Production Recovery of Fishery and Seafood Manufacturing After the Disaster in Japan: Economic Evaluation Using Dynamic CGE Model

  • Yuko AkuneEmail author
Part of the New Frontiers in Regional Science: Asian Perspectives book series (NFRSASIPER, volume 11)


The purpose of this chapter is to evaluate the economic effects of the recovery of fishery and seafood manufacturing after the disaster in Japan under depopulation by employing a dynamic Computable General Equilibrium (CGE) model. We confirmed a clear contrast between the production recovery of seafood manufacturers in Iwate and Miyagi Prefectures after the Great East Japanese Earthquake (GEJE) of 2011. The economic evaluation involves setting up simulation scenarios based on actual recovery evidence after GEJE. The results of five simulations indicated the following five points. (1) The disaster accelerated problems caused by depopulation. (2) Prompt capital restoration and production recovery contributed to shortening the period of output loss. (3) The degree of output recovery of the downstream industry was faster than that of the upstream industry. (4) No scenario based on GEJE evidence was sufficient to reach base scenario without disaster. (5) Stepwise production recoveries contributed to increases not only in specific industries but also economic welfare in the long term.


Production recovery Fish food system Geographic concentration Great East Japan Earthquake Dynamic CGE model 


  1. Akune Y, Okiyama M, Tokunaga S (2013) Evaluation of the restoration of fisheries and seafood manufacturers after the Great East Japan Earthquake: economic analysis utilizing a dynamic computable general equilibrium model, RIETI Political Discussion Paper, 13-P-022Google Scholar
  2. Akune Y, Okiyama M, Tokunaga S (2015) Economic evaluation of dissemination of high temperature-tolerant rice in Japan using a dynamic computable general equilibrium model. Jpn Agric Res Q 49(2):127–133CrossRefGoogle Scholar
  3. Anselin L, Syabri I, Smiirnov O (2002) Visualizing multivariate spatial correlation with dynamically linked windows, REAL 02-T-8Google Scholar
  4. Armington PS (1969) A theory of demand for products distinguished by place of production. Staff Pap Int Monet Fund 16(1):159–178CrossRefGoogle Scholar
  5. Ellison G, Glaeser EL (1997) Geographic concentration in U.S. manufacturing industries: a dartboard approach. J Polit Econ 105:889–927CrossRefGoogle Scholar
  6. Fujita M et al (1999) The spatial economy: cities, regions, and international trade. MIT Press, Cambridge, MAGoogle Scholar
  7. Hallegtte S, Prsyluski V (2010) The economics of natural disaster: concepts and methods. Policy research working paper 5507. World Bank, doi:
  8. Huang MC, Hosoe N (2016) Computable general equilibrium assessment of a compound disaster in northern Taiwan. Rev Urban Reg Dev Stud 28(2):89–106CrossRefGoogle Scholar
  9. Krugman P (1991) Geography and trade. MIT Press, Cambridge, MAGoogle Scholar
  10. Moran PAP (1950) A test for the serial dependence of residuals. Biometrika 37:178–181Google Scholar
  11. Porter ME (1998) On competition. Harvard Business School Press, BostonGoogle Scholar
  12. Rose A, Liao SY (2005) Modeling regional economic resilience to disasters: a computable general equilibrium analysis of water service disruptions. J Reg Sci 45:75–112CrossRefGoogle Scholar
  13. Shibusawa H, Yamaguchi M, Miyata Y (2009) Evaluating the impacts of a disaster in the Tokai region of Japan: a dynamic spatial CGE model approach. Stud Reg Sci 39(3):539–551CrossRefGoogle Scholar
  14. Tohoku Bureau of Economy, Trade and Industry (2016) Report of society for regional revitalization by seafood processing in the affected regions (Suisan Kakougyou wo Syutai to shita Hisaiti ni okeru Tiiki Kasseika Kennkyuukai Torimatome Houkokusyo). (in Japanese)
  15. Tokunaga S, Okiyama M, Akune Y (2013) Analyses of disrupted supply chains by the Great East Japan Earthquake and reconstruction of the disaster-affected region by the cluster of the automotive industry: utilizing the regional CGE model, RIETI Discussion Paper Series 13-J-068Google Scholar
  16. Tokyo University of Marine Science and Technology (2014) Research on recovery of fisheries and seafood manufacturing from the Great East Japan Earthquake: evidence in third year since the disaster, (Higashi-Nihon-Daisinsai kara no Suisangyou oyobi Kanren Sangyou no Fukkou Taisaku ni kakaru Kenkyu: Daisinsai kara no 3 nen me no Genti no Fukkyu-Fukkou Jyoukyou). (in Japanese)
  17. Tsuchiya S, Tatano H, Okada N (2007) Economic loss assessment due to railroad and highway disruptions. Econ Syst Res 19(2):147–162CrossRefGoogle Scholar
  18. Wartenberg D (1985) Multivariate spatial correlation: a method for exploratory geographical analysis. Geogr Anal 17(4):263–283CrossRefGoogle Scholar

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© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Faculty of Economics and Business AdministrationReitaku UniversityKashiwaJapan

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