Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

How shaky was the regional economy after the 1995 Kobe earthquake? A multiplicative decomposition analysis of disaster impact

Abstract

The long-run effects of the 1995 Kobe earthquake have been studied in various papers (Chang in Disasters 34(2):303–327, 2010; DuPont and Noy in Econ Dev Cult Change, 2015; Okuyama in Singap Econ Rev, 2015), and their findings have revealed the continuous and significantly negative economic trend in Kobe, suggesting that considerable structural changes occurred in the Kobe economy resulting from the damages from and subsequent reconstruction activities after the earthquake. At the same time, Fujiki and Hsiao (Disentangling the effects of multiple treatments—measuring the net economic impact of the 1995 Great Hanshin-Awaji Earthquake. IMES Discussion Paper 2013-E-3. Institute for Monetary and Economic Studies, Bank of Japan, 2013) concluded that the effects from the event were only short-lived and the persistent decline of the Hyogo economy had come from structural change of the economy. In order to investigate the disaster-induced structural changes further, this paper aimed to analyze the extent to and the composition of the structural change, based on the input–output framework. While the previous study (Okuyama in Econ Syst Res 26(1):98–117, 2014) lacked the 1995 data and was inclined toward a longer-run analysis, this paper examined immediate structural changes after the event employing the estimated 1995 input–output tables for the damaged region based on the observed macroeconomic data and with a set of different assumptions (Ashiya and Jinushi in Kokumin Keizai Zasshi 183(1):79–97, 2001). The results show that the significant structural changes were observed in the damaged region and that many manufacturing sectors tightened the regional interindustry linkages, whereas service sectors weakened their regional linkages in the aftermath. In addition, the assumptions of how the reconstruction demands would have been leaked out appear to make some critical differences in the results.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Notes

  1. 1.

    Since their studies include only econometric analysis, which cannot distinguish or derive higher-order effects, and they did not include those studies using the models estimating the higher-order effects, such as input–output, social accounting matrix, or computable general equilibrium models, their result of insignificant total losses should be treated carefully.

  2. 2.

    Toyoda (2006) also estimated the long-run effects of the Kobe earthquake using a simple trend analysis without providing the details.

  3. 3.

    These input–output tables are estimated for respective calendar year, while the Japanese fiscal year runs from April of a particular year to March in the next year. In this way, the 1995 tables include the earthquake and 1 year of response and recovery activities.

  4. 4.

    These include the cities of Kobe, Amagasaki, Akashi, Nishinomiya, Sumoto, Ashiya, Itami, Takarazuka, Miki, and Kawanishi, and the towns of Tsuna, Awaji, Hokudan, Tsuna-gun Ichinomiya, Goshiki, Higashiura, Midori, Seidan, Mihara, and Nandan.

  5. 5.

    It is ideal to validate the estimated input–output table for the damaged region in a retrospective way. The data used for proportionating the damaged region table from the Hyogo table and adjusting further were publicly available and mostly officially released ones, and the method for adjustment was one of the standard methods for constructing a regional table from the national table. Thus, up to this point, without having the officially released damaged region input–output table, it can be considered that the estimated benchmark table is as good as it can be. The assumptions imposed for import of construction and capacity limitation have not been empirically examined in any way. These assumptions are treated as scenario cases in this study.

  6. 6.

    The reconstruction demand by sector is found in Table 1 of “Appendix.”

  7. 7.

    This assumption may violate one of the basic rules regarding regional input–output table—construction output (built environment) should not be traded over space. However, during the early recovery period, reconstruction activities were carried out mostly by the other regions’ construction companies bringing labor and equipment from the outside, due to damages and labor shortages in the local construction sector (Ashiya and Jinushi 2001).

  8. 8.

    The Kanto region is the largest region in Japan in terms of economic activities. The Kanto region includes the prefectures of Tokyo, Kanagawa, Saitama, Chiba, Gunma, Tochigi, and Ibaraki. It is also far from the Kinki region, where the City of Kobe locates.

  9. 9.

    As noted before, Okuyama (2014) used the Kobe regional input–output tables, and its sector aggregation scheme is different from the AJ tables in this paper. The Kobe input–output tables are aggregated to 28 sectors, while the AJ tables have 34 sectors. Thus, the discussion here uses only this study’s sector number but not for the 2014 study.

  10. 10.

    The results in Figs. 11 and 12 are based on the 95III version of AJ tables. Because the results are very similar between 95II and 95III except those capacity-constrained sectors [construction (19) and real estate (24)], the analysis and discussion here are based only on the 95III results.

  11. 11.

    Chang (2010) also reported this tendency.

  12. 12.

