Do Natural Disasters Promote Long-Run Growth?

Beginning of article

I. INTRODUCTION

Risks to life and property exist, in varying degrees, in every country of the world. Numerous studies on the relationship between risk and expected losses and economic decisions are available and generally widely known, (1) but to our knowledge there are no empirical studies that evaluate the effects of natural hazards on long-run economic growth in a macroeconomic framework. (2) Despite the vast empirical literature that examines the linkages between long-run average growth rates, economic policies, and political and institutional factors, the relationship between disaster risk and long-run growth has not been empirically examined.

There is, however, a body of research that has examined the effects of natural disasters on economic variables in the short run. Tol and Leek (1999) provide a summary of the recent studies that assess the immediate repercussions of natural disasters on economic activity. The empirical findings in this literature (Albala-Bertrand, 1993; Dacy and Kunreuther, 1969; Otero and Marti, 1995) report that gross domestic product (GDP) is generally found to increase in the periods immediately following a natural disaster. This result is due to the fact that most of the damage caused by disasters is reflected in the loss of capital and durable goods. Because stocks of capital are not measured in GDP and replacing them is, GDP increases in periods immediately following a natural disaster.

Our article extends the short-run analysis by examining the possible linkages among disasters, investment decisions, total factor productivity, and long-run economic growth. Because disaster risks differ substantially from country to country, it is reasonable to question whether there exists some relationship between disasters and long-run macroeconomic activity. On cursory examination, one might conclude that a higher probability of capital destruction due to natural disasters reduces physical capital investment and therefore curtails long-mn growth. However, such analysis is only partial and may be misleading. Disaster risk may reduce physical capital investment, but disasters also provide an opportunity to update the capital stock, thus encouraging the adoption of new technologies.

Furthermore, an endogenous growth framework also suggests that disaster risk could potentially lead to higher rates of growth. In this type of model individuals invest in physical and human capital, but there is a positive externality associated with human capital accumulation. If disasters reduce the expected return to physical capital, then there is a correspondingly higher relative return to human capital. The higher relative return to human capital may lead to an increased emphasis on human capital investment, which may have a positive effect on growth.

We present some initial evidence regarding the relationship between disasters and economic growth in Figures 1 through 4. These figures show the simple relationship between the number of natural disasters and long-run economic growth using a sample of 89 countries. The vertical axis represents the average annual growth rate of per capita GDP over the 1960-90 period. Data on per capita GDP are taken from Summers and Heston (1994). Along the horizontal axes are four different measures of the propensity for natural disasters. The disaster data in Figures 1 and 3 are historical information from Davis (1992) covering 190 years of the world's worst recorded natural disasters. Figures 2 and 4 represent more current and detailed information on natural disasters events for the period 1960 through 1990 from the Center for Research on the Epidemiology of Disasters (CRED) (EMDAT, 2000). Figures 1 and 2 show the natural log of one plus the total number of disaster events from Davis and CRED, respectively. (3) However, bec ause larger countries may be subject to more disasters, we present the natural log of one plus the number of disasters normalized by land area from Davis and CRED in Figures 3 and 4. All of the figures indicate a clear positive association between the number of disasters and economic growth.

As shown in Table 1, a semilogarithmic regression equation yields a positive and statistically significant relationship between number of disasters and economic growth, explaining as much as 9% of the variation in the growth of per capita GDP. In this simple regression, both the historical disaster measures from Davis (1992) and the recent disaster measures from EMDAT (2000) are significantly correlated with economic growth. These findings are consistent whether we use total disasters or disasters normalized by land area.

In the remainder of this article, we use cross-country variation in natural disasters to estimate their effects on human capital accumulation, physical capital investment, total factor productivity, and economic growth. We demonstrate that the statistical relationship between disasters and economic growth is robust to the inclusion of control variables typically considered important determinants of growth (such as initial income, initial secondary schooling, fertility rate, investment to GDP ratio, trade openness, population, latitude, and a tropics dummy variable). The empirical results also show that climatic disasters are correlated with higher rates of human capital investment and increases in total factor productivity. However, we find no significant correlation between disasters and long-term physical capital accumulation.

In the following section, we present historical and current information on disasters around the world. In section III, we present extensive empirical evidence regarding the relationship between natural disasters and long-run economic growth. In section IV we propose several hypotheses and identify the routes through which disasters affect growth. Finally, we offer our concluding remarks in section V.

II. DISASTERS AND RISK TO LIFE AND PROPERTY

International Differences in Natural Disasters

Although the potential for natural disasters exists nearly everywhere, exposure to catastrophes varies significantly around the world. For example, Jones (1981) compiles data on disasters and finds that a person living in Asia is about 30 times more likely to die in a seismic disaster than one living in Europe. (4) Similarly, Alexander (1993) shows that most hurricanes occur within the tropics between latitudes 30[degrees] N and S, but not within [+ or -]50[degrees] of the equator, where atmospheric disturbances tend to be insufficient to cause them.

