National Academies Press: OpenBook

The Impacts of Natural Disasters: A Framework for Loss Estimation (1999)

Chapter: 4 Conclusions and Recommendations

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Suggested Citation:"4 Conclusions and Recommendations." National Research Council. 1999. The Impacts of Natural Disasters: A Framework for Loss Estimation. Washington, DC: The National Academies Press. doi: 10.17226/6425.
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4
Conclusions and Recommendations

This report has explained the gaps in our knowledge of natural disaster losses and why these gaps should be filled. Poor knowledge of the resulting economic losses hinders implementation of effective disaster mitigation policies and emergency response programs. Better loss estimates would benefit federal, state, and local governments, insurers, scientists and researchers, and private citizens (both as taxpayers and insurance purchasers).

It is clear that data on economic losses of natural disasters to the nation are incomplete and spread widely across the public and private sectors. Information on both direct and indirect costs is lacking. If data on uninsured direct losses are limited, our understanding of indirect losses is even more incomplete. These indirect losses are clearly difficult to identify and measure. However, in large disasters they may be significant and, within the immediately affected regions, potentially greater than the direct losses due to physical destruction, especially in large disasters.

Losses Versus Costs

In generating a national indicator of disaster damage, the focus should be upon the losses resulting from disasters, rather than costs. Losses encompass a broader set of damages than costs. Losses include direct physical destruction to property, infrastructure, and crops, plus indirect losses that are the consequence of disasters, such as temporary unemployment and lost business. Costs typically refer only to cash payouts from insurers and governments. The term "losses," as defined above, better portrays the true economic impacts of disasters.

Suggested Citation:"4 Conclusions and Recommendations." National Research Council. 1999. The Impacts of Natural Disasters: A Framework for Loss Estimation. Washington, DC: The National Academies Press. doi: 10.17226/6425.
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Direct Losses: Data Collection, Reporting, and Agency and Organizational Roles

One step toward producing more complete loss estimates would be to assign one agency of the federal government to compile a comprehensive data base identifying the direct costs of natural disasters, as well as the individuals and groups who bear these costs. These data should be collected according to the framework described in Chapter 2, for each natural disaster exceeding a given dollar loss threshold. The U.S. Department of Commerce's Bureau of Economic Analysis appears to have the capabilities to compile such a data base, with considerable input and assistance from FEMA and other relevant federal agencies. Whatever agency is selected should be given sufficient resources to accomplish this assignment.

The recommended loss estimate data base would be compiled from many sources, including organizations such as Property Claims Services and the Institute for Business and Home Safety (which compile data on paid insurance claims) and other federal, state, and local agencies. The assistance of relevant professional associations, such as the National Association of Insurance Commissioners, should be enlisted to obtain other relevant data. A synthesis report containing data on disaster losses should be published periodically, preferably annually. One way the federal government might make sure it receives at least the state and local data is by amending the Stafford Act, requiring the data to be submitted as a condition for future federal disaster aid.

A related recommendation is for the federal Office of Management and Budget, with advice from FEMA, to develop annual, comprehensive estimates of the payouts for the direct losses (due directly physical damage) made by federal agencies. These data should be divided into at least four categories:

  1. compensation payments to individuals and businesses (including subsidies on loans to help cover disaster-related expenses);
  2. response costs;
  3. losses to government-owned infrastructure (including state and local costs that are reimbursed by the federal government); and,
  4. payouts from federal disaster insurance programs (with annual premiums shown separately).

These data should be assembled for some historic period in order to provide information of trends of disaster losses and payouts. Such an effort is critical if the federal government and policymakers are to better plan for future disaster-related expenditures, including mitigation programs and activities.

The largest current gap in direct loss data involves uninsured losses borne by businesses and individuals. These data might be obtained through post-event sampling (in large disasters) and extrapolating these losses from other data

Suggested Citation:"4 Conclusions and Recommendations." National Research Council. 1999. The Impacts of Natural Disasters: A Framework for Loss Estimation. Washington, DC: The National Academies Press. doi: 10.17226/6425.
×

bases. Data from loan applicants to the SBA's disaster relief program or data from insurers like PCS would indicate the deductibles paid by insured businesses and individuals.

