Why do some countries recover faster now from natural hazards than they did before?

By Dr Harvey Hill, scholar – We often read about massive losses in human lives and damage to infrastructure, economic output and the environment due to hurricanes, typhoons, Super Storms, earthquakes and tsunamis. Less often do we read about events that produce less damage and fatalities than similar previous events have in the same region. Two examples of this are: 1) The earthquake that struck Chile in 2010 and 2) The tropical cyclones that regularly make landfall in Bangladesh. Why are the impacts Chile and Bangladesh have experienced less devastating now than in the past? Were the countries simply fortunate or have they increased their resilience?

Since 1970 Bangladesh and its international partners have created and iteratively improved its early warning systems, storm shelters and emergency response organizations. Chile has also consistently updated and enforced its earthquake building standards for structures and infrastructure systems like power generation and delivery grids. What have been the results?

Fatalities from equivalent cyclone events with peak wind speeds in the 225-250 km/hr range and consequent flooding have declined though the Bangladesh population has grown from 66.7 million in 1970 to 147 million in 2007. In 1970 a cyclone caused up to 500,000 fatalities in Bangladesh. 1n 1991 slightly less than 140,000 fatalities and in 2007 resulted in less than 5,000 fatalities, see Figure 1 (Haque et al., 2012). Chile experienced a similar trend with regards to earthquakes.


Fig 1

Figure 1: Fatalities as a percent of population in Bangladesh and Chile due to Tropical Cyclones or Earthquakes, Source, The International emergency database, (EM-DAT and World Bank, (http://www.emdat.be/).


Fig 2

Figure 2: Percent of population in Bangladesh and Chile made homeless due to Tropical Cyclones or Earthquakes, Source, The International emergency database, (EM-DAT and World Bank, (http://www.emdat.be/)

Despite the progress each country has made there appears to be an emerging opportunity to take resilience at the macro-economic level. In 2010, an 8.8 magnitude earthquake severely tested the resilience of Chile’s infrastructure. Though many structures were damaged there were marked improvements over the last major earthquake in 1960 (a 9.5 magnitude earthquake). Not all parts of the infrastructure systems fared equally well. For instance critical elements of the electrical grid were disabled (Figure 3). (Araneda et al., 2010). Electricity were restored in many areas within 48 hours but it took weeks for all users to have their services restored (Ibid). Similar issues were observed for gas, transportation and communication systems as was noted in a report by Risk Management Services:


Fig 3

Figure 3: Vulnerability levels of key parts of the Chilean electrical Grid at the time of the 2010 Maule earthquake where red is vulnerable (Aranado et al., 2010).

“The relatively low casualty count and degree of destruction from the 2010 earthquake demonstrates the success of the Chilean seismic building code in providing superior performance against earthquake ground motions. The geographical concentration of industrial risks, which are highly interdependent on one another illustrates how business interruption loss is compounded over time. The status of reconstruction efforts over a year later – particularly along tsunami-impacted coastlines-highlights the complexities inherent to societal recovery after a catastrophe” (Risk Management Services, 2010).

The impact on the Chilean economy was measured in billions of US dollars (Ibid). It could have been much worse without the proactive steps Chile took between 1960 and 2010 (Barҫena et al., 2010). Bangladesh’s macro-economy also appears to be increasingly resilient to disasters (Benson and Clay, 2002). Given the lesson learned and the emergence of new technologies and datasets is it possible to increase a country’s macro-economic resilience systematically?

What might Systematic Macro-Economic Resilience Look Like?

Recent research indicates that the dominant impact of natural hazards on macro-economies is damage to capital stock, i.e. Infrastructure and infrastructure systems. Secondly the research has found countries with open market economies, high literacy rates, high incomes per capita, healthy foreign exchange reserves and domestic credit have greater resilience than countries without those characteristics. Third, developing countries often cope with the impacts of a disastrous event by relying on remittances from its citizens that have immigrated to other countries and increased foreign aid. (Hochrainer 2009; Noy, 2009).

Other researchers have articulated why such events are so disruptive for the development of smaller less developed countries:

  1. Disasters divert limited national and international foreign aid budgets to disaster relief and reconstruction from public and private investment critical long term growth, and
  2. Complex budget planning processes are disrupted resulting in systematic development of the educational and physical capital required to support growth and diversification in an economy (Benson and Clay, 2004; Mackellar, Freeman, & Ermolieva, 1999).

