Advertisement

Advantages of the Regional and Sectoral Disaggregation of a Spatial Computable General Equilibrium Model for the Economic Impact Analysis of Natural Disasters

  • Yoshio KajitaniEmail author
  • Hirokazu Tatano
Chapter
Part of the Advances in Spatial Science book series (ADVSPATIAL)

Abstract

Computable general equilibrium (CGE) models are promising for estimating the economic losses of natural disasters. This type of model has a sound theoretical foundation and can explain both forward and backward linkages in an economy; hence, it is suitable for predicting the economic impact of supply and demand shocks during a disaster. Spatial and sector classifications for the CGE model are key elements that affect the performance of the model. Although physical damage to an area by a hazard is local, the damage induces higher-order effects on flows that can spread to other areas, and constructing the CGE model on a fine spatial scale is necessary for describing these effects. Sectoral disaggregation would also improve the quality of the model if key industries that have low substitutability and cause supply chain impacts are separated from other sectors with higher substitutability. This study validates the spatial and sectoral disaggregation effects of the CGE model through a case study of the Great East Japan Earthquake and Tsunami in 2011. In addition, this study examines whether two patterns of the elasticity of substitution parameters for interregional trade contribute to improving the forecasting capability of the CGE model.

Notes

Acknowledgements

We would like to thank the editors and two anonymous reviewers for their constructive comments. We also acknowledge Taylor and Francis and the International Input-Output Association because this chapter is derived in part from an article published in Economic Systems Research (28 Sep 2017, copyright: International Input-Output Association, available online: http://www.tandfonline.com/doi/full/10.1080/09535314.2017.1369010).

References

  1. Atkeson A, Kahoe PJ (1999) Models of energy use: putty-putty versus putty-clay. Am Econ Rev 89:1028–1043CrossRefGoogle Scholar
  2. Badri NG, Walmsley TL (2008) Global trade, assistance, and production: the GTAP 7 Data Base. Center for Global Trade Analysis, Purdue UniversityGoogle Scholar
  3. Bourguignon F, Michel G, Miqueu D (1983) Short-run rigidities and long-run adjustments in a computable general equilibrium model of income distribution and development. J Dev Econ 13:21–43CrossRefGoogle Scholar
  4. Dixon PB, Jorgenson D (eds) (2013) Handbook of computable general equilibrium modeling, Vols. 1A and 1B, Handbooks in economics. North-Holland, AmsterdamGoogle Scholar
  5. Greenberg MR, Lahr M, Mantell N (2007) Understanding the economic costs and benefits of catastrophes and their aftermath: a review and suggestions for the U.S. Federal Government. Risk Anal 27:83–96CrossRefGoogle Scholar
  6. Hertel TW (ed) (1997) Global trade analysis: modeling and applications. Cambridge University Press, New YorkGoogle Scholar
  7. Ichioka O (1991) Applied general equilibrium analysis. Yuhikaku, Tokyo. (In Japanese)Google Scholar
  8. Kajitani Y, Tatano H (2014) Estimation of production capacity loss rate after the Great East Japan earthquake and Tsunami in 2011. Econ Syst Res 26(1):13–38CrossRefGoogle Scholar
  9. Kajitani Y, Tatano H (2018) Applicability of a spatial computable general equilibrium model to assess the short-term economic impact of natural disasters. Econ Syst Res 30(3):289–312CrossRefGoogle Scholar
  10. Koike A, Ito K, Nakao T (2012) Estimation of Armington elasticities in Japan. J Jpn Soc Civil Eng 68:55–61. In JapaneseGoogle Scholar
  11. Ministry of Economy, Trade and Industry (METI) (2010) 2005 Interregional input-output table. http://www.meti.go.jp/statistics/tyo/tiikiio/result/result_02.html (In Japanese). Accessed 22 Sept 2014
  12. Miyagi T, Ishikawa Y, Yuri S, Tsuchiya K (2003) The construction of interregional input-output table at prefecture level using intraregional input-output tables. Infrastruct Plann Rev 20(1):87–95. In JapaneseCrossRefGoogle Scholar
  13. Okuyama Y, Hewings GJD, Sonis M (2004) Measuring economic impacts of disasters: interregional input-output analysis using sequential interindustry model. In: Okuyama Y, Chang SE (eds) Modeling spatial and economic impacts of disasters. Springer, New York, pp 77–101CrossRefGoogle Scholar
  14. Oosterhaven J, Bouwmeester MC (2016) A new approach to modeling the impact of disruptive events. J Reg Sci 56(4):583–595CrossRefGoogle Scholar
  15. Partridge MD, Rickman DS (1998) Regional computable general equilibrium modeling: a survey and critical appraisal. Int Reg Sci Rev 21(3):205–248CrossRefGoogle Scholar
  16. Rose A, Guha G (2004) Computable general equilibrium modeling of electric utility lifeline losses. In: Okuyama Y, Chang SE (eds) Modeling spatial and economic impacts of disasters. Springer, New York, pp 119–141CrossRefGoogle Scholar
  17. Rose A, Liao S (2005) Modeling regional economic resilience to disasters: a computable general equilibrium analysis of water service disruptions. J Reg Sci 45:75–112CrossRefGoogle Scholar
  18. Shoven JB, Whalley J (1992) Applying general equilibrium. Cambridge University Press, Cambridge, UKGoogle Scholar
  19. Tatano H, Tsuchiya S (2008) A framework for economic loss estimation due to seismic transportation network disruption: a spatial computable general equilibrium approach. Nat Hazard 44:253–265CrossRefGoogle Scholar
  20. Taylor L, Lysy FJ (1979) Vanishing income redistributions: Keynesian clues about model surprises in the short run. J Dev Econ 6:11–29CrossRefGoogle Scholar
  21. Ueda T (ed) (2010) Regional and urban economics analysis with excel. Corona, Tokyo. (In Japanese)Google Scholar
  22. Wilcoxon F (1945) Individual comparisons by ranking methods. Biometrics Bull 1(6):80–83CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Engineering and DesignKagawa UniversityTakamatsuJapan
  2. 2.Disaster Prevention Research InstituteKyoto UniversityUjiJapan

Personalised recommendations