The Economic Toll in Haiti, and Its Implications

Keyword: 
Natural disaster
Topic: 
Environmental Economics
Poverty - Inequality - Aid Effectiveness

The heart-rending images of the catastrophic earthquake that hit Haiti in January 2010 failed to convey the extent of death and destruction brought to the capital Port au Prince and surrounding areas. Estimates of the loss of life indicate that the earthquake killed between 200,000 and 250,000 people. The latter figure exceeds that of any natural disaster worldwide in recent decades, including the Indian Ocean tsunami of 2004. But Haiti is a small country, with fewer than 10 million inhabitants. The quake thus killed between 2% and 3% of the entire population—a staggering blow to any nation. Indeed, no natural disaster in recent history has claimed the lives of such a share of a single country’s population. And Haiti, even before this tragedy, was already the poorest country in the Western Hemisphere.

Table 1: Large Natural Disasters

What of the damage to property—to homes, public buildings and infrastructure, and to the business capital from which Haitians drew their livelihood? As the quake struck so close to the capital, the buildings housing many of the nation’s key institutions--from the presidential palace down--were destroyed or rendered unusable. Much of the country’s productive infrastructure was also located in Port-au-Prince. 10%-15% of the population, or up to one and a half million people, were rendered homeless.

A month before the release of the detailed Post Disaster Need Assessment (PDNA) report we published a paper presenting a first approximation of Haiti’s economic losses based on demographic information and the statistical relationship between the economic loss and the human loss resulting from a natural disaster (Cavallo, Powell and Becerra, 2010).. 

Methodology

Following the literature (Kahn, 2005, Skidmore and Toya, 2007, Cavallo and Noy, 2009), we estimate a model of the form :

(1)  ,

where  is a measure of the dollar amount of direct damages caused by the immediate impact of a disaster in country i at time t. The economic impact of a disaster usually consists of direct consequences on the local economy (e.g., damage to infrastructure, crops, housing) and indirect consequences (e.g. loss of revenues, unemployment, market destabilization). When the information is available in the Emergency Events Database (EM-DAT), the registered figure corresponds to the value of the immediate damage at the time of the event and usually only to the direct damage, expressed in US dollars (current value).  is a vector of control variables of interest that capture the “vulnerability” of the country to disasters (i.e., the conditions which increase the susceptibility of a country to the impact of natural hazards) and the country’s demographic characteristics.  is an independent and identically distributed (iid) error term. 

We first estimate the model for the full sample of events available in the dataset over the timeframe 1970-2008. Next, we use the coefficient estimates α ̂  and β ̂  to predict out of sample the dollar amount of direct damages for the recent earthquake in Haiti. In other words, we replace  in (1) with  and use the coefficient estimates from the model to provide an estimate for . Finally, we use bootstrapping simulation methods to determine the confidence intervals around these predictions. 

Results

The results of the estimates indicate that, for an earthquake that causes 200,000 deaths in a country with Haiti’s characteristics, the estimated damage is US$7.2bn, with 90% confidence intervals between US$4.1bn and US$12.2bn. If the death toll were to reach 250,000, the estimated damage is US$8.1bn, with 90% confidence intervals between US$4.6bn and US$13.9bn. Intermediate numbers give intermediate results. For example, using the official death toll of 230,000 (the estimate as of February 10th, 2010), the estimated damage is US$7.7bn. 

Fig. 1 shows the partial correlation scatter plot between the log of US$ damages (y-axis) and the log of total number of people killed (x-axis). This figure illustrates the strength of the relationship between the two variables after conditioning on the other explanatory variables included in the regression. Furthermore, it shows that while the event in Haiti is indeed very large, even after accounting for the observable characteristics we control for in the regression, the results do not appear to be driven by outliers.

Fig. 1.

Given the nature of the exercise, the results should be interpreted with caution. First, there are conceivably measurement errors in the data, and the model we postulate may be incorrectly specified. Other problems with the empirics may also exist. Second, we cannot know if the experience of past episodes around the world will be relevant for Haiti. Every event is different and, although we control for country and regional-specific characteristics in the regressions, we could have missed one or more important variables. This concern is compounded by the fact that the characteristics of this particular event are quite special: it is the most destructive event a country has ever experienced when measured in terms of the number of people killed as a share of the country’s population (see Table 1), and it has affected the capital city of the country: the centre of commerce, government and communication.

