Hurricanes and economic research: an introduction to the Hurricane Katrina symposium.

Ewing, Bradley T. ; Kruse, Jamie Brown ; Sutter, Dan 等

1. Introduction

Hurricane Katrina wreaked havoc on the United States. The tropical depression that became tropical storm Katrina on August 24, 2005, was the 11th named storm in a busy Atlantic hurricane season. Just one day later, Hurricane Katrina made its first landfall in Southern Florida as a Category One storm, causing both death and destruction. After moving into the Gulf of Mexico, it intensified and made its second landfall August 29, 2005, near the Louisiana-Mississippi border as a strong Category Four storm. The total impact of this killer storm in all of its human and environmental dimensions will not be determined for several years. Estimates of the monetary impact indicate that Katrina was the costliest storm in U.S. history. More than a million Gulf Coast residents were displaced by the storm.

On the other side of the world, nine months before Katrina, the December 26, 2004, Indian Ocean tsunami created devastation that was unimaginable. We learned that people had virtually no warning of the killer wave according to news bulletins that arrived minutes after the natural disaster. In contrast, the tropical depression that became Hurricane Katrina was tracked for more than six days before it made landfall in Mississippi. Again, we watched in disbelief as news commentators showed us the damage and suffering that resulted from destructive wind, waves, and rain. Scenarios projecting a major hurricane making landfall near New Orleans have been studied for the last 20 years. Yet Katrina overwhelmed us in every way. Surely we can do better than this.

As researchers, the failure of the system to deal adequately with the disaster provokes us to apply our intelligence and expertise to understanding the problem and to identify ways to protect our capital stock both human and physical. We cannot and probably should not interfere with the natural processes that create hurricanes. Therefore, the challenge is to identify and adopt strategies that allow a region to reduce the disruption and promote recovery that improves the quality of life for all segments of the population. Resilience is the goal for structural, environmental, and human systems.

The destruction caused by a hurricane is undeniable and has moved front and center on the national stage. Katrina disabled and destroyed much of the region's capital stock, including businesses, production facilities, lifelines, and housing. The forced migration prompted by Katrina highlights the potential for an area to also lose its human capital. The loss of physical and human capital by a region has significant short-term and possibly long-term effects on regional economic growth.

2. Regional Economic Consequences of Hurricanes

Hurricanes and natural disasters disrupt the economic activity of regions in a number of ways as business activity is interrupted and infrastructure is destroyed. In fact, a number of studies have documented the extent to which hurricanes, tornadoes, and other catastrophes interrupt business activity with some of the work geared toward determining how long these effects might last (Rose et al. 1997; Tierney 1997; Webb, Tierney, and Dahlhammer 2000; Rose and Lim 2002).

A number of factors contributed to the findings reported in the literature, such as the type and severity of the event, the economic and political environment of the communities affected, and the state of the economy at the time of the disaster. Recognition of these factors is what has led to a small but growing body of literature that focuses on issues related to recovery and resilience (Burrus et al. 2002; Rose and Liao 2002; Rose 2004). In this research, we attempt to determine the drivers of economic recovery and draw some models from the vast literature on economic growth theory. This line of research includes traditional regional economic tools, such as input-output modeling, to understand the economic effects of disasters (Guimaraes, Hefner, and Woodward 1993; West and Lenze 1994). The results from traditional regional models tell only part of the picture and, as such, researchers have expanded their approach to include other methods, mostly borrowed from macroeconomics. These methods include time series analysis, event studies, and computable general equilibrium analysis (CGE). The studies that use these analytical techniques might shed light on the longer term economic effects of severe storms, such as why some regions never fully recover whereas others are economically stronger in the aftermath of a natural disaster.

The time series analysis of hurricanes has generally been conducted in the framework of an event study or an intervention analysis but has also incorporated analysis of both first and second moments. For example, Ewing, Kruse, and Thompson (2005) estimated a time series econometric model of the Corpus Christi, Texas, unemployment rate that included an intervention variable to capture the effect and recovery activity associated with Hurricane Bret in August 1999. They found evidence that Corpus Christi's labor market improved after the hurricane, controlling for business cycle trends and general movements in the economy. Ewing and Kruse (2001) also found that hurricane recovery activity in Wilmington, North Carolina, was associated with a longer term improvement in the local economic environment. Theoretical reasons for how and why a natural disaster might actually produce improvements in economic indicators are covered in Ewing, Kruse, and Thompson (2003, 2004) and Skidmore and Toya (2002); the latter provided evidence that natural disasters have been associated with higher rates of national economic growth, total factor productivity, and accumulation of human capital for many countries.

