US Carbon Transition Risk: The Highwire Act of Municipal Credit Impairment and Climate Justice

by risQ and DPC Data

  • Carbon is a massive financial liability for the U.S.: Using the Biden administration’s Social Cost of Carbon (SCC) of $51 per metric ton of CO2 applied to Scope 1 emissions in the contiguous US, there is ~$294B in annual carbon transition risk liability. In the electricity production sector alone, that liability still stands at ~$116B.
  • Areas with some of the worst physical climate risk contribute the most emissions: Texas and Florida, two states with outsized physical climate change risk, have the highest electricity production Scope 1 CO2 liabilities, with the former totaling $13.5B on its own, or 12% of the US total. Locally, Harris County, TX and Jefferson County, AL lead the way among counties. The former saw significant destructive climate events in recent years, while the latter is legendary in the municipal bond community for its debt-defaulting financial challenges.
  • Municipal debt issuing communities’ carbon transition risk swamps their pension liabilities: Across 334 debt-issuing counties across 5 states, 92% of counties with available pension data have larger total Scope 1 emission liabilities aggregated over all greenhouse gas sectors than pension liabilities — an issue that itself has led the list of municipal market concerns for years.
  • Communities vulnerable to carbon transition risk also have outsized employment risk and education gaps: A socioeconomic vulnerability analysis using all US census tracts shows that communities with the highest per capita electricity emissions are those with the highest levels of risk from an employment sector perspective, have significantly lower educational attainment levels and more health risks.
  • Black populations near power plants suffer from disproportionate health risks: Although the direct relationship between racial settlement patterns and carbon intensive electricity production is complex, education gaps and health risks (themselves being directly correlated to carbon intensity of electricity production) are significantly higher for communities of color.
  • Carbon transition and flood risks present a double-edged sword: For communities with non-zero electricity production, flood risk — which is demonstrably linked to negative outcomes for property value, mortgage delinquency and population loss — is positively correlated with per capita emissions. Communities with high flood risk and significant transition risk are particularly vulnerable to the double-edged climate sword.
  • Municipal debt stakeholders have a crucial role in catalyzing a just transition away from fossil fuels: The combination of federal, state, and local jurisdictions and fixed income investors can and should explicitly incorporate views and data on carbon emissions into risk management and ESG-related decisions. Communities that are currently heavily dependent on fossil fuel — and especially those that are vulnerable from employment, educational, racial, and municipal credit perspectives — can and should be proactively targeted by appropriate public and impact investing capabilities.

Carbon Transition Risk: A Local Problem for Local Economies

There is a useful conceptual parallel to the notion of inflation for municipal obligors with high carbon transition liabilities — regardless of the level of ‘obligorship’ of those liabilities — wherein the cost of living, commercial operations, project financing, and so on increase within a municipality’s taxable boundaries enough to materially impair credit. Carbon-intensive municipal obligors will experience revenue- and cost-line impacts, resulting in inflation in the costs of living and operating for their constituents as a direct function of carbon transition mandates and/or as an indirect function of financial market and social pressures. The inflationary effects of a more stringent environmental regulatory regime are expected to have an impact on a number of sectors — commercial and residential real estate, transportation, electricity production, industrial and agriculture, to name a few large and substantial examples.

In parallel, there is also a social impact to consider in any given carbon transition in the US. The local populations around carbon intensive US locations will bear the brunt of any significant transition but they also would bear the costs of not transitioning. Municipal bond issuers — one hopes — would have an intrinsic responsibility to serve their constituents throughout the local carbon transition journey, but also understand the imperative to take this journey.

With that construct, carbon transition risk becomes both a credit and social impact consideration that the municipal bond ecosystem must navigate, and here we analyze both components to provide that very picture.