Although death tolls vary from year to year, major disasters kill about 140,000 annually worldwide. In Table 2, we present deaths caused by various types of natural disasters by continent. About 95% of the deaths occur in developing countries, but natural catastrophes also have severe impacts on highly developed countries. For example, the occurrence of both geologic and climatic disasters in Japan, Italy, and the United States make these countries particularly vulnerable. According to Alexander (1993), in the United States 30 disasters are declared in an average year, of which floods account for about 40% of property damage and hurricanes and other tropical storms yield 20% of all disaster-related fatalities (Alexander, 1993). As shown in Table 2, Asia is affected most severely by natural disasters both in terms of the number of events and deaths.

Historical Evidence on Natural Disasters

Historically, recovery from extreme disasters, such as region-wide famine caused by severe drought, has been very flow. Capital and working animals were lost and, perhaps more important, skills disappeared with death and outmigration of craftsmen. Full recovery from a severe famine might take as long as 25 years. (5) Before the Industrial Revolution, the impact of natural disasters on capital accumulation among the poor was negligible. The poor built shelters that were expendable and could easily be replaced. However, in disaster-prone regions the wealthy, ignorant of engineering principles, spent enormous sums of money to overdesign their structures to withstand forces well in excess of the likely forces (Alexander, 1993).

Despite the improvements of engineering and construction, the potential for capital destruction is enormous. For example, in 1992 Hurricane Andrew caused damages in southern Florida and Louisiana exceeding $20 billion, but due to effective forecasting and evacuation procedures, only 13 deaths occurred. Japan is highly susceptible to both climatic and geologic natural disasters. The Tokyo area, home to about one-fifth of Japan's population, is in the vicinity of several plate tectonic faults and is especially vulnerable to seismic activity. Shaw (1994) estimates the cost of an earthquake in the Tokyo area equivalent in magnitude to the Great Kanto earthquake of 1923 to be as much as $1.2 trillion. (6) Given that a large earthquake is estimated to occur every 60 years, a disaster of enormous consequence could be imminent. These two examples provide some indication of the enormous potential that exists for disaster-induced capital destruction.

Measuring Disasters

There are many types of potential hazards and the probabilities that these events will occur differ substantially across countries. Although the potential hazards are abundant, we focus on climatic disasters and geologic disasters. In this study, we use two sources of data on natural disasters.

First, historical data on natural disasters come from Davis (1992), who compiles information on the world's worst natural disasters. Some constraints were made in compiling and including natural disasters into our analysis. Davis made an attempt to document all natural disasters through history, but we only include those disasters that occurred within the last 190 years (1800 through 1990). Davis defines the world's worst natural disasters according to both scientific and subjective criteria. Davis made several subjective judgments before including a natural disaster in his compilation. (7) For example, a volcanic eruption of enormous magnitude might be classified by scientific measures as a serious disaster. However, if the eruption were to occur on a remote and sparsely inhabited island, it would not kill many people and destruction of physical capital would be limited. But if the eruption were to occur near a populated city, serious damage would result. There is then a potential that growth would lead to m ore and greater population centers and thus a greater likelihood that Davis would record the event. However, countries that experience relatively high growth are better able to take precautionary steps so that the magnitude of human suffering is less, reducing the likelihood that an event would be recorded.

Were it not for the fact that most of the disasters in the Davis data set occurred prior to the period of analysis, causality between disasters and growth would be in question. However, given that population and economic centers 100-200 years ago were significantly different than they are for the 1960-90 period, Davis's recording of natural disaster events is not systematically biased toward high-growth countries over the 1960-90 period. One advantage of using historical data is that it is arguably exogenous to recent changes in capital accumulation, total factor productivity, and economic growth. We interpret past events as affecting the cultural mindset such that these experiences affect capital accumulation decisions as well as the adoption of new technology. Although the disaster data from Davis (1992) are somewhat crude measures of disaster risk, they should provide an adequate initial estimate of the possible relationships among disasters, investment decisions, total factor productivity, and long-run gr owth.

We also use a second data set from CRED at the Universite Catholicque de Louvain in Brussels, Belgium (EMDAT, 2000). CRED has compiled data on the occurrences and effects of mass disasters in the world from 1900 to the present. CRED makes a concerted effort to validate the contents of the database by citing and cross-referencing sources. CRED also uses specific criteria for determining whether an event is classified as a natural disaster. (8) The database includes information on number of events, damages, numbers affected, and deaths. However, we are reluctant to use data on damages, number affected, and deaths for three reasons. First, data on these factors are not always available. Therefore, an estimation procedure must be used to generate predicted values to be used in place of the missing data. However, such a procedure only provides estimates for the missing data. More important, because total damages increase with income, the damages caused by disasters may be endogenously determined. Similarly, numbers of people affected fall with income, so that low-income countries experience more human casualties and losses. Wealthy countries clearly spend more money on safety in terms of building codes, engineering, and other safety precautions, thereby reducing deaths. On the other hand, wealthy countries also have far more physical capital at risk should a natural event occur, increasing the possible damages. (9) Finally, as noted by Albala-Bertrand (1993), the impacts of disasters are sometimes exaggerated in developing countries to secure international assistance. Thus, data on damages and loss of life are to some degree unreliable.

In our analysis we use the total number of significant events occurring in a country over the 1960-90 period because we believe natural events are the best exogenous measures of disaster risk available. Whether or not a country …