A Multiregional Impact Assessment Model for disaster analysis

Elco E Koks,Mark Thissen

doi:10.1080/09535314.2016.1232701

Abstract

ABSTRACTThis paper presents a recursive dynamic multiregional supply-use model, combining linear programming and input–output (I–O) modeling to assess the economy-wide consequences of a natural disaster on a pan-European scale. It is a supply-use model which considers production technologies and allows for supply side constraints. The model has been illustrated for three floods in Rotterdam, The Netherlands. Results show that most of the neighboring regions gain from the flood due to increased demand for reconstruction and production capacity constraints in the affected region. Regions located further away or neighboring regions without a direct export link to the affected region mostly suffered small losses. These losses are due to the costs of increased inefficiencies in the production process that have to be paid for by all (indirectly) consuming regions. In the end, the floods cause regionally differentiated welfare effects.

Highlights

A vast amount of research has been done to assess a wide variety of disaster losses, ranging from direct and indirect losses, tangible and intangible losses, to short-term (e.g. Li et al, 2013; Hallegatte, 2014; Koks et al, 2015; Santos et al, 2014) and long-term losses (e.g. Skidmore and Toya, 2002; Coffman and Noy, 2012)
A novel methodology is introduced which simultaneously allows for production limitations, production inefficiencies and cascading effects in an assessment of the short-run multiregional economic effects of a natural disaster in Europe
This paper presented a recursive dynamic multiregional supply-use model, combining linear programming with elements of I–O modeling, to assess the effects of a local natural disaster on the European Union (EU) regional economy

Summary

Introduction

A vast amount of research has been done to assess a wide variety of disaster losses, ranging from direct and indirect losses, tangible and intangible losses (see Meyer et al, 2013 for an overview of existing literature), to short-term (e.g. Li et al, 2013; Hallegatte, 2014; Koks et al, 2015; Santos et al, 2014) and long-term losses (e.g. Skidmore and Toya, 2002; Coffman and Noy, 2012). Li et al, 2013; Hallegatte, 2014; Koks et al, 2015; Santos et al, 2014) and long-term losses Disaster impact analysis is often still focused on the effects to only one single country or region. Natural hazards and their economic consequences, do not stop at administrative boundaries. In a world with increasing economic relations between regions and countries, it can be expected that areas which are not directly hit by a disaster will suffer economic losses via cascading effects (Okuyama and Santos, 2014).

Objectives

Methods

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Conclusion