Electricity Emissions as a Liability: Data and Approach

Texas and Florida: Carbon Transition Risk to go with their Physical Climate Risk

While state-level analysis is all well and fine, it’s critical to drill down to a local level to make it applicable to the larger municipal bond issuing universe and to the impacts on specific communities. To make this more digestible, a five-state sample of New York, New Jersey, Ohio, Mississippi, and Texas was used. These five have a relatively high percentage of counties that are municipal debt issuers — New Jersey, 21/21 (100.00%); New York, 53/62 (85.48%); Ohio, 70/88 (79.55%); Mississippi, 59/82 (71.95%); Texas, 95/254 (37.40%). Factors related to location (geographic, climate risk exposure, etc.), political landscape, and economic diversity are also considered in the selection of these five states. The states collectively represent ~19% of the total Scope 1 EP sector emissions and their counties ranked on average in the 63rd percentile, nationally, for emissions in the EP sector. For illustrative purposes, we also included Jefferson County AL, given the fact that the county is home to the largest greenhouse gas emitting power plant in the United States (James H. Miller Jr. Electric Generating Plant). It is also well known for its landmark municipal bankruptcy a decade ago, which was partially driven by poor ESG practices. The very presence of a carbon intensive electric utility as a major local taxpayer should raise both credit and ESG concerns.

One of the critical assumptions established when calculating each municipal obligor’s CO2 liability is the social cost of carbon (SCC). The interim figure proposed by the Biden administration is $51 for every metric ton of CO2 (tCO2), which equates to the Obama-era number adjusted for inflation. Figure 2 shows key statistics for a subset of counties. Harris County TX ranks #1 in aggregate emissions with ~67 million tCO2 annually. Applying the SCC figure of $51/tCO2, Harris County’s tCO2 liability equates to $3.4 billion annually. Harris County TX also ranked #1 in total emissions attributable to the EP sector, with 21 million tCO2 equating to a liability of just over $1 billion. Titus, Rusk, Fort Bend, Bexar, and Robertson Counties in Texas ranked 4–8 in tCO2 liability, highlighting the fact that counties in Texas generally have the highest aggregate exposure to tCO2 liability originating in the electricity production sector.

Figure 1: State-level population and emissions figures for all contiguous US states plus the District of Columbia, with focal states highlighted.
Figure 2: Rankings (top) and values of absolute tCO2 liability $ figures (bottom) for selected counties across the 5-state group, as well as tCO2 liabilities denominated in terms of each county’s assets, revenues, and assessed values, according to each county’s most recent year of reported data.

For counties in our five selected states with non-zero Scope 1 EP emissions, here are some numbers that certainly put localized carbon liabilities in context:

● ~13% of counties (23/178) for which we have total assets data show EP-based transition liabilities exceeding total assets

● ~20% of counties (33/169) for which we have total liabilities data show EP-based transition liabilities exceeding total liabilities.

● ~30% of counties (53/178) for which we have annual revenues data show EP-based transition liabilities exceeding annual revenues.

● ~38% of counties (51/134) for which we have direct debt data show EP-based transition liabilities exceeding direct debt.

● ~43% of counties (52/122) for which we have pension liabilities data show EP-based transition liabilities exceeding pension liabilities.

If we expand this beyond Scope 1 EP emissions to also include transportation, industry, and residential & commercial categories, the carbon liabilities of local economies, their infrastructure and their populations become even more stark:

● ~19% of counties (57/308) for which we have total assets data show total Scope 1 transition liabilities exceeding total assets

● ~37% of counties (106/286) for which we have total liabilities data show total Scope 1 transition liabilities exceeding total liabilities.

● ~70% of counties (214/308) for which we have annual revenues data show total Scope 1 transition liabilities exceeding annual revenues.

● ~74% of counties (171/231) for which we have direct debt data show total Scope 1 transition liabilities exceeding direct debt.

● ~92% of counties (200/217) for which we have pension liabilities data show total Scope 1 transition liabilities exceeding pension liabilities.

Figure 3: Population-weighted dot plot of counties in the 5-state group (+ Jefferson County AL); EP tCO2 liability is provided on the y-axis, and total county assets on the x-axis. Counties in the top left represent those that are most vulnerable.