The CGE framework offers one way to allow for adaptive behavior, such as substitution or market adjustment in response to input shortages when modeling disruptions in economic activity or performance of a region. Rose and Liao (2002) and Rose and Guha (2003) use CGE modeling that incorporates refinements to reflect short-run and long-run adjustments to input supply disruptions that occur after a natural disaster.

Clearly, from a regional standpoint and, in some cases, possibly a national one, disasters can have an immediate economic effect on the ability of an economy to produce and supply goods and services. The evidence on the intermediate and longer term effects of these events is mixed. Additionally, the debate continues in terms of what might constitute the drivers of recovery and resilience. The majority of research on the regional economic effects of hurricanes and disasters is conducted by examining economic indicators such as output, income, and employment. However, other metrics are being considered. In particular, the housing and financial markets have been examined to observe the effects of hurricanes and natural disasters. Studying these markets allows for particular insights regarding the efficiency of markets and the forward-looking behavior of individuals making decisions that are often related to the arrival of news and information.

Ewing, Kruse, and Wang (2007) examined the effect of severe wind events on the mean and variance of housing price indices of six metropolitan statistical areas that are vulnerable to hurricanes, tornadoes, or both. Their findings showed an immediate but short-lived decline in housing prices after a tornado or hurricane but little difference between the two types of disasters. They suggest that the market response to destruction of real property does not distinguish between the types of wind events that could have produced damage to the region. Furthermore, they conclude that the market serves the purpose of integrating and normalizing the losses. In other housing-related research, Coulson and Richard (1996) provided evidence that unseasonable temperature and precipitation significantly influenced housing starts and completions. In a similar study, Fergus (1999) showed that abnormal precipitation and temperature affect housing construction and concluded that builders adjust production fairly quickly to offset favorable or unfavorable weather effects.

Financial markets are also affected by hurricanes. For example, Lamb (1998) examined the market value of insurance firms and found evidence that 1992's Hurricane Andrew, which hit south Florida and Louisiana, adversely affected the stock returns of property and casualty firms with exposure in these areas. This market response likely is due to the amount of destruction and insured losses. However, Angbazo and Narayanan (1996) noted that a hurricane can have two opposing effects on the value of insurer stock prices. They hypothesize a negative effect because of payments on claims and a positive effect because of expectations of higher future premiums. Ewing, Hein, and Kruse (2006a) also used an event study methodology to examine the effect of Hurricane Floyd; however, they specifically recognize the scientific and media releases occurring during the synoptic life cycle of the hurricane on the market value of insurance firms. Thus, they explain the movements in insurer stock prices as arising from the information describing the development of the storm over time and space. They find significant market reaction to the news concerning the path and strength of the storm before landfall, and their results indicate that markets find reliable time-sensitive reports provided by the National Weather Service, the National Hurricane Center, and other media outlets to be valuable information.

Other financial markets have also been examined with event study methodology. For example, studying several hurricanes in three hurricane-prone markets throughout the southeastern United States, Ewing, Hein, and Kruse (2006b) concluded that, for the most part, current and existing risk management practices appear to have worked well for commercial banks. They found little to no evidence of adverse effects on profitability from the wind events and, in some cases, even positive effects.

Issues related to production and the inputs used in various production processes as well as the flow of goods, services, and information has led to new research on the supply chain effects of hurricanes. This strand of literature has tied together elements of regional economics, industrial organization, and operations management. In fact, operations research and management, as well as information systems research, has traditionally provided insight into emergency management practices, evacuation issues, disaster support systems, disaster recovery, transportation, and logistics but has not yet been fully explored with cutting-edge econometrics, survey, and experimental methods. These issues are addressed in Tang (2006) and lay the foundation for future work in this area. Innovative decision and risk management strategies will be the products of adapting new and well-developed methodologies from economics.

3. Risk Perception and Risk Management

Decision making in the face of hurricane threats is multidimensional, with timescales that range from minutes to years and with each stakeholder's decision contributing to a complex system. Public decision makers respond to the risk by designing disaster plans and establishing regulatory constraints such as building codes, planning ordinances, and mandatory evacuation orders. Private decision makers create a portfolio of risk management decisions that span a set that includes location choices for homes and businesses, choices of risk mitigation instruments (self protection), and market-based loss reduction instruments such as insurance. Individuals can undertake a range of actions to reduce casualties or property damage from natural hazards. Kunreuther (1996) stresses improved construction in reducing vulnerability. The low rates of purchase of subsidized flood insurance suggest that people treat low-probability catastrophe risks as if they are zero-probability events, either because of a bias in risk perception or myopia (Camerer and Kunreuther 1989; Kunreuther and Pauly 2004).

