首都直下地震災害からの経済復興シナリオ作成の試み



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ESRI Discussion Paper Series No.250 October 2010 Economic and Social Research Institute Cabinet Office Tokyo, Japan

The views expressed in ESRI Discussion Papers are those of the authors and not those of the Economic and Social Research Institute, the Cabinet Office, or the Government of Japan.

112 1

Economic recovery scenario planning for the Tokyo inland earthquake Shingo Nagamatsu Associate Professor, Faculty of Safety Science, Kansai University Haruo Hayashi Professor, Disaster Prevention Research Institute, Kyoto University Abstract The economic damage caused by the Tokyo Inland Earthquake disaster is estimated at 112 trillion yen by the Central Disaster Management Council of Japan. The estimated figure however is surrounded by so much uncertainty that there surely exists a risk of the actual damage caused by an earthquake disaster exceeding the estimated damage. Moreover, the figure does not present a concrete image of disasters and the recovery process and has little impact on the development of concrete countermeasures against the economic problems caused by the disaster. In order to cope with such a problem, we employ scenario planning as a decision-making method under uncertainty. In this paper, we developed four scenarios of economic damage and recovery processes after the disaster. These scenarios are generated by the following two major uncertainties. The first uncertainty is the default risk of Japanese government. In the event that Japan s financial status deteriorates or the damage caused by the earthquake far exceeds the estimate, the Japanese government might face difficulties in financing the recovery. The second uncertainty is a gap between demand and supply in a recovery-related market, especially in the construction sector. If the gap is sufficiently larger, damaged houses, infrastructure, and firms assets can be quickly restored without price increase. Otherwise, restoration will take a long time and bring with it the risk of price increase. The anticipated Tokyo inland earthquake will not be so catastrophic as to compel the Japanese government to default. However, it will be large enough to delay the recovery process and cause a price increase, since the construction market has shrunken to almost half since the 1995 Hanshin Awaji Great Earthquake. To avoid such a risk, assistance from the international community in debris removal, waste disposal, and reconstruction should be seriously considered. 2

1 M7.0 2004 16 12 11,000 112 M8.0 M8.1 (M8.4 ) 2003 3 (Munich Re, 2003; p.33) 112 3

5 2 3 4 5 6 7 2 1 1 Munich Re(2009), p.36 http://www.emdat.be/natural-disasters-trends 4

2.1 1 1000 (6,434 ) 9.9 66.6 6 10 10 2.2 2.2.1 5

2.2.2 2.2.3 K Y Y F(K) K Y Y F K K F K F(X) K F BCP 6

2.2.4 (Bertrand, 1993) (Toya and Skidmore, 2007) 2.3 2 2 Forge(2009) 7

, 1998 Forge, Blackman and Bohlin, 2006 2003 8

1 5 (2003), p.105 3 3.1 5 10 20 3.2 11,000 112 9

1923 M8.0 100 M8.0 M7.0 M7.3 18 15m 112, 2006, 2007 M8.0 112 66.6 66.6 51.4 5.2 3.8 2.7 10

2 M7.3 4 4.1 1923 12 20 45 2008, 1955, 2006 30 21 15 21 11

1 4 3000 1926 2 1927 2 1988; 1993; 1999 1924 13 3 5 5 8% 100 49 1924 ( 13 )4 100 40 100 40 1999 100 50 1988 1924 ( 13 )6 12

, 2008 4.2 1986 61 150 50 150 65% 2 3 2 10% 6.5% 13

46 56 GDP GDP 30 50 1 10 12% 1.2% 4.3 1995 9 9 6434 0.8 1959 9 1.9 1923 9 10.5 (1) (2) ( ) 7 11 1995 90 1995 1996 2 Horwich(2000) 3 1995-1.4% -3.4 14

3 1995 1 43 43 1 17 18 37 11 18 20 10 1 27, p485 9, 1995 8 2 15

(2005) 1980 3 1993 6 32 24,1997;, 1999 1969 10,402 1985 3,131 1996 1,687 2007 9 80% 60% 50% 13 2009 7 10 16

4.4 (Hadfield, 1995) 1989, 1995, 2001, 1995 17

4.5 (Bertrand 1993) 1960 1979 26 28 GDP 3 Bertrand, 1993, p.87 Table 3.39. GDP Bertrand GDP GDP 3 (consistent) (Albara-Bertrand, 1993; p.87) (In contradiction) 18

2 2 1960 70 5 5.1 2010 863 2009 3 1409 1063 66.6 2007 2.2% 2.2% 2020 (Tokuoka, 2010) (, 2006) 19

3.2.4 5.2 1995 2008 2005 8 Richardson (2007) 1990 13,600 20 6.5% 4 ( U.S. Department of Housing and Urban Development, Fair Market Rent History 2000 to 2005 20

15 7169 2008 162 9.6% 109 3485 67.5% 41.6 1981, 2009 552,000 30,686 2007 288,426 2008 5.5% 52 1995 790,169 2010 416,000 1995 12 551 2008 427 77% 5.3 1980 1983 1.220 1999 2003 0.544 OECD 1970 1974 0.736 1990 1994 0.346, 2006; p.40 21

5.4 66.6 6 6.1 (1) (2) (3) (4) 5 22

(1) (2) (4) (1) (2) (4) 6.2 (1) (4) 6.3 (2) (4) 23

I II III IV 2010 1 6 6.4 IS-LM 6.5 24

2, 2003 2008 11 86 7 2 25

2 7.1 I 2 3 GDP 26

7 I 7.2 II 8 27

8 II 7.3 III GDP 9 28

9 III 4 7.4 IV 4 5.5 29

GDP 10 10 IV III 8 II M8.0 III IV 30

3 3 2010 6 18 19 22 31

,94(6), 2009., 2004, 1995., 2001. 21, 1995, 2006. 18 2006. 1986., 1999., 2007. 1955., 1988 2006., 1993. 2008. 1923 3 2009. 15 7 25, 2003., 2006., 1995.2.8. 60, 1995. 1 1997., 51-63, 1997. A. J. M. Bertrand, The Political Economy of Large Natural Disasters. Clarenden Press, 1993. Munich Re, Topics, Annual Review: Natural Catastrophes 2002, 2003. Munich Re, Topics Geo, Natural catastrophes 2009: Analyses, assessments, positions, 32

2010. Simon Forge, Colin Blackman and Erik Bohlin, Constructing and using scenarios to forecast demand for future mobile communications services, Foresight, 8(3), 36-54, 2006. Simon Forge Forecasting quantitatively using micor/meso/macro-economics with scenarios for qualitative balance, Foresight, 11(1), 43-60, 2009. Kiichi Tokuoka The Outlook for Financing Japan s Public Debt, IMF Working Paper, WP/10/19, 2010. http://www.imf.org/external/pubs/ft/wp/2010/wp1019.pdf H. Toya and M. Skidmore Economic Development and the Impacts of Natural Disasters Economics Letters, 94, pp. 20-25, 2007. 33