Figure 3 shows the relationship between EP tCO2 liabilities and total county assets across all 5 focal states. While Harris County TX ranks #1 across the 5 states in total emissions attributable to the electricity production sector, it ranks just #78 when those emissions are denominated in terms of total assets (6.8% of total assets) and #83 when denominated in terms of assessed value (0.2% of assessed value). Across the counties for which DPC DATA has total asset values ($), Adams County OH ranked #10 in annual EP emissions, but #1 in terms of tCO2 liability / total assets = 2,819%. Denominating CO2 liability in terms of total assessed value rearranges the rankings substantially. Across the counties for which DPC DATA has total assessed values ($), Gallia County OH ranks #1 with 79.8% tCO2 liability / Total Assets.

The Appendix dives deeper into 4 exemplary counties with significant Scope 1 EP footprints to illustrate differences in the challenges communities with varying physical climate risk and socioeconomic profiles will face.

We’ll return to the credit implications of carbon liability to municipal bond issuers. Before we do that, the localized social impact should also be considered. After all, what is a municipal bond issuer unless it best serves the needs of the local population?

Socioeconomic Vulnerability & Electricity Production

The most obvious and intuitive social implications of EP emissions are with respect to health, and the data supports that the localized populations indeed have outsized health challenges. Figure 4 shows that the Health Obstacle Score, a 0–100 score that increases as the population living in a tract is more often without health insurance and faces higher levels of underlying health conditions including obesity, high cholesterol, and asthma, among others, is also correlated with higher per capita EP emissions (Spearman rank correlation = 0.21). The same data also shows that the communities with higher Health Obstacle Scores are higher percentage Black residents on average (Spearman rank correlation = 0.32). Mitigation of emissions will only serve these populations well from a health perspective.

Figure 4: Using all census tracts (N=9,380) with non-zero electricity production emissions, per capita emissions are log-transformed and then grouped into 5 bins with a simple univariate k-means clustering algorithm. Distributions of risQ’s Health Obstacle Score are shown for each emissions bin. Each point is a census tract, colored by percentage of population that is white alone and sized by population density.

Of course, there will also be economic challenges to navigate for the same local populations. Figure 5 shows that the At-Risk Employment Sector Score, a 0–100 score that increases as the population living in a tract is more heavily weighted toward mining, oil & gas, utilities, construction, agriculture, and service sectors, is most strongly correlated with per capita emissions (Spearman rank correlation = 0.27). This relationship is also intuitive and obvious, and it has clear risk implications for especially the communities with the highest scores. When carbon intensive electricity plants are decommissioned without employment transition programs, plans, and funding in place, those communities will suffer the most. Related to this employment transition, Figure 6 shows that the Low Educational Attainment Score, a 0–100 score that increases as the population living in a tract has a higher concentration of population that has little or no college education and lower high school and GED diploma rates, is also correlated with per capita emissions (Spearman rank correlation = 0.21). Many tracts with the lowest scores and highest electricity emissions tend to have higher percentage non-white populations. Low education levels will compound vulnerability in the employment transition challenge, where many communities disproportionately of color may be most likely to face more hurdles when plants decommission. Increasing percentage of Black, Latino, and Native American populations are modestly but significantly correlated with increasing Low Educational Attainment Score (Spearman rank correlations of 0.15, 0.11, and 0.13, respectively).

Figure 5: The same is shown as Figure 4 but for the At-Risk Employment Score.
Figure 6: The same is shown as Figure 4 but for the Low Educational Attainment Score.

