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Using virtual laboratories for disaster analysis – a case study of Taiwan

Author

Listed:
  • Futu Faturay
  • Ya-Yen Sun
  • Erik Dietzenbacher
  • Arunima Malik
  • Arne Geschke
  • Manfred Lenzen

Abstract

Due to its geographic location, Taiwan frequently experiences severe natural disasters (for example earthquakes and typhoons) that significantly interrupt business operations and subsequently cause extensive financial losses. Prior work on economic losses resulting from such natural disasters in Taiwan has not considered regional and sectoral spillover effects. In this work, we estimate the economic impacts resulting from the 1999 Chichi earthquake, the 2009 typhoon Morakot, the 2016 Tainan earthquake, and the 2016 typhoon Megi. We do so in the new TaiwanLab, a collaborative virtual laboratory that is capable of generating a time-series of subnational multiregional input–output (MRIO) tables, capturing interregional transactions among 267 sectors across Taiwan’s 22 city-counties. We identify critical economic sectors in regions of high vulnerability to natural disasters. Our research is, thus, a credible reference to decision-making that determines regional and sectoral prioritisation for damage mitigation, improved resiliency, and faster recovery schedules.

Suggested Citation

  • Futu Faturay & Ya-Yen Sun & Erik Dietzenbacher & Arunima Malik & Arne Geschke & Manfred Lenzen, 2020. "Using virtual laboratories for disaster analysis – a case study of Taiwan," Economic Systems Research, Taylor & Francis Journals, vol. 32(1), pages 58-83, January.
    • Handle: RePEc:taf:ecsysr:v:32:y:2020:i:1:p:58-83
    DOI: 10.1080/09535314.2019.1617677
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    Cited by:

    1. Hanspeter Wieland & Manfred Lenzen & Arne Geschke & Jacob Fry & Dominik Wiedenhofer & Nina Eisenmenger & Johannes Schenk & Stefan Giljum, 2022. "The PIOLab: Building global physical input–output tables in a virtual laboratory," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 683-703, June.
    2. Venkata Sai Gargeya Vunnava & Jaewoo Shin & Lan Zhao & Shweta Singh, 2022. "PIOT‐Hub ‐ A collaborative cloud tool for generation of physical input–output tables using mechanistic engineering models," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 107-120, February.
    3. Kuik, Onno & Zhou, Fujin & Ciullo, Alessio & Brusselaers, Jan, 2022. "How vulnerable is Europe to severe climate-related natural disasters abroad? A dynamic CGE analysis of the international financial and economic impacts of a large hurricane in the southern USA," Conference papers 333438, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    4. Balakrishnan, Srijith & Lim, Taehoon & Zhang, Zhanmin, 2022. "A methodology for evaluating the economic risks of hurricane-related disruptions to port operations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 58-79.
    5. Jacob Fry & Arne Geschke & Sarah Langdon & Manfred Lenzen & Mengyu Li & Arunima Malik & Ya‐Yen Sun & Thomas Wiedmann, 2022. "Creating multi‐scale nested MRIO tables for linking localized impacts to global consumption drivers," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 281-293, February.

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