Development of a theoretical framework to describe risk and the protective mechanisms chosen by individuals against disasters has a long history yet continues to evolve (e.g., Hirshleifer 1966; Ehrlich and Becker 1972; Kunreuther 1978, 1996; Slovic 1978; Lewis and Nickerson 1989; Shogren 1990; Quiggin 1992; Arrow 1996; Shogren and Crocker 1999).

Numerous survey studies of risk perception for low-probability, high-consequence (LPHC) hazards (Kunreuther 1976, 1978; Slovic, Fischoff, and Lichtenstein 1980; Fischoff, Watson, and Hope 1984; Slovic 1987; Smith and Devousges 1987; Camerer and Kunreuther 1989; McDaniels, Kamlet, and Fischer 1992; Kunreuther 1996; Kunreuther, Onculer, and Slovic 1998) have found divergence in risk perceptions and mitigation actions taken by individuals. Evidence suggests that people integrate risk into their decisions poorly, especially in the case of LPHC risk. In addition, behavioral anomalies such as overconfidence (Debondt and Thaler 1995), source preferences for ambiguous risk (Heath and Tversky 1991), and time-inconsistent preferences (Prelec 2004) also find support in observed behavior. Laboratory experiments have also been used to examine wind risk mitigation (Kruse and Thompson 2003; Kruse and Simmons 2006; Kruse, Ewing, and Thompson 2007).

Field data on market transactions have provided an empirical description of human response to risk. Hedonic property models provide an intuitive analytical tool for examining value revelation for both positive (amenity) and negative (risk) product attributes. In their test of expected utility theory, Brookshire et al. (1985) consider spatially delineated risk factors in the context of the hedonic model. Their analysis suggests that California households are aware of spatial differences in earthquake risk, primarily because of special risk assessments conducted by government authorities in conjunction with disclosure requirements, and that the market capitalizes this risk, discounting properties in the high-risk area.

A number of hedonic property studies of hazards followed in the environment and risk literature that demonstrated lower valuation for higher risk locations or construction techniques. Homes in storm surge flooding zones in Miami-Dade and Lee counties in Florida experienced slower price growth after Hurricane Andrew, indicating greater perceived risk of hurricanes throughout the state (Hallstrom and Smith 2005; Carbone, Hallstrom, and Smith 2006). Other studies focused on surge zone or riverine flood hazards (MacDonald, Murdoch, and White 1987; MacDonald et al. 1990; Simmons, Kruse, and Smith 2002; Bin and Polasky 2004; Bin and Kruse 2006; Bin, Kruse, and Landry 2007; Bin et al. 2007) and beach erosion risk (Kriesel, Randall, and Lichtkoppler 1993; Landry, Keeler, and Kriesel 2003). Study of the human/flood hazard interaction in coastal areas is of increasing importance for several reasons. One reason stems from the growth in population in the coastal zone. Over the last several decades, the coastal population growth rate was more than double the national growth rate (Rappaport and Sachs 2003; Sadowski and Sutter 2005). This growth coupled with coastal development brought greater vulnerability to hurricanes. The amount of developed property and the value of real property in the coastal zone have seen steady increase over the last two decades. The combination of economic growth, population growth, and increased vulnerability has been seen as an explanation for the trend of rising insured disaster losses (Kunreuther 1998).

4. Policy Implications

Natural disasters create community-wide risk. In other cases of spatially and temporally dispersed losses, a homeowner or business owner knows the characteristics of the community he or she will rebuild into. However, a hurricane can devastate a neighborhood or entire city, affecting the future viability of a business or a neighborhood. The correlation of catastrophe risks creates the potential for insolvency for insurers, leaving policy holders without the resources expected for rebuilding (Born and Viscusi 2006). Catastrophes create significant Samaritan's dilemma problems, because many protective measures like levees and seawalls require collective action. Consequently, public policy plays an important role in protecting and responding to natural hazards, a role widely accepted by the public (Viscusi and Zeckhauser 2006).

