Case study: applying a regional CGE model for estimation of indirect economic losses due to damaged highway bridges.

Destruction from natural and man-made disasters can result in extensive damage to the affected area's infrastructure. While the destruction results in costs that are necessary to restore the physical destruction and repair of existing infrastructure, a wider economic impact is often indirectly measured and felt. Policy-makers generally focus only on losses that are directly caused by the destruction, such as the replacement of roads and bridges, yet tend to overlook the consequences from indirect economic losses. This study proposes a framework to estimate the indirect economic loss due to damaged bridges within the highway system of a major metropolitan area. For the research, a simulated earthquake within the St. Louis metropolitan region is selected as a case study. The computable general equilibrium (CGE) model is applied as the loss estimation tool for modeling the indirect cost. The study results show that the indirect loss is significant when compared to the direct loss and should therefore be considered by policy-makers when making both pre- and post-disaster infrastructure decisions.

INTRODUCTION

Natural disasters not only cause fatalities and injuries but also result in infrastructure damage, social effects, and economic impacts. Without appropriate preventive action plans and effective mitigation policies, unforeseen natural catastrophes can cause tremendous losses, as evident from the 2005 Hurricane Katrina in the southern coastal United States and the 1994 Northridge earthquake in Southern California. From an economic perspective, there are costs associated with the damage caused by natural disasters, such as the repair or replacement costs for the damaged structure, temporary unemployment, business interruption, etc. Generally, economic natural hazard losses can be categorized into two groups: direct economic loss and indirect economic loss.

Direct Economic Loss

Direct economic loss is the economic damage generated directly by a natural disaster; for example, the damage of buildings, roads, production facilities, indoor property loss, etc. Basically, these losses can be measured by the repair or replacement costs of the damaged structure and properties, including building contents and business inventory (Brookshire et al., 1997; Lindell and Prater, 2003; Enke et al., 2007; Commission on Geosciences, Environment and Resources, 1999; An et al., 2004; Chen et al., 2005; Sohn et al., 2003; Federal Emergency Management Agency 2001).

Indirect Economic Loss

Indirect economic loss is the loss that represents the consequences of disaster destruction. Brookshire et al. (1997) gave the definition of indirect loss as any loss that extends beyond the direct physical impact, such as income losses, business inventory loss, etc. Boisvert (1992) defined the indirect loss as the loss that resulted from the multiplier or ripple effect throughout the economy due to supply bottlenecks and reduced demand as a result of the direct economic loss. Burrus et al. (2002) referred to the indirect loss as the decreases in economic output due to business disruption/interruption. From these studies and others (Enke et al., 2007; Federal Emergency Management Agency, 2001; Commission on Geosciences, Environment and Resources, 1999), it is obvious that there are variations in the definition and defined boundary of what is considered as an indirect economic loss.

The physical damage to structure, death and injury, and the collateral hazards are just the beginning of an economic damage assessment. At times, policy-makers focus only on the physical damages, or direct losses. Naturally, these direct losses are easy to notice and observe since they are directly caused by the incident. However, they are only part of the total losses that are caused by the disasters. Policy-makers tend to overlook the subsequent indirect losses that are characterized with more ambiguous causes and uncertain loss amounts, compared to direct losses (Commission on Geosciences, Environment and Resources 1999; Enke et al. 2007; Chang et al. 2000). These indirect consequences are also important and significant.

STUDY SCOPE AND FRAMEWORK

Earthquakes are one of the most serious natural disasters. From 1947 thru 1980, earthquakes produced 28 of the greatest recorded disasters, causing about 450,000 deaths (Lindell and Prater 2003). Earthquakes usually cause short-term effects, such as unemployment, business disruption, etc. They also leave long-term impacts on the affected area, such as a permanent change in business/economic patterns, residence migration out of the area, lower real estate values, etc. (Chang 2000; Commission on Geosciences, Environment and Resources 1999). In this study, a simulated magnitude 7.0 earthquake scenario centered in St. Louis, Missouri, was selected as a case study. It was assumed that the earthquake situation occurred in the year 2004. The study scope and definition of indirect loss are limited to indirect losses that occur due to damaged bridges in the highway network. An outline for the study framework is illustrated in Figure 1.

The study framework begins with the simulation of the earthquake scenario that provides information about the ground-shake motion within the study region. The earthquake ground-shake information is then transformed into physical damage, and the damage is estimated into a dollar figure by utilizing the HAZUS-MH model, developed by the Federal Emergency Management Agency (FEMA). In this study, the concerned physical damage refers to damaged highway bridges. The direct loss that results from the event is basically the cost to repair or replace the damaged bridges.

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The indirect economic loss for this study is the loss that occurs just from the damage bridges, besides the repair or replacement cost. Other than the physical damage, the damaged bridges will reduce the highway transportation capacity, or even completely close some of the routes in the network. This will obviously increase the transportation time and distance in the highway network, as well as the transportation cost. By combining information about damaged bridges with the transportation network model, along with the value of travel time and distance, the initial loss, or the increased travel cost that is a direct consequence from the lower capacity highway network, can be estimated.

The increased transportation cost can only be considered as the initial impact on the economic system. In addition to this increased travel cost, there will also be a ripple effect on the economy resulting from these costs. For the producers, this additional cost will cause an increase in the production cost of the sector's output, and consequently the price of commodities. For the consumers, this additional cost will reduce their spending allowance and eventually reduce the final demand of commodities. The increased price for some of the commodities, along with possible spending reductions for all commodities, will cause additional economic ripple effects. The computable general equilibrium (CGE) model is selected as the tool to capture ripple effects throughout the entire economic system due to increased travel cost. The CGE model estimates this loss into a dollar figure.

The direct loss, or the cost to repair or replace the damaged bridges for this study scenario, is estimated at $1.3 billion (Chen et al., 2005). Consequently, these damaged highway bridges will result in an increased travel cost of $703 million for the 500-day period (Enke et al., 2007) or $684 million for the first 365-day period after the earthquake (Tirasirichai, 2007). Since the CGE model is usually developed using a yearly basis, the increased travel costs for a one-year timeframe will be applied as the first impact on the entire economic system. The discussion in this article focuses on the application of a regional CGE model to capture the ripple effects, beginning with background on the CGE model, followed by the approach used for the CGE model construction, and, finally, the study results and sensitivity analysis. More information regarding the entire study framework, the direct loss estimation, and the increased travel cost estimation can be found in previous studies (Tirasirichai, 2007; Enke et al., 2007; Tirasirichai and Enke, 2006: Chen et al., 2005).

COMPUTABLE GENERAL EQUILIBRIUM (CGE) MODEL

The CGE model represents multimarket simulation models based on simultaneous optimizing behavior of individual consumers and firms, subject to economic account balances and resource constraints (Shoven and Whalley, 1992). The core theory of the CGE model is the general equilibrium theory. Different from partial equilibrium, which considers the equilibrium of any single market, the general equilibrium theory by itself involves the study of simultaneous equilibrium in all markets of the entire economy (Nicholson, 1994; Shoven and Whalley, 1992). The prices and production of all goods are interrelated. A change in the price of one good, say fuel, may affect another price, such as transportation service. If the price of fuel goes up, the price of transportation service might go up as well. The demand for fuel might be affected by a change in transportation service demand, with a consequent effect on the price of fuel. Calculating the equilibrium price of just one good, in theory, requires an analysis that accounts for all of the millions of different goods that are available. Therefore, it is practically impossible to find the equilibrium state freely without some restrictions.