August 19, 2019
The costs of weather-related disasters have been growing in recent years. Over the past decade, the United States has spent over $200 billion in off-budget supplemental legislation to fund recovery from disasters such as hurricanes, storms, floods, and wildfires. While climate change is worsening many natural hazards, losses are also increasing from our building and land use decisions. Indeed, one of the most impactful policies to mitigate rising disaster costs are under state and local control: land use decisions and building codes.
While there are local governments that have been leaders in incorporating resilience into development decisions (see here for flood examples), many do very little. For flood, communities in the National Flood Insurance Program must adopt minimum requirements (see here and here) but exceeding these is the exception, not the rule. And despite increasing risks, particularly in coastal areas, several coastal states are actually weakening their building codes, despite demonstrated economic benefits (see here).
In part, this is because there is very little financial incentive to regulate development and building: local governments usually claim all the tax revenues from allowing hazardous development, but pay few of the costs when disasters strike. Those costs often fall on the property owner, who may not have adequate information or understanding of the risks, on insurers, if the damage was covered by a policy, or on the federal taxpayer through disaster assistance. Many broader costs to the community from disasters are reimbursed by FEMA’s Public Assistance Program and, for large disasters that receive additional Congressional appropriations, through disaster block grants from the Department of Housing and Urban Development or appropriations to other agencies (see here).
This misalignment of costs and benefits can distort decision-making. One step to start encouraging local governments to pay more attention to disaster costs is a community resilience policy score. This could be used by insurers to offer more competitive rates in higher scoring areas, by rating agencies in assessing bond ratings for hazard-prone locations (as they are starting to do – for example, see here), or by FEMA in allocating disaster aid (such as in the now abandoned public assistance disaster deductible concept). It could likely spur other uses, as well, since, as the saying goes, “what gets measured gets managed.”
This would not be a resilience index or set of indicators, as explored in many efforts (see here). Such efforts have raised thorny questions about objectives, measurement, comparability, and subjectivity. Instead, this would be a resilience policy score based on actual public policy, on-the-ground implementation and enforcement, and regulatory decisions made by the local government. For instance, it could include whether model codes for different perils had been adopted, what zoning requirements were put in place in high risk areas, and whether regulations for new development and citing of infrastructure incorporated state-of-the art estimates of increasing risk.
This concept is not without precedent. One example is the Firewise Program. Firewise is a community-level program run by the National Fire Protection Association, a non-profit focused on reducing fire losses. Participants undertake a range of activities to reduce wildfire risk in their jurisdiction; these can be tailored to each community. This program is currently being used by the insurer USAA, which provides discounts to policyholders residing in communities that participate in the Firewise program to reflect their lower risk of losses.
Another program that is similar in concept is the Community Rating System (CRS) of the National Flood Insurance Program (NFIP). The CRS rewards communities with points as they adopt flood risk management measures (different activities receive different point levels), and as they accrue a certain number of points, they reach a new level in the program. Each improvement in level is rewarded by discounts on NFIP policies purchased by community members. One challenge with the CRS, however, is that the premium reductions are not actually reflective of lower claims—instead the NFIP has in place a cross-subsidy from other policyholders to those getting CRS discounts. Also, some communities find participation costly and burdensome.
The resilience rating envisioned here would only be rewarded with lower insurance costs when insurers find they are justified, such as USAA and the Firewise program. That means that the adoption of such a metric would need to be accompanied by studies to document the benefits to insurers, as well as impacts on total losses, disaster assistance, and recovery more broadly, for other users. This could help with the concerns voiced by Breckinridge, for example, that current approaches by rating agencies to incorporate climate risk are not transparent, that their metrics are not necessarily material, and that they fail to fully appreciate the full impact of natural disasters.
Essentially, any resilience policy score, to be influential, would need to be seen as credible, salient, and legitimate (see Cash et al. 2003). For example, the public policies included in the score card and the methodology for calculating and adapting them across a country where areas are differentially exposed to various hazards would need to be seen as technically sound. To be viewed as salient, the score must also reflect achievable policies at a local level and linked, through causal studies, to measurable improvements in recovery. And finally, it would need to be calculated by an independent third-party to be seen as legitimate and unbiased and not able to be manipulated.
There are a number of questions that must be answered before a resilient policy score could be created. For instance, should the scores should vary by region or state to reflect variations in hazards and state level policy that influences building and development? Could it work with systems already in place, such as CRS and Firewise? A team of interdisciplinary scholars could tackle the challenges in collaboration with potential user groups to create a useful measure of community policy that could help align incentives for cost-effective investments in risk reduction.