Finally, there is an additional interaction term between climate risk and social impact to be considered which also highlights the critical transition that must be managed for these EP-proximate populations. Our Flood risQ Score measures risk coming from inland and non-hurricane coastal flood on a 0–5 scale, where every 1-point increase translates to an approximate doubling in financial risk. We have shown previously that the Flood risQ Score correlates with negative property value growth, mortgage delinquency, and reduced population growth outcomes. Figure 7 shows that on average, for tracts with non-zero Scope 1 EP emissions, the Flood risQ Score is positively correlated with per capita tCO2 (Spearman rank correlation = 0.15). This is intuitive given that water was a key site-selection criteria for power generation, as it is needed for cooling towers as well as for ease of access to fossil fuel shipping channels. In many of these locations, we also know that FEMA SFHA flood zones underrepresent total flood risk and underserve minority communities. There is already significant carbon transition risk in these locations, but as climate change increases flooding frequency and severity, these areas will face climate transition and either investment in resilience or managed retreat. Ironically, just as Florida and Texas have high EP Scope 1 emissions and are ground zero for climate risk in the US, local communities with both high EP carbon footprints are inadvertently — at least for them — fueling their own future flood risk via the resulting climate change.

“Double-whammy” does not do justice to the extent of the total climate burden placed on vulnerable communities. What are the collective implications to consider for those in the municipal bond debt and/or ESG ecosystems?

Figure 7: The same is shown as Figure 4 but for the Flood risQ Score.

Insights for US Fixed Income Participants

● Reduced demand for fossil fuel-based electricity and increased competition with renewables-based energy producers, potentially leading to reduced revenues and market share erosion for large power company taxpayers. This would flow through to materially reduced county tax revenues and assessed values at the generation locations.

● Second derivative impacts on carbon-intensive electricity production counties include job loss, slowing economic activity, and migratory outflows as jobs and taxpayers leave counties. Depending on the level of localized distribution of electricity from fossil fuel generation assets, there is also the potential for higher electricity costs from emissions mitigation or cap-and-trade to flow through to the cost lines of the local economy and population, neither of which will be beneficial to long-term growth for the municipality.

● Potential credit positive includes capital inflows from federal- and state-levels directed towards investments in renewable energy plants and infrastructure that could stimulate economic activity.

Looking at historical precedent for carbon transition and environmental regulatory exposure impacting municipal credit:

● Campbell County WY: A 2019 Brookings Institute study linked the collapse of the coal industry to the inability of coal-dependent communities to service debt obligations. Campbell County WY was one cited example, wherein the County’s assessed value dropped from $6.2 billion in the 2015–2016 fiscal year down to $4.19 billion for the 2017–2018 fiscal year, driven primarily by falling coal revenues.

● State of Illinois: Residents of Illinois have historically benefited from the State’s relatively cheap electricity — in 2019, the average price for electricity in Illinois was 9.56 cents/kWh, approximately 9.3% below the national average. Pending state climate legislation is aimed at closing all coal plants in the state by 2035 and natural-gas plants by 2045, a policy that is expected to hike rates on consumers and businesses in the State. Some estimates have placed the initial hit via electricity cost increase on businesses and municipalities was going to be around $700 million annually.

● Jefferson County AL: In the early 2000s, Jefferson started issuing debt to finance improvements to its sewer system to comply with an order from the Environmental Protection Agency (EPA). The EPA had accused Jefferson of dumping raw sewage into nearby rivers and mandated that the County expand and repair its sewer system. As a result of corrupt governance and the 2008 financial crisis, Jefferson failed to service these debt obligations and ultimately filed for Chapter 9 bankruptcy. At the time, it was the largest municipal bankruptcy in US history, totaling more than $4 billion (Detroit’s bankruptcy broke that record in 2013, with a value estimated at $18–20 billion). Poor environmental standards still persist in Jefferson, which is home to the largest greenhouse gas emitting power plant in the United States, the James H. Miller Jr. Electric Generating Plant, and was recently given a grade of ‘F’ by the American Lung Association for its ozone levels. The owner of the Miller plant — Alabama Power — is responsible for ~6.5% of the county’s total assessed value according to Jefferson’s most recent financial disclosure.

