報告書番号

U03060

タイトル（和文）

地震災害後の経済回復過程に関する一考察

タイトル（英文）

Analysis of Economic Recovery Process After an Earthquake Disaster

概要 （図表や脚注は「報告書全文」に掲載しております）

本研究では，兵庫県南部地震後の製造業の回復過程（鉱工業生産指数）に着目し，その要因分析を行うことによって，地震災害による経済被害推計モデルの提案を試みた．その際，都市インフラ機能の破壊がもたらす操業停止状態からの早期回復に影響を及ぼす産業特性をレジリエンシー(回復・復元性)と定義し，その関数化を行った．統計学的な検定の結果，各部門のレジリエンシーは，直接被害の大きさ，生産額のシェア，経済のトレンド，交易への依存度，地域間の交易で必要とする交通量によって有意な影響を受けていることが実証された．得られたレジリエンシー関数は刻一刻と時間軸上で変化する製造業の回復状況を把握することが可能であり，数週間，数ヶ月単位で発生するライフライン途絶影響の分析を行う上で有効となる．

概要 （英文）

There are many studies on the loss estimation after a disaster. However, these studies usually target the yearly economic loss estimation and cannot determine the recovery process on a smaller temporal scale such as weekly or monthly period. This is due to the complexity of recovery process; however, it is necessary to evaluate the economic loss at a finer temporal scale to conduct a more strategic reconstruction work schedule, allocate financial aid and address traffic flow adjustments. Degree of favorable characters for recovery such as recovery speeds from the economic shock from urban functional damage (e.g. energy supply disruption, transportation damage) are defined as "resiliency" and this is thought as play an important role in the economic loss estimation on a smaller temporal scale. There are many factors contributing to resiliency, many of which are difficult to determine theoretically. One useful approach is to accumulate the post-disaster analyses and empirically determine the resiliency of each sector. In this paper, we focus on a monthly time series of indices of industrial production (IIP) after the 1995 Hyogoken-Nanbu Earthquake in Japan and investigate statistically the resiliency of each sector. An input-output model and traffic census data are applied to estimate the monthly losses and test if the economic model can explain the index data. It is found that the temporal change of the indices depends not only on physical damages but also on other economic conditions such as share of production, economic trend, trade with other non-damaged regions and traffic amount required for trading. Based on the results, we propose resiliency functions for each industrial sector to support the loss estimation of lifeline disruptions caused by future disasters.

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