Indirect Losses: Modeling the Losses and Constructing a Loss Data Base

Indirect losses in natural disasters stem from the consequences of physical damage (direct losses). Physical damages in disasters typically initiate events that alter economic flows. Businesses may be disrupted after a disaster due to damaged infrastructure (power, water, transportation, communications), and many workers may be temporarily unemployed. These indirect losses have not been studied or measured as closely as direct losses, largely because they are notoriously difficult to identify and accurately measure.

Due to the limited sources of indirect loss data, statistical models are often used to compile indirect loss estimates. Though these models may help address problems due to a lack of available data, they must become more reliable if they are to be used as guides in setting mitigation and other hazard-related policies.

If this is to occur, however, accurate, firsthand (primary) data on indirect losses must be available for model calibration and validation. The recommended data collection and coordination program should thus also include surveys for the collection of detailed primary data on indirect economic losses from recent disasters (again, sufficient resources for this effort must be budgeted). Once a sufficiently reliable data base of these indirect losses has been generated, the agency should continue to collect indirect loss data on large disasters—those with model estimates of greater than $10 billion in losses. While the indirect loss data base is being constructed, efforts toward more effective uses of secondary data (data generated for purposes other than indirect loss estimation, such as unemployment insurance payouts) should be continued. We thus recommend that an assessment of methods for estimating indirect losses with secondary data be conducted.

It is important to understand the timing of economic disruptions that trigger indirect losses in order to plan for efficient emergency responses and to assess the cost-effectiveness of alternate mitigation strategies. The committee recommends that a microsimulation model be developed to create a timeline of regional commercial and industrial closures. Other models that should be devised include a formal restoration model and a comprehensive indirect loss model.

Suggested Citation:"4 Conclusions and Recommendations." National Research Council. 1999. The Impacts of Natural Disasters: A Framework for Loss Estimation. Washington, DC: The National Academies Press. doi: 10.17226/6425.
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Moving Toward Better Knowledge of Disaster Losses

The lack of accurate information on these losses is a barrier to more effective hazard mitigation. As a step toward improving mitigation programs, efforts at centralizing these data and compiling better loss estimates must be strengthened. The federal government and private sector should combine their knowledge and data in providing better estimates of direct losses. The federal government must mount and back a significant data collection and research effort if better estimates of losses due to disasters are to be compiled, especially indirect losses. With a strong commitment, this could be accomplished within the next ten years. Until relatively accurate estimates are available, the true economic losses in natural disasters will remain poorly understood and the benefits of disaster mitigation activities only imprecisely evaluated.

Suggested Citation:"4 Conclusions and Recommendations." National Research Council. 1999. The Impacts of Natural Disasters: A Framework for Loss Estimation. Washington, DC: The National Academies Press. doi: 10.17226/6425.
×
Page 45
Suggested Citation:"4 Conclusions and Recommendations." National Research Council. 1999. The Impacts of Natural Disasters: A Framework for Loss Estimation. Washington, DC: The National Academies Press. doi: 10.17226/6425.
×
Page 46
Suggested Citation:"4 Conclusions and Recommendations." National Research Council. 1999. The Impacts of Natural Disasters: A Framework for Loss Estimation. Washington, DC: The National Academies Press. doi: 10.17226/6425.
×
Page 47
Suggested Citation:"4 Conclusions and Recommendations." National Research Council. 1999. The Impacts of Natural Disasters: A Framework for Loss Estimation. Washington, DC: The National Academies Press. doi: 10.17226/6425.
×
Page 48
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We in the United States have almost come to accept natural disasters as part of our nation's social fabric. News of property damage, economic and social disruption, and injuries follow earthquakes, fires, floods and hurricanes. Surprisingly, however, the total losses that follow these natural disasters are not consistently calculated. We have no formal system in either the public or private sector for compiling this information. The National Academies recommends what types of data should be assembled and tracked.

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