Large capital projects are evaluated using the “weighted average cost of capital,” or WACC. Traditionally, WACC is composed of two elements: the cost of debt and the cost of equity. The Dasgupta review on The Economics of Biodiversity, along with the growing consensus in capital markets and financial regulation to account for all risks, makes clear that a new term needs to be added: the cost of nature.

One could argue that the cost of nature is already included in the cost of capital since capital markets anticipate changes in policy and markets. This assumption implies that a portion of the cost of debt and equity is attributable to the use of nature and can be quantitatively estimated. This important insight has allowed Harvard Business School to develop the “Impact Accounting” model, which provides a generally accepted way to measure the cost of nature as part of its measurement of financial, social, and environmental performance.

However, such estimates still undercount the true cost of nature because they are mostly based on the most important policy change that is affecting markets today: pricing carbon. As Dasgupta’s review makes clear, natural capital goes far beyond the planet’s carbon budget, and hence beyond the “triple bottom line,” “stakeholder value,” and other approaches not based in substantive calculation. It is instead important to measure the cost of nature and include it directly in business decision making.

Providers of capital are already including the cost nature in the price of capital they provide and they are raising that cost almost daily. Companies that do not incorporate that cost in their investment committee decisions are therefore underestimating their financial cost. Their primary financial reporting will likely be inaccurate as a result, and by doing so they may be creating a new fiduciary risk. This vulnerability is now well understood by large investment funds that are revising their investment decisions based on green transition plans or new financial projections that include this cost of nature. Financial regulators and central banks will be the next to adopt this approach and this pivot will affect all businesses.

But how? This short article proposes to measure changes to the cost of debt and equity through two sets of quantifiable data:

Changing base prices of capital provision, as providers of capital alter their risk perspective to account for the direct impact of climate change and use of nature; and

Changing tail risk possibilities and risk correlations within project/asset and firm portfolios tied to a potential evolution in pricing and technology capabilities

Our approach is initially to offer an analytical and measurement framework through the capital markets lens, as it most easily allows modelling the impact of carbon markets on the cost of capital. We will then expand to a broader perspective where the cost of nature is affected by more than carbon policies and prices (Figure 1).

Figure: 1 Integrating the cost of nature in the weighted average cost of capital.

Effect on Cost of Debt

The impact of nature on the cost of capital flows through the debt and equity terms in different ways.

For debt, the first effect is captured by already-existing pricing differentials for “green bonds,” reflecting the fact that there is additional supply of capital for projects with a low cost of nature. Several rigorous papers in the past few years have found a robust premium of 5-15 basis points (Baker et al. 2018, Dorfleitner et al. 2021) associated with projects or investments that have a low impact.

The other effect on debt is that the risk of default increases for projects with a particularly high cost of nature, especially those with large carbon effects. That does not double count the green bond premium, since the default term captures the risk of a project becoming a stranded asset in an uncertain future, while the green bond premium captures the difference in supply of capital between a vanilla and a slightly green (or slightly brown) project today. Default risks may materialize on as short a timeframe as five to seven years—for example, if 2030 climate commitments become more fixed and aggressive. That timeframe is well within the lifespan of a large capital investment.

Monte Carlo methods provide a means to price such risks, using several random variables (see Technical Annex, Figure 3). The first variable is the remaining carbon budget, as estimated by Intergovernmental Panel on Climate Change (IPCC) migration pathways, with uncertainties quantified; the other is the policy response to that budget, as quantified in, for example, carbon prices in the EU Emissions Trading System (ETS) or China’s National Emissions Trading Scheme, over the period of the project; and finally, the probability of compensation payments from public authorities. From there, cash flow estimates can be constructed using standard techniques and compared to debt terms. These are the same techniques that BlackRock, the investment fund, used to turn perceived climate risk into precise investment risk.

The Staudinger power plant in Germany. David Brown - stock.adobe.com

As an example, an analysis of coal power plants in Germany simulated the cash flows of the industry under different scenarios for coal’s “phase-out” in the country (Breitenstein et al. 2019). It modelled base loads, pricing, and other factors, and estimated that a 2030 phase-out scenario would lead to the plants becoming unviable in cash-flow terms between 2026 and 2030. Current German policy is a 2038 phase-out, but pressure is growing for the earlier, 2030 date.

As importantly, industry estimates are that if carbon prices under the ETS exceed EUR 80 per ton (if that high), plants become unviable. That price level seemed improbable a few years ago, but no longer. The German government has agreed to compensate plants that are still economical but forced to shut. However, given the demographic and fiscal pressures anticipated by the late 2020s, this type of exit subsidy is increasingly unlikely, which means that firms will have to bear the cost themselves.

Using standard views of carbon budgets, carbon prices, and phase-out dates, a Monte Carlo simulation therefore gives an estimated 14 percent default rate for coal plants. It is perhaps no surprise, then, that in May 2021, coal mine contractors in Australia were unable to secure default or liability insurance. For a non-coal project still drawing on natural capital—such as a firm or project able to service debt up to a carbon price of 120 EUR per ton—the corresponding increase in default risk is still 1 percent (a significant effect in debt underwriting).