Despite these many caveats, the results were validated by the now-available PDNA. Using a very different methodology, based on an analysis on the ground, the official report estimates economic damages at US$7.9bn and total needs (taking into account the recovery, reconstruction and reorganization of the Haitian State) at US$ 11.5bn. PDNA exercises take time and are costly, and they are also subject to their own list of challenges and potential errors. Therefore, a regression-based estimate that exploits cross-country evidence may be a useful complement for putting the costs of natural disasters into perspective and informing the international community very quickly about the possible costs of reconstruction in the aftermath of such catastrophes.

Implications for Haiti

The estimated reconstruction costs are then greater than the country’s US$6.5bn GDP. Indeed, the devastation was so widespread that reconstruction requires thinking about the nation’s overall development strategy; as many have already left the capital should there be a significant push to decentralize both Government and the private sector? Should there be a significant redeployment of the workforce to new sectors and in new areas? How can the country reforest, avoid re-deforestation, ensure alternative energy sources are available to the population, and become more resilient to natural disasters? How can Haiti grow a more vigorous, prosperous and competitive private sector? 

We may all have our views regarding the answers to these questions but for any decision to be legitimate and sustainable it requires as full participation as possible of the Haitian people. A recent IDB publication, “Beyond Facts”, finds that there is frequently a divide between what a government thinks is best and what people value or consider is best. This divide may be breached by information and monitoring systems to ensure people are content with the actions of their public servants or to alert officials about interventions that would be strongly welcomed. Several cities in Latin America have implemented such systems and they have also been used in respect to specific projects; they are even more important in a situation of substantial construction aimed at consolidating what may amount to a new national development strategy.

Moreover, the amount of money involved goes far beyond what can reasonably be expected from any one country or international agency. Effective coordination between donors, regarding both funding and the reconstruction itself, will be essential. In previous work done by the IDB, donor coordination has been identified as a critical element for aid to be successfully delivered (see Bobba and Powell, 2006). The scale of the efforts required in Haiti over the next several years only underlines this point. Moreover, the inevitable bottlenecks in the supply of goods required for reconstruction coupled with a large influx of aid funds and aid-workers can quickly raise local prices and lead to Dutch-Disease putting at risk new export sectors. Appropriate sequencing, which itself requires excellent coordination, will be of paramount importance.

On the one hand, Haiti’s institutions are notoriously weak; on the other hand, externally imposed structures in a country identified by its proud independence will likely not be considered as legitimate and ultimately will be unlikely to succeed. In effect, if success can be declared when looking back ten years from now, it will be because significant strides have been made in coordinating donors, ensuring legitimate decision-making processes at both the local and national levels and improving governance structures, as significant elements of the reconstruction effort. 

Disclaimer: The views expressed in this article are entirely those of the authors, and no endorsement by the Inter-American Development Bank, its Board of Executive Directors, or the countries they represent is expressed or implied.

References

Bobba, M. and A. Powell (2006) “Multilateral Intermediation of Foreign Aid: What is the Trade-Off for Donor Countries?” Inter-American Working Paper, Research Department, No. 4500.

Cavallo, E., A. Powell and O. Becerra “Estimating the Direct Economic Damages of the Earthquake in Haiti”, Economic Journal, August 2010.

Cavallo, E., and Noy, I. (2009). ‘The Economics of Natural Disasters: A Survey.’ IDB Working Paper 124. Washington, DC, US: Inter-American Development Bank.

Inter-American Development Bank (2008). “Beyond Facts: Understanding Quality of Life“, Development in the Americas.

Kahn, M.E. (2005). ‘The Death Toll from Natural Disasters: The Role of Income, Geography, and Institutions.’ Review of Economics and Statistics 87(2): 271–284.

Scheuren, J-M., Le Polain de Waroux, O., Below, R., Ponserre, S., and Guha-Sapir, D. (2008). Annual Disaster Statistical Review: Numbers and Trends 2007. Brussels: CRED.

Skidmore, M., and Toya, H. (2007). ‘Economic Development and the Impacts of Natural Disasters.’ Economic Letters 94: 20-25.

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