A Quick Method for Assessing Economic Damage Caused by Natural Disasters: An Epidemiological Approach

By Hayashi, Mampei | International Advances in Economic Research, November 2012 | Go to article overview

A Quick Method for Assessing Economic Damage Caused by Natural Disasters: An Epidemiological Approach


Hayashi, Mampei, International Advances in Economic Research


Abstract In the aftermath of any natural disaster, a quick assessment of economic damage is called for, without which recovery planning and fiscal budgeting is impossible. What is customarily done as damage accounting is to use some aggregation by parts method, which is predisposed to commit double counting, omission, and bureaucratic inconsistencies. As an alternative, we propose to work with a social epidemiological model. First, we present a result by means of a log linear model which shows evidence of hazard factors and vulnerability factors at work. We then simplify the model by deleting the variables that are not significant in a linear formulation. Lastly, we give our estimate of economic damage for the case of the North East Japan Earthquake and Tsunami of March 11, 2011 and alert that the true damage may well be the double of government's estimate.

Keywords Direct economic damage * Natural disaster * Epidemiological model

JEL 3 * 15 * 29 * 31

Introduction

Japan is a natural disaster prone country. Figure 1 compares the top 10 countries in terms of the occurrences of natural disaster per 100,000 square kilometers of land territory for the period 1990-2010. Japan ranks number two after the Philippines. Among the high income countries, however, Japan stands at the top by the same metric.

[FIGURE 1 OMITTED]

In any occurrence of a natural disaster, it is imperative, as well as academically challenging, to assess the value of economic damage involved. From a practical point of view, assessment needs to be done in the midst of an on-going emergency, where time is the most scarce resource of all. In retrospect, it must be conducted in order to search for possible policy measures for future mitigation.

However, as Cochrane (2004, pp.290-291) says in relation to the 9/11 incident in New York, 2001, "Loss accounting, as currently practiced, is problematic for several reasons." He goes on to say that" ... most problems stem from double counting, failure to identify clearly an accounting stance, ignoring non-market losses, confusion as to whether post-disaster economic trends are a product of the event or some other unrelated factor, and the employment of too limited a time frame."

Thus, the purpose of this paper is to present a simple epidemiological model for assessing economic damage, which is applicable to any event or natural disaster. The method comprises an alternative to the common accounting practice of aggregation by parts.

In the next section, we will explain what is commonly done in Japan regarding the economic damage measurement. In the section following that, we will present a social epidemiological model of hazard and vulnerability leading to economic damage. We will then examine the data availability and select variables to be used for estimation. Finally, we will present the fixed effect estimation result.

In the section after that, we will propose yet another model of a simple equation, which is convenient for a quick estimation. By applying this method to calculate the damage of the North East Japan earthquakes and tsunami of March 11, 2011 (the Tohoku earthquake), we conclude that the true direct economic damage may well be the double of government's estimation.

Measurement of Post-Disaster Economic Damage: The Common Practice

The Fire and Disaster Management Agency (FDMA) of the Japanese government has been compiling statistics regarding natural disasters based on reports filed by 47 prefectures. (1) The FDMA classification of disaster damage is shown in Table 1. All types of damage are reported in physical units except economic damage.

Table 1 FDMA classification of Natural disasters damage

Damage           Type of damage                      Unit
classification

Human damage     dead                                person

                 missing                             person

                 injured               seriously     person
                                       injured

                                       injured       person

                 affected population   affected      household
                                       household

                                       affected      person
                                       population

Building damage  housing damage        totally       building
                                       destroyed

                                       half          building
                                       destroyed

                                       partially     building
                                       destroyed

                                       inundated     building
                                       above floor

                                       inundated     building
                                       below floor-

                 non-housing           public        building
                                       buildings

                                       other         building

Others           rice field destroyed                ha

                 rice field flooded                  ha

                 fruit and vegetable                 ha
                 patch destroyed

                 fruit and vegetable                 ha
                 patch flooded

Public           public                school        campus
infrastructure   infrastructure

                                       bridge        bridge

                                       river         site

                                       landslide     site

Transportation   railway blocked                     site

                 ship                                ship

Economic damage                                      thousand
                                                     yen

Data is compiled on a yearly basis, and it covers the period 1995-2007. …

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