Abstract
Regionally disaggregated Computable General Equilibrium (CGE) models, namely spatial CGE (SCGE) models, have the potential to estimate high-order disaster impacts over a wide region. However, the validation of SCGE models based on actual disasters has begun to be addressed in the literature. This chapter aims to illustrate the SCGE simulation results for the Great East Japan Earthquake and the 2000 Tokai Heavy Rain, whose production capacity losses were estimated in the previous chapter. Throughout this paper, the current forecasting capability and applicability of models are discussed, focusing on short-run settings and key parameters, such as the elasticity of substitution for interregional trade. In the case study, the 9-region version was employed for the Great East Japan Earthquake case, while the 47-region version was considered for the Tokai Heavy Rain, as in the latter case, the area directly affected by the inundation was limited.
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Notes
- 1.
The multiregional CGE model is identical to the SCGE model.
- 2.
The effects of regional and sectoral disaggregation in an SCGE model are deeply investigated in Kajitani and Tatano (2019). It is likely that both regional and sectoral disaggregation improve forecasting capability.
- 3.
- 4.
For an example, see Romanoff and Levine (1986).
- 5.
- 6.
The technological tree (sometimes referred to as a “nesting structure” or “production hierarchy”) is similar to the model presented in chapter Economic Impacts of a Nankai Megathrust Earthquake Scenario” except that export and import rates can be fixed or not. In addition, the supply and demand conditions are slightly different (e.g., intermediate and final demands might be balanced separately or pooled in one equation and balanced by total supply). The influence of such a difference might be negligible, but needs to be explored in future studies.
- 7.
The redistribution of income across regions can stem from policies such as tax and social security spending.
- 8.
\(X_{i}^{r}\) is a composite of domestic and imported goods as in Fig. 1.
- 9.
Putty-clay models assume different substitutability of production factors before and after the capital is installed, with substitutability usually being zero for clay. On the other hand, putty-putty models assume substitutability both before and after and often the same level of substitutability.
- 10.
All effects are negative because of the assumption that factors’ endowments are fully utilized (thus, maximum production is achieved) and unchangeable across regions and sectors. However, some of the sectors in non-damaged regions actually benefit from a disaster. This phenomenon can be understood by considering an idle capacity before a disaster, but the degree of such idle capacity should be further explored.
- 11.
More investigations are needed, but models at a finer spatial scale may require higher substitution parameter values depending on distances from the disaster hit area if production outsourcing occurs at a closer distance.
- 12.
The exchange rate of 106 yen/$ is applied to the data for the year 2000.
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Acknowledgements
This chapter contents are partly derived from an article published in Economic Systems Research (09 Jan 2014, copyright: International Input-Output Association, available online at: http://www.tandfonline.com/doi/full/10.1080/09535314.2017.1369010) and a book chapter in “Advances in Spatial and Economic Modeling of Disaster Impacts” (Okuyama and Rose eds), Springer Nature Switzerland AG.
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Kajitani, Y., Tatano, H. (2022). SCGE Models to Assess Higher-Order Impacts of Production Capacity Losses. In: Tatano, H., Kajitani, Y. (eds) Methodologies for Estimating the Economic Impacts of Natural Disasters. Integrated Disaster Risk Management. Springer, Singapore. https://doi.org/10.1007/978-981-16-2719-4_4
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