Applying these findings to Chile and Honduras provides some interesting insights. Chile is considered a middle income country with a highly literate population, healthy foreign exchange reserves and an open economy. As noted previously prior to the 2010 earthquake and tsunami, Chile increased its resilience both physically via its construction standards and financially with purchases of US dollar catastrophe insurance to ensure credit costs were low enough to maintain market access for its export industries (Victoria da Lobo, 2013). Still, Chile experienced significant capital stock and financial losses:


Fig 3-2

Figure 3: Three projected growth paths for Chile after the 2010 earthquake (I 10) assumes ESC 1, 4.2% 2010 GDP growth, ESC 2, 4.5% 2010 GDP Growth and ESC 3, 5% 2010 GDP Growth. The diversion of resources to reconstruction do not immediately return the economy to original capacity (Barҫena et al., 2010, p.16).

In 1998, Honduras suffered a Force 5 hurricane (Mitch) that destroyed 60 % of its capital stock. Foreign aid funding did increase immediately after the event but what is most striking is the role remittances took on as part of the Honduran GDP. In 1997 it was less than 5 % of the GDP by 2008, ten years after Mitch, it was over 20%. The population of Hondurans in the United States rose from approximately 200,000 people to over 790,000 by 2013, including children born in the United States in those families (Lopez, 2013).


Fig 4

Fig 4-2


Figure 4-1 and 4-2: The annual percent of Honduran GDP Foreign Aid and Expatriate Remittances contributed to the Honduran GDP and the number of Honduran immigrants and offspring (World Bank, Pew Research Institute (http://www.pewhispanic.org/2015/09/15/hispanics-of-honduran-origin-in-the-united-states-2013/ph_2015-09-15_hispanic-origins-honduras-01/).


So Why Aren’t We Doing More to Increase the Resilience of Capital Stock and Capital Stock Systems before Disasters Strike?

Decision-makers have not typically made pre-disaster resilience investing a priority for a variety of reasons:

  1. Politicians see little immediate political benefits from such investments,
  2. They perceive there are high risks of losing political capital if the disaster risk reduction actions require direct investments by their electorate , and
  3. Quantifying the value of such large scale integrated systematic investments has been difficult historically (Kelman, 2014; Environmental Risk Management, 2005).

Another reason is the difficulty differentiating between the visible benefits of economic recovery versus the less visible benefits of long term economic growth. Bastiat observed that post-disaster reconstruction only benefits certain sectors such as the construction industry but the overall economy’s total productive capacity is reduced. This has long term impacts implications for a country (Cain, 1995). An adapted schematic developed by Mechler describes the difference between direct and indirect costs (Figure 5).
Fig 5

Figure 5: Natural Disaster Risk and Categories of Potential Disaster Impacts (adapted from Mechler, 2005; Environmental Risk Management, 2005)

Freeman et al. (2002) explored this issue of hazards, capital stock and macro-economic impacts using a Cobb-Douglas production function for Honduras. Like Hochrainer, they concluded that a small low income country like Honduras would have great difficulty rebuilding its capital stock if impacted by an event like Hurricane Mitch. To understand how a natural hazard impacts an economy beyond a statistical relationship, however, requires quantifying how the pathway that links a hazard to infrastructure systems with and without resilience modifications (Figure 6), (Mitch, 2002; Christensen, Sparks and Kostuk, 2005).


Fig 6

Figure 6: Linking Extreme events to Infrastructure systems via landscape pathways (Christensen, Sparks and Kostuk, 2005).


Fig 7

Figure 7: Choluteca Bridge after Hurricane Mitch totally isolated from the River due in part to landslides caused by deforestation (Musi, 1998; Mitch 2002).

Despite the foreign aid, diversion of Honduran government budgets and expatriate remittances the best case scenario is that it took 3 years to get back to the level of capital stock the country at the time Mitch made landfall and 5 years to get to the capital stock it would have had with no disruption assuming its normal growth rate of 1.1% annually (Figure 8). If the country had been able to reduce the impacts to a decline of 2% due to resilience actions rather than the 5% recorded reduction. The recovery times would have improved.


Fig 8

Figure 8: A comparison of possible Honduran GDP growth paths to the actual growth post Hurricane Mitch. World Bank data was the source.

Benson and Clay identified four questions an analytical framework would have to answer to be able to proactively increase the resilience of a macro-economy:

  1. Can the analytical macro-economic framework link natural hazards to the constraint structure of a country or region that policy and decision makers can use to identify the highest vulnerabilities to a country’s macro-economy, society and environment?
  2. Can the framework identify the resilience investments that have the highest probability of maintaining the economy’s long term growth, while maximizing the reduction in fatalities and damage to property?
  3. Can it also be able to describe the point where it is economically better to purchase disaster insurance for public finances and infrastructure?
  4. Finally can it help its citizens understand their responsibilities in terms of personal property and insurance for their residual risk? (Benson, C. and Clay, 2002).