    According to Okuyama and Santos (2014), impact analysis with input–output table usually overestimates the impact with various reasons.

References

  1. Albala-Bertrand JM (2007) Globalization and localization: an economic approach. In: Rodriguez H, Quarantelli E-L, Dynes R-R (eds) Handbook of disaster research. Springer, New York, NY, pp 147–67

  2. Ashiya T, Jinushi T (2001) Shinsai to Hisaichi Sangyoukouzou no Henka: Hisaichi Chiiki Sangyourennkanhyo no Suitei to Ouyou. Kokumin Keizai Zasshi 183(1):79–97 (in Japanese)

  3. Baade RA, Baumann R, Matheson V (2007) Estimating the economic impact of natural and social disasters, with an application to Hurricane Katrina. Urban Stud 44(11):2061–2076

  4. Cavallo E, Galiani S, Noy I, Pantano J (2013) Catastrophic natural disasters and economic growth. Rev Econ Stat 95(5):1549–1561

  5. Chang SE (2010) Urban disaster recovery: a measurement framework and its application to the 1995 Kobe earthquake. Disasters 34(2):303–327

  6. Coffman M, Noy I (2011) Hurricane Iniki: measuring the long-term economic impact of a natural disaster using synthetic control. Environ Dev Econ 17:187–205

  7. Cuaresma JC, Hlouskova J, Obersteiner M (2008) Natural disasters as creative destruction? Evidence from developing countries. Econ Inq 46(2):214–226

  8. DuPont W, Noy I (2015) What happened to Kobe? A reassessment of the impact of the 1995 earthquake. Econ Dev Cult Change 63(4):777–812

  9. Fujiki H, Hsiao C (2013) Disentangling the effects of multiple treatments—measuring the net economic impact of the 1995 Great Hanshin-Awaji Earthquake, IMES Discussion Paper 2013-E-3. Institute for Monetary and Economic Studies, Bank of Japan

  10. Hallegatte S, Przyluski V (2010) The economics of natural disasters. CESifo Forum 2:14–24

  11. Hornbeck R (2009) The enduring impact of the American Dust Bowl: short and long run adjustments to environmental catastrophe, NBER Working Paper Series: W15605

  12. Horwich G (2000) Economic lessons of the Kobe earthquake. Econ Dev Cult Change 48:521–542

  13. Hyogo Prefecture Government (2010) Status of recovery and reconstruction after the Great Hanshin-Awaji Earthquake (in Japanese)

  14. Lazzaroni S, van Bergeijk PAG (2014) Natural disaster’s impact, factors of resilience and development: a meta-analysis of the macroeconomic literature. Ecol Econ 107:333–346

  15. Odell KA, Weidenmier MD (2002) Real shock, monetary aftershock: the San Francisco earthquake and the panic of 1907, NBER Working Paper Series: W9176

  16. Okuyama Y (2003) Economics of natural disasters: a critical review. Research Paper 2003-12. West Virginia University, Regional Research Institute

  17. Okuyama Y (2014) Disaster and economic structural change: case study on the 1995 Kobe earthquake. Econ Syst Res 26(1):98–117

  18. Okuyama Y (2015) Long-run effect of a disaster: case study on the Kobe earthquake. Singap Econ Rev (forthcoming)

  19. Okuyama Y, Santos JR (2014) Disaster impact and input–output analysis. Econ Syst Res 26(1):1–12

  20. Okuyama Y, Hewings GJD, Sonis M (1999) Economic impacts of an unscheduled, disruptive event: a Miyazawa multiplier analysis. In: Hewings GJD, Sonis M, Madden M, Kimura Y (eds) Understanding and interpreting economic structure. Springer, Berlin, pp 113–144

  21. Skidmore M, Toya H (2002) Do natural disasters promote long-run growth? Econ Inq 40(4):664–687

  22. Toyoda T (2006) Dai Saigai karano Keizai Fukko: Zaigen Mondai to Teian. Keizaigaku Kenkyu 10(1):95–110 (in Japanese)

  23. van Bergeijk PAG, Lazzaroni S (2015) Macroeconomics of natural disasters: strengths and weaknesses of meta-analysis versus review of literature. Risk Anal 35(6):1050–1072

Download references

Author information

Correspondence to Yasuhide Okuyama.

Appendix

Appendix

See Table 1.

Table 1 Sector classification and reconstruction demand in Ashiya–Jinushi input–output table

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Okuyama, Y. How shaky was the regional economy after the 1995 Kobe earthquake? A multiplicative decomposition analysis of disaster impact. Ann Reg Sci 55, 289–312 (2015). https://doi.org/10.1007/s00168-015-0691-z

Download citation

JEL Classification

  • C67
  • Q54
  • R11