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

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.

KEYWORDS:

• Disaster
• Taiwan
• multiregional input–output analysis
• MRIO
• virtual laboratory

Acknowledgements

The authors thank Pei-Wen Syu for help with collecting data for the TaiwanLab. We also thank an anonymous referee for providing insight that is identified in footnotes 2–4.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Futu Faturay http://orcid.org/0000-0001-5636-1794

Arunima Malik http://orcid.org/0000-0002-4630-9869

Arne Geschke http://orcid.org/0000-0001-9193-5829

Manfred Lenzen http://orcid.org/0000-0002-0828-5288

Notes

1 Based on a collaboration between the University of Sydney in Australia and the National Cheng Kung University in Taiwan.

2 Oosterhaven and Többen (2017) show in an IO context that full capacity utilisation leads to substantially higher indirect disaster impacts. A similar finding was reported by Hallegatte and Ghil (2008) using a systems time-series macroeconomic model.

3 In the context of underutilised capacities, excess demand (households can consume less than desired due to the disaster) and prices fixed (as always in the quantity IO model), maximising output implies profit maximisation.

4 Natural disasters can yield positive impacts to regions or sectors that are not directly affected (cf. Carrera et al., 2015; Koks and Thissen, 2016; Oosterhaven and Többen, 2017).

Additional information

Funding

This work was financially supported by the Indonesia Endowment Fund for Education (Lembaga Pengelola Dana Pendidikan/LPDP) [grant number PRJ-1491/LPDP/2014], Ministry of Science and Technology of Taiwan [grant number 105-2410-H-006 -055 -MY3], National eResearch Collaboration Tools and Resources project (NeCTAR) through its Industrial Ecology Virtual Laboratory, and Australian Research Council (ARC) through its Discovery Projects DP0985522 and DP130101293. IELab infrastructure is supported by ARC infrastructure funding through project LE160100066.