahin, Sebnem. (2009). Impact Estimation of Disasters: A Global Aggregate for 1960 to 2007. 10.1596/1813-9450-4963.
Okuyama, Yasuhide, Geoffrey J.D. Hewings, and Michael Sonis, (1999) “Economic Impacts ofan Unscheduled, Disruptive Event: A Miyazaw a Multiplier Analysis,” in Geoffrey J.D.Hewings, Michael Sonis, Moss Madden, and Yoshio Kimura eds. Understanding andInterpreting Economic Structures, New York, NY; Springer-Verlag: pp. 113-144.
Okuyama, Yasuhide. (2007). Economic Modeling for Disaster Impact Analysis: Past, Present, and Future. Economic Systems Research. 19. 115-124. 10.1080/09535310701328435.
Oosterhaven, Jan & Bouwmeester, Maaike. (2016). A new approach to modeling the impact of disruptive events. Journal of Regional Science. 56. n/a-n/a. 10.1111/jors.12262.
Pelling, M.,A. Özerdem and S. Barakat (2002) The Macro-Economic Impact of Disasters. Progress in DevelopmentStudies, 2, 283–305.
Ratiranjan Jena, Biswajeet Pradhan, Ghassan Beydoun, Earthquake vulnerability assessment in Northern Sumatra province by using a multi- criteria decision-making model, International Journal of Disaster Risk Reduction, Volume 46, 2020, 101518, ISSN 2212-4209,retrieved from: https://doi.org/10.1016/j.ijdrr.2020.101518.
Rose A, Liao SY (2005) Modeling regional economic resilience to disasters: a computable general equilibrium analysis of water service disruptions. J Reg Sci 45:75–112.
Rose, A. (2004) Economic principles, issues, and research prioritiesin hazard loss estimation, in: Y. Okuyama and S.E. Chang (Eds)Modeling Spatial and Economic Impacts of Disasters, pp. 13-36(New York: Springer).
Rose, A., Benavides, J., Chang, S.E., Szczesniak, P. and Lim, D. (1997) The regional economic impact of anearthquake: direct and indirect effects of electricity lifeline disruptions, Journal of Regional Science, 37,pp. 437 –458.
Rossouw, R. & Saayman, M. (2011).Assimilation of tourism satelliteaccounts and applied general equilibrium models to inform tourism policy analysis, Tourism Economics,17(4):753-783.
Santos, J.R., Haimes, Y.Y., 2004. Modeling the demand reduction input-output (I-O) inoperability due to terrorism of interconnected infrastructures. Risk Analysis, 24, 1437–1451.
Steenge, Albert & Bockarjova, Marija. (2007). Thinking About Imbalances in Post-Catastrophe Economies: An Input-Output Based Proposition. Economic Systems Research. 19. 205-223. 10.1080/09535310701330308.
Subiyanti, Heni & Islam, Moinul & Ichihashi, Masaru. (2020). Recuperation of economy after volcanic eruption in Mt. Merapi, Indonesia: a multiregional input-output analysis. 10.21203/rs.3.rs-29358/v1.
Suh, Sangwon & Kagawa, Shigemi. (2005). Industrial ecology and input-output economics: An introduction. Economic Systems Research. 17. 349-364. 10.1080/09535310500283476.
Tan L, Wu, Xianhua & Guo, Ji. (2019). Comprehensive Economic Loss Assessment of Disaster Based on CGE Model and IO model—A Case Study on Beijing “7.21 Rainstorm”. 10.1007/978-981-16-1319-7_4.
The indirect economic effects of a terrorist attack on transport infrastructure: a proposal for a SAGE, Disaster Prev. Manag., 13, 315–322, 2004.
Tian, Kailan & Zhang, Zhuoying & Zhu, Lingxiu & Yang, Cuihong & He, Jianwu & Li, Shantong. (2022). Economic exposure to regional value chain disruptions: evidence from Wuhan’s lockdown in China. Regional Studies. 1-12. 10.1080/00343404.2022.2078802.
Tsuchiya, S., Tatano, H., & Okada, N. (2007). Economic Loss Assessment due to Railroad and Highway Disruptions. Economic Systems Research, 19, 147 - 162.
West, C.T. and Lenze, D.G. (1994) Modeling the regional impact of natural disaster and recovery: a generalframework and an application to hurricane Andrew, International Regional Science Review, 17, pp. 121–150.
Wilson, R. (1982) Earthquake Vulnerability Analysis for Economic Impact Assessment (Washington, DC:Information Resources Management Office, Federal Emergency Management Agency)
World Bank Group. (2021, November 23). How Indonesia strengthened its disaster response with Risk Finance and insurance. World Bank. Retrieved January 22, 2023, from https://www.worldbank.org/en/news/feature/2021/11/17/how-indonesia-strengthened-its-disaster-response-with-risk-finance-and-insurance
Wyk, Lukas & Saayman, Melville & Rossouw, R.. (2015). CGE or SAM? Ensuring quality information for decision-making.. African Journal of Hospitality Tourism and Leisure. 4. 1-20.
Wyk, Lukas & Saayman, Melville & Rossouw, Riaan & Saayman, Andrea. (2015). Regional economic impacts of events: A comparison of methods. South African Journal of Economic and Management Sciences. 18. 155-176. 10.17159/2222-3436/2015/v18n2a2.
Xia Y, Guan D, Steenge AE, Dietzenbacher E, Meng J, Mendoza TD (2019) Assessing the economic impacts of it service shutdown during the York flood of 2015 in the UK. Proc Roy Soc A Math Phys Eng Sci 475(2224):20180871.