Effect on Cost of Equity

For equity, we utilize the standard capital asset pricing model. The cost of nature is already affecting both systemic and individual risks, or the market risk premium and asset-specific betas (an asset beta measures the specific market risk of a company without the burden of debt). Recent research has quantified “carbon betas” for tens of thousands of traded securities, alongside a “carbon factor,” similar to the Fama-French ¹ “size” and “momentum” factors (Görgen et al. 2019). That carbon factor has turned from positive to negative; that is, accounting for new and prospective carbon policies led to adding to the equity risk premium as early as 2015, and has accelerated since.

The carbon factor at a point in time will reflect capital markets’ aggregate view of the then-future evolution of carbon pricing and policy. The carbon factor was most recently estimated in 2019 at a 3 percent premium. Assuming, conservatively, that the 2019-2021 shift in the market’s pricing of carbon risk is equivalent to the largest prior two-year shift, the carbon factor has now likely grown to approximately 3.5 percent. Firm-specific carbon betas range from 0.3 to -1; that is, from a net reduction in the cost of equity of around 1.2 percent for a carbon-positive project to a net increase of 3.5 percent. Within a firm, per-asset betas may have a much wider range, if the asset provides significant diversification in the firm’s portfolio of carbon risks. So, for example, within a firm carrying a high carbon risk (an overall beta of -1), a strongly carbon-positive project may have an asset-specific carbon beta well above the 0.3 maximum found for individual firms (and vice versa for a further carbon-negative project).

Combined Effect

We can now combine these measurable effects to evaluate their overall impact. Consider a long-lived (multidecade) project that incurs some carbon costs with a debt/equity ratio of 30/70 and which becomes unviable at a cost per ton of EUR 100. Then the stranded asset risk under simulation is 3-4 percent, and the carbon beta in the region of 0.7-1, for a carbon equity premium of 2-3 percent. That implies (net of taxes on the cost of debt) a blended impact on the cost of capital of 2.5-3 percent.

That effect might sound small, but it is not. Optimistic forecasts for large mining or industrial projects typically have internal rates of return in the range of 10-20 percent, and project-specific WACCs in the range of 6-10 percent. A 3 percent increase in the cost of capital might shift a project from having a healthy margin of safety to being marginal or unviable. Even for a project with rates of returns in the high teens, a 3 percent increase in the cost of capital might reduce net present value by half.

At a firm level, most industries have a WACC of roughly 6 percent at present, so a portfolio of assets and projects concentrated in high cost-of-nature projects would see an increase in their cost of capital by roughly 50 percent. That will have dramatic effects on enterprise value. For example, for a company growing earnings in the short-term at 10 percent per year and with a terminal growth rate of 3 percent, a change in the cost of capital from 6 percent to 9 percent will halve the company’s value on a discounted cash flow basis.

The converse of these effects is a lower—possibly much lower—cost of capital for projects that replenish natural capital. A project with the full green bond premium, no climate-related default risk, and a carbon beta at the lowest-climate-risk range, or -0.3, would have a reduction in its cost of capital of approximately 0.5 percent. For a company with the same growth rates and base costs of capital as the prior paragraph, this would be the equivalent of a 20 percent increase in present value.

Finally, portfolio effects might create even greater impact, even for projects with otherwise moderate profiles. An investment that significantly replenished natural capital—for example, a high-risk carbon capture project—in a portfolio otherwise concentrated in high cost-of-nature projects, might have a carbon beta of large magnitude, up to -1. That would reduce its cost of capital by as much as 2 percent, or the spread between “investment grade” and “junk” bonds. The difference in cost of capital between such a nature-augmenting project and a nature-depleting one would be approximately 5 percent, matching the most recent estimate of the premium that venture capital earns over public markets (Harris et al. 2020).

From the Cost of Carbon to the Cost of Nature

Our analysis so far has focused exclusively on one part of the cost of nature, the cost of depleting nature’s carbon budget. That is because the cost of carbon is the first of the costs of nature to be incorporated in capital market pricing. It may be that the movement to incorporate the costs of nature in the cost of capital will end there. But the current global policy environment and some of the changes signaled by some private sector leaders do not seem to lead in that direction.

Many of the arguments being developed under pressure of the climate emergency will serve for other costs of nature too. For example, the German member of the European Central Bank governing board, Isabel Schnadel, recently made a general case for central banks to lean against “market neutrality” when significant externalities are underpriced or not priced at all. She did so in the context of shaping the Bank’s market operations to reflect the social cost of carbon. However, the framework of the argument can be applied and may soon be applied to other costs of nature. More generally, participants throughout the capital allocation process, from individual investors through regulators to asset managers, are becoming comfortable with the incorporation of shadow prices for natural assets into their decisions. Such incorporation, increasingly accepted and part of the general fabric of thinking about capital allocation, may easily transfer from carbon into other costs.

If that should happen, the effect on capital costs may be significant. The Dasgupta Review, unfortunately, does not make an explicit estimate of what share of natural capital is comprised by the carbon budget. However, the review does estimate that the consumption rate of the stock of natural capