| Project/Area Number |
25245043
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Public finance/Public economy
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| Research Institution | Nihon University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
瀬下 博之 専修大学, 商学部, 教授 (20265937)
日引 聡 東北大学, 経済学研究科, 教授 (30218739)
青木 研 上智大学, 経済学部, 教授 (70275014)
浅田 義久 日本大学, 経済学部, 教授 (70299874)
中川 雅之 日本大学, 経済学部, 教授 (70324853)
有村 俊秀 早稲田大学, 政治経済学術院, 教授 (70327865)
宅間 文夫 明海大学, 不動産学部, 准教授 (80337493)
川西 諭 上智大学, 経済学部, 教授 (90317503)
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| Research Collaborator |
HARANO Kei 日本住宅総合センター
SADAYUKI Taisuke 早稲田大学
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| Project Period (FY) |
2013-10-21 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥40,300,000 (Direct Cost: ¥31,000,000、Indirect Cost: ¥9,300,000)
Fiscal Year 2017: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2016: ¥7,280,000 (Direct Cost: ¥5,600,000、Indirect Cost: ¥1,680,000)
Fiscal Year 2015: ¥7,930,000 (Direct Cost: ¥6,100,000、Indirect Cost: ¥1,830,000)
Fiscal Year 2014: ¥11,440,000 (Direct Cost: ¥8,800,000、Indirect Cost: ¥2,640,000)
Fiscal Year 2013: ¥10,790,000 (Direct Cost: ¥8,300,000、Indirect Cost: ¥2,490,000)
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| Keywords | 時間整合性 / モラルハザード / 強制保険 / 事後的救済 / 木造住宅密集地域 / 区分所有法 / 糸魚川大火 / 災害対策 / 地価データ / 危険回避度 / 都市防災対策 / 事後的救済・補償 / モラル・ハザード / 民主的選挙制度 / 開発規制 / 法と経済学 / 社会的費用の計測 |
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| Outline of Final Research Achievements |
We consider the locational decisions of residents in a small, open linear city at risk for natural disasters and analyzes the relationship between public investment in disaster prevention and compensation by the government. Remarkably, the ex post optimal compensation policy, a type of fully covered compensation, causes time-inconsistency problems. That is, such ex post policy makes the residential area more vulnerable to natural disasters in ex ante. As a result, the ex post compensation policy requires excess preventive investment, unless it is financed from outside the community. External financing does not improve this problem rather may exacerbate these problems. Basing on this theoretical findings, we argue socially optimal disaster policy to resolve these problems.
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