All that said, the US municipal market has a clear role and responsibility to play in catalyzing the transition away from fossil fuels. The latest UN report is dire and the most urgent yet, calling for action now. Debt investors have the leverage to pressure issuers/utilities and the capital and apparatus to fund the transition away from fossil fuels. In the bigger (more abstract) picture, investors should also have the self-interest to do so — more fossil fuel burning equates to practically permanent increases in property and GDP losses from physical climate risk. risQ’s recent work makes the difference between financial losses from wildfires and flooding under more and less carbon intensive near term futures clear — our current carbon intensive trajectory is expected to lead to ~+8% property losses from wildfire and ~+19% from inland flooding by 2050 compared to today, to name just a couple of the many physical risks that will continue to worsen as we continue with business as usual.

The on-going saga in Illinois reveals the political and economic complexity in actually doing so on a practical level: utility operators and labor unions pushed back on a state-backed clean energy package that included early bond repayment to decommission the two plants. Ratepayer-backed bond refinancing is one potential avenue to accelerating the retirement of fossil fuel intensive power plants in a way that can be structured to be equitable to ratepayers and can generate transition funding for workers with jobs at risk from decommissioning. One recent successful case study can be found for the 2018 retirement of the Pleasant Prairie plant in Wisconsin.

US municipal market investors, especially those with ESG, Social Impact or Responsible Investing mandates and genuine strategies, can advocate for state-level legislation to accelerate the transition to clean energy that is equitable to people facing employment risk and those whose property values might suffer. State and federal investment should be weighted toward those often historically marginalized communities that both will be impacted by the economic implications of carbon transition and are comprised of populations least capable of doing so due to limited individual and collective financial and infrastructural resources; the Justice40 initiative holds significant promise in this regard. A focus on investment in the relevant school districts will enhance the local populations forward-facing employment. Investment in flood resilience projects will help shore up potential losses in property value. Ensuring health care is available via hospital systems serving these locations, many of which are municipal bond issuers. These are all tangible approaches that federal, state, and local authorities as well as fixed income and social conscious investors can catalyze and contribute to.

Appendix

The Social Cost of Carbon

County-Level Case Studies

New York: Nassau County

The county also has a Flood risQ Score of 3.7 out of 5.0, putting it at the higher end of US flood risk. Median household income and median monthly housing costs both rank 100th percentile nationally — making the county’s Housing Unaffordability Score, which increases as income is higher relative to housing costs, of 84 out of 100. So, although the county is affluent, both physical and carbon transition climate risks pose eventual threats to property values.

Ohio: Gallia County

The county’s Flood risQ Score is high at 4.2 and stands at the 98th percentile nationally for inland flood driven GDP impairment risk. In addition, ~21% (92nd percentile nationally) of the county’s population is below the poverty line, and the At-Risk Employment Sector score is 97 of 100 given that it ranks highest in the nation in terms of percent employment in the utilities sector. Gallia County is clearly one of the most financially and socially vulnerable places in the US to both physical climate risk and carbon transition risk.

Texas: Titus County

By 2030, risQ’s drought model projects that Titus County is expected to experience mild to severe drought conditions ~38–51% of the time (85th percentile nationally), compared to ~30% in the past few decades. The county is also broadly socioeconomically vulnerable, with a Social Impact Score of 81, a Health Obstacle Score of 78, an At-Risk Employment Sector Risk Score of 94 and a ~42% Latino population. In total, Titus County is another distinct example of one that is acutely vulnerable to both physical climate and carbon transition risks.

Mississippi: Attala County

By 2030, risQ’s drought model projects that Attala County is expected to experience mild to severe drought conditions ~34–44% of the time, compared to ~30% in the recent past. The county has a Social Impact Score of 92 of 100, an At-Risk Employment Sector Score of 95 of 100, a Health Obstacle Score of 92, and a population that is ~43% Black (60th percentile in Mississippi, 93rd percentile nationally).

We quantify climate risk, carbon transition risk and social impact for US Fixed Income, covering the full municipal bond and MBS universes

We quantify climate risk, carbon transition risk and social impact for US Fixed Income, covering the full municipal bond and MBS universes