Forecasts and research comprise one part of hazards policy. Weather forecasts have long been recognized as a quintessential public good; thus, national governments around the world collect weather data and issue forecasts. The U.S. Weather Bureau was founded in 1870, and the National Hurricane Center (NHC) was established in 1967. Investments in weather observations and forecasts provide substantial benefits to society, as documented by previous research. Installation of a national network of Doppler weather radars by the National Weather Service in the 1990s reduced tornado fatalities and injuries by about 40% (Simmons and Sutter 2005). Hurricane forecasts are worth an estimated $15 million annually to oil and natural gas producers in the Gulf of Mexico, which exceeds the annual budget of the NHC (Considine et al. 2004). The NHC accurately warned for Katrina, forecasting substantial strengthening and indicating a high probability of a strike near New Orleans three days before landfall.

Investing in hurricane forecasts is an economic question. The economics of information provides the basis for valuing forecasts, and Katz and Murphy (1997) presented an excellent synthesis of the meteorology and economics involved. Hurricane forecasts can be improved on several different dimensions, including different time horizons (24 hour, 72 hour, one week, or seasonal), storm track, and intensity; economics provides the basis on which we can compare the value of improvements in different dimensions (Letson, Sutter, and Lazo 2007). Public policy must also balance the public and private sectors in weather forecasting. Craft (1999) examined two private sector alternative providers of Great Lakes storm forecasts in the 1870sinsurers and newspapers--and concluded that neither could have profitably supplied forecasts at that time. But today, many skilled forecasters work in the private sector and provide specialized or detailed forecasts to help reduce business losses and facilitate recovery. The Miami Hurricane Futures market, in which forecasters can trade shares about where and when a tropical system might make landfall, provides a means to aggregate the varying forecasts (http://hurricanefutures.miami.edu). Improved hurricane forecasts, however, are not a panacea because the reduced danger of living along a coast has increased property damage (Sadowski and Sutter 2005).

Levees and land use planning protect entire communities and consequently are considered public goods. Poor design and maintenance led to catastrophic levee breaches in New Orleans during Katrina, but many scholars consider a failure to prepare ahead of time for natural hazards as typical. Politicians often exhibit the "not during my term in office" syndrome and delay investing in mitigation (Kunreuther and Pauly 2006). Income inequality might also reduce public investments. Anbarci, Escaleras, and Register (2005) modeled conflicting interests of the rich and poor in public good investments in mitigation. With greater inequality, if the rich are required to pay for a larger share of public mitigation, then at some point they optimally choose to self-protect through private actions, leaving the poor exposed to the hazard. International evidence that greater inequality, in addition to low income, increases natural hazard fatalities supports this conjecture (Anbarci, Escaleras, and Register 2005; Kahn 2005). A lack of hard evidence on its cost effectiveness could also explain a lack of support for mitigation (Mileti 1999). But this is changing. Wilmington, North Carolina, was struck by four hurricanes between 1996 and 1999, and Ewing and Kruse (2002) found that Wilmington's participation in FEMA's Project Impact reduced the labor market impact of the 1999 hurricanes. Burby (2005) found lower disaster costs in states that mandate natural hazards planning as part of their comprehensive land use planning legislation. And a major study of FEMA mitigation projects found a benefit to cost ratio of over four to one (Multihazard Mitigation Council 2005).

Society faces a Samaritan's Dilemma problem in the aftermath of hurricanes and natural disasters. The natural human response after a disaster is to assist the victims, and government increasingly takes the lead in providing disaster assistance. But Garrett and Sobel (2003) document the influence of political forces that drive disaster declarations and appropriations. The inadequacy of government preparation for and response to Katrina was evident to television viewers across the world. The public sector faces both incentive problems and information problems in responding to a disaster like Katrina. The information problem involves difficulty in determining what is needed, where, when, and by whom, and getting the needed relief to victims in a timely manner, whereas division of responsibility among different agencies and the lack of a residual claimant generate incentive problems (Shughart 2006; Sobel and Leeson 2006, 2007). Instead of continuing to provide massive amounts of relief after the fact, Kunreuther and Pauly (2006) argue that a better approach would be to require comprehensive disaster insurance in addition to the standard multihazard homeowner's insurance.

5. Symposium Overview

The five papers presented in this symposium examine the effects of Katrina on populations and policy with the use of a variety of methodologies. Katrina spawned an evacuation that turned into migration for a significant number of former Mississippi and Louisiana residents. The first paper by Landry et al. examines the Katrina evacuees' decisions to return home. The return migration decision has received scant attention compared with the evacuation decision, yet how many and which evacuees return will dramatically affect the region's future. Landry et al. examine the determinants of evacuees' stated preference to return using two different surveys. Surprisingly, they find that variables proxying connection to community, such as whether a person was born in their county or parish of residence, were not significant determinants of the decision to return. However, evacuees were willing to give up higher wages in Houston to return to New Orleans; the typical evacuee's willingness to pay to return is nearly $4000 per year, a substantial amount given average annual income in this sample was $18,000.

