- Our model projects that the effects of climate change — such as heat, storms and flooding — may pose increasing risks to investments. New risks may emerge or the severity may increase in southern and coastal locations in the U.S.
- Marrying asset locations and cost profiles to climate risk data may provide deeper insight into the physical risks facing U.S. corporate issuers.
- A map that incorporates both climate data and economic activity may be useful for assessing risks to other sub-asset classes such as municipal bonds, where it can be hard to calculate the potential costs from physical risks.
Climate change is expected to increase the frequency and severity of physical climate risks such as extreme temperatures, tropical cyclones, torrential rainfall and flooding in many regions around the world, threatening lives and destroying structures and infrastructure.1,2 The wildfires in California3 and highly active 2020 Atlantic hurricane season4 are just two examples of what this can look like. Over time, the implications for investment portfolios could be considerable, and it’s not necessarily obvious where new risks will materialize if the climate continues to become more extreme.
To identify emerging climate risk hotspots in the United States, we combined climate data, asset and facility locations and the potential costs to individual facilities from physical risks, which we call “cost profiles.” We found that company facilities in some regions may be facing significantly increased exposure to hazards like flooding and extreme heat, while in a few places they could see reductions. The marriage of these data sets could provide useful insights into noncorporate sub-asset classes, such as municipal bonds, where information about the issuers may be scarcer.
Where the Emerging Hot Spots Are
Location data is useful for understanding where and how natural hazards may evolve. Adding data about where companies actually have assets — factories, infrastructure, offices, etc. — and how their cost profiles could be affected by increasing or decreasing physical risks over time can provide a more fine-grained picture of where investment risks might lurk. We identified the locations of facilities owned by constituents of the MSCI ACWI Investable Market Index (IMI) as of May 2020 and analyzed what costs those facilities might incur between now and 2035 due to changing physical climate risks. Using this combination of data, we were able to compile a physical risk map that reflects the presence and cost profile of corporate assets as well as changing natural hazards.
This combined map, shown below, reflects a high relative increase of aggregated risk for ACWI IMI assets located in the southern United States as well as coastal areas. This result is unsurprising given the growing frequency of storms and storm-related flooding as well as heat, combined with the density of high-value facilities. Using our Climate Value-at-Risk (VaR) model, we also see that some areas may be more impacted by certain hazards than others and a few may become less risky — mainly in the north, where a warming planet may mean there will be less snow and cold.
Emerging Hot Spots for Physical Climate Risks in the US
The physical climate risk aggregate for the U.S. based on the MSCI ACWI IMI is given in the upper risk map. The bottom maps show the estimated risk for two selected individual risks (heat and tropical cyclone). Results are aggregated to the U.S. county level. Source: MSCI ESG Research. Data as of July 2020.
Beyond Corporates: Insights Across Asset Classes
It can be hard to calculate cost profiles from physical risks for sub-asset classes such as municipal bonds. But if we calculate location-based risk that translates potential physical impacts into economic fallout in the area, we may gain more insight into the scope of risk facing municipal bond investors.
In the exhibit below, we marked the locations of a sample5 of municipal bond issuers on a map showing (at the county level) how our Climate VaR model projects that physical risk may change over the next 15 years. It is important to keep in mind that these overall assessments reflect exposure to multiple possible hazards, ranging from extreme heat to storms to severe cold and snow. If we compare, for example, Miami-Dade County, Florida, with Clark County, Washington, we can see that the future of their physical climate risks looks very different. While Miami-Dade is projected to see a sharp increase in tropical cyclones and heat, Clark County may experience an overall decline in risk as its weather moderates, resulting in less cold and precipitation.
Mapping Potential Risks for US Municipal Bond Issuers
|Heat||Low Risk Increase||Clark County, Wash.||High Risk Increase||Miami-Dade County, Fla.|
|Cold||Risk Reduction||No change/No score|
|Precipitation||Risk Reduction||Medium Risk Increase|
|Snow||No change/No score||No change/No score|
|Wind||No change/No score||No change/No score|
|Tropical Cyclone||No change/No score||Very High Risk Increase|
|Coastal Flood||No change/No score||Low Risk Increase|
|Aggregated Risk||Risk Reduction||High Risk Increase|
The map depicts the geocoded locations of a sample of municipal bond issuers in the aggregated risk score map. Below, the table shows the breakdown in risk scores for these two sample issuers. Source: MSCI ESG Research. Data as of July 2020.
Marrying asset location and cost profile data with projections of changing physical climate hazards could provide investors with a more nuanced and granular look at physical risks facing corporate issuers. The most significant future risks may be where hazards become more severe and where companies have operations or assets that would be expensive to lose, repair or replace. Perhaps equally important, this analysis may also offer insight into climate risks faced by other types of issuers, such as municipalities, where cost profiles can be difficult to assess.
1National Academies of Sciences, Engineering, and Medicine. 2016. Attribution of Extreme Weather Events in the Context of Climate Change.
2Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor and P.M. Midgley (eds.). 2012. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. Intergovernmental Panel on Climate Change (IPCC).
3Yoon, J. H., S.-Y. S. Wang, R. R. Gillies, L. Hipps, B. Kravitz and P. J. Rasch. 2015. “Extreme Fire Season in California: A Glimpse into the Future?” Special supplement to the Bulletin of the American Meteorological Society.
4Estrada, F., Botzen, W. and Tol, R. 2015. “Economic losses from US hurricanes consistent with an influence from climate change.” Nature Geoscience.
5The sample was designed to maximize the variability of physical risk scores.
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