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.
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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.
Toyoda (2006) also estimated the long-run effects of the Kobe earthquake using a simple trend analysis without providing the details.
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.
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.
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.
The reconstruction demand by sector is found in Table 1 of “Appendix.”
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).
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.
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.
Chang (2010) also reported this tendency.
According to Okuyama and Santos (2014), impact analysis with input–output table usually overestimates the impact with various reasons.
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See Table 1.
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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