An Approach that might Link Capital Stocks to Long Term GDP Resilience

One attempt to answer those questions is in the paper, From Fatalism to Resilience: Reducing Disaster Impacts Through Systematic Investments. From a risk perspective, (Risk = hazard x vulnerability) the resilience of the macro-economy is contingent on the vulnerability of its capital stock/systems to the natural hazards to which that economy is exposed. They compare the macro-economy under three states: 1) No extra resilience investments and no natural hazard impact, 2) No resilience investments and a natural hazard impact and 3) Resilience investments with a natural hazard impact (Figure 9).


Fig 9

Figure 9: Generic steps to identify vulnerability and resiliency to natural disasters (Hill, Wiener and Warner, 2012)

In their framework they describe the macro-economy as a “profit function”. (Hill, Wiener and Warner, 2012). The paper describes the function in more detail but it basically is made up of the following elements:

The Profit = Outputs x Price of outputs – the costs of inputs x inputs – the cost of risk reduction investments- – insurance premiums for residual risk +α

(Where α represents the uncertainty or variability of the climate and other disruptions outside of the control of the players in the economic area).

The function is constrained by the infrastructure systems (communications, energy, and transportation, etc.), labor quantity and technical capacity of labor, the governance system, environmental conditions, access to capital and markets, and other assets (Hill, Wiener, and Warner, 2012).

Based on the profit function and constraints the economy has at any one time a maximum possible production capacity. The limits of an economy’s productive capacity are the constraints that limit the country’s production possibility frontier (PPF). Over time a country’s PPF evolves as profits are reinvested, people are trained, new markets are accessed, technologies are adopted, and infrastructure is built, etc. The α (in this case a natural hazard event) can reduce the production possibility frontier due to direct changes to capital stock, and indirect impacts such as companies going bankrupt due to lack of liquidity, etc. How much the PPF contracts is a function of how well the extra expenditures on resilience investments reduce the vulnerability of the most valuable parts of the infrastructure systems.


Fig 10

Figure 10: A stylized example of a production possibility frontier with and without disaster risk reduction investments and a natural hazard impact (Florida International University, http://drr.fiu.edu/courses/cost-benefit-analysis-in-disaster-risk-reduction-course/).

Each year then, if an economy is growing, the PPF will be moving outwards. If the resilience of the capital is low then the path can be quite different if a natural hazard event occurs. In Figure 10 three pathways are described. The highest path is the anticipated growth path without damage from a hazardous event. The lowest is the anticipated path after a hazardous event without any additional resilience investments. The middle path is the macro-economy with a systematic application of resilience investments. . The key piece of the of the analysis is to identify what are the core parts of the economy’s constraint structure that have the highest probability of ensuring the most robust current and future potential for the economy’s, safety of its citizens and environmental.


Fig 11

Figure 11: An economy’s growth paths with three production possibility frontiers, 1) No natural hazard, impact, 2) Path impacted by a natural hazard with minimum disaster risk reduction investments and 3) A growth path with damage risk reduction investments impacted by a natural hazard

Applying the framework proposed by Hill, Wiener and Warner would have attempted to identify which parts of the economy’s infrastructure system should be engineered to withstand lower probability higher impact events to maintain the macro-economy’s resilience and ability to recover. Secondly, it would provide guidance as to when to address residual risk with insurance (Figure 11). Interestingly enough Chile did purchase disaster insurance to ensure Chile’s exporters would have access to credit at manageable interest rates post-earthquake and tsunami (Victoria Da Lobo, 2013).


Fig 12

Figure 12: An approach to deciding when the value of investing in Disaster Risk Reduction investments in a system is no longer beneficial and insurance is required for the residual risk.

If we apply the concepts described in figures 10, 11 and 12 to Chile we can see the three paths in terms of proactive risk reduction investments. If Chile had not experienced any earthquakes after the Valdivia earthquake in 1960 its growth path would look like the highest path (Figure 10) even if it had not changed its building codes. However, if it had not changed its building codes with the 2010 earthquake its growth would have looked like the lower pathway in Figure 10. Because of Chile’s consistent application of strict building standards over fifty years ultimately looked more like the middle adaptation pathway in Figure 10. Note the adaptation pathway is not at the same level as the highest path as some key public and private infrastructure systems were damaged.

Is the Framework Proposed Technically Feasible?

In the next article the feasibility of this approach will be discussed in terms of how the integration of remote sensing, geographic information systems and hydrology could be linked to a linear programming model. Examples will also be provided of some preliminary partial applications and potential tools.



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Bárcena, A., Prado, A., López, L., & Samaniego, J. (2010). The Chilean earthquake of 27 February 2010: An overview. United Nations publication. Benson, C., & Clay, E. J. (2004). Understanding the economic and financial impacts of natural disasters (No. 4). World Bank Publications.

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