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
Part of the Advances in Spatial Science book series (ADVSPATIAL)


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.



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:


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

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

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