Political factors are important determinants of Federal disaster relief (Garrett and Sobel 2003). Chappell et al. extend these results by examining the determinants of individual assistance after Katrina among Mississippi Gulf Coast residents. They survey respondents about whether government was the source of the most aid or any aid in relief in the immediate post-Katrina period and in the longer run recovery. Relatively few respondents cite government as the source of aid despite a considerable imbalance in the monies spent; for instance, 37% identify the Federal government as a source of aid. Further, only 25% identify a government agency (Federal, state, local, military) as the source of most emergency aid in the immediate storm aftermath. Measures of individual distress (for instance, property damage to home, having received an injury) and whether a person received public assistance prior to Katrina are two consistent factors that increase the likelihood an individual identifies government as a source of aid.

Boettke et al. present the analogy of a three-legged stool to describe society's political, social, and economic/financial dimensions. Each leg must be strong for the stool to be strong or for a region to successfully recover from a disaster like Katrina. For the case of New Orleans, the prognosis for two of the legs is not good. On the political leg, they find a strong link between Federal disaster relief and political corruption. The effect is similar to the resource curse in development economics, as political actors seek to get a share of the available dollars. The economic leg also appears weak, in that New Orleans and Louisiana rank low on measures of freedom and entrepreneurship, and the New Orleans metro area had minimal population growth between 1980 and 2000, a sign of stagnation. Instead of being a "living city" with a dynamic, growing economy, they characterize New Orleans as a "welfare city." But a number of New Orleans neighborhoods exhibit substantial social capital and capacity to rebound, as typified in the Vietnamese community in New Orleans East. Strong social ties create an expectation of return and reconstruction, but delays in the political plans for rebuilding New Orleans create uncertainty for neighborhood recovery efforts.

The last two papers use Katrina as an opportunity for timely and important experiments. Whitt and Wilson use a public goods experiment to examine levels of cooperation among Katrina evacuees in Houston. They investigate whether the ordeal of Katrina eroded group ties and find that group ties remain resilient in the aftermath of disaster, in that participants contribute 40% of their endowment to the public good, in line with traditional public goods experiments. Katrina did not stamp out cooperation, which is consistent with the strong social ties Boettke et al. found in recovering neighborhoods. But stress does limit cooperation; participants with immediate family members still missing contributed a significantly smaller amount to the public good. Finally, Eckel, Grossman, and Milano (EGM) examine the indirect effect of Katrina on student populations outside of the Katrina-affected area to determine the effect of Katrina on charitable giving. The results derived from this experiment can also give some insight into how Katrina evacuees might be received into new communities. EGM find evidence of "Katrina fatigue," in that participants closer to the disaster (Texas as opposed to Minnesota) contribute less when primed with Katrina information before the experiment. This is similar to the results of a nationwide survey reported by Viscusi and Zeckhauser (2006) in which two thirds of Americans oppose extensive assistance if another hurricane were to strike New Orleans again in the near future.

6. Concluding Remarks

In the past 30 years there has been a significant increase in economic losses from hurricanes. Pielke and Landsea (1998) argued that the dramatic increase in losses depends solely on inflation, wealth, and population growth. They noted prophetically that "it is only a matter of time before the nation experiences a $50 billion or greater storm" (p. 630). Simply put, there are more people and wealth in vulnerable coastal areas. The prospect of sea level rise in the coming decades means that already vulnerable low-lying areas will be at even greater risk to storms of even moderate intensity (Category One to Three). Hurricane Katrina has stretched this nation's resources as never before in our effort to protect and sustain the recovery of businesses and a massive displaced population. Wharton Risk Center (2007) argues that we must create innovative risk management mechanisms to deal with future catastrophes. To support well-informed public and private hazard mitigation investment decisions, economists must play a role. Meade and Abbott (2003) described the absence of reliable monetary measures of the gain from public and private mitigation investment as the "missing metric." It is imperative that we develop a more thorough understanding of the effects of severe storms.

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Bradley T. Ewing, * Jamie Brown Kruse, ([dagger]) and Dan Sutter, ([double dagger])

* Jerry S. Rawls College of Business and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX 79409-2101, USA.

([dagger]) Center for Natural Hazards Research. East Carolina University, Greenville, NC, 27858-4353, USA; E-mail krusej@ecu.edu; corresponding author.

([double dagger]) Department of Economics, University of Texas-Pan American, Edinburg, TX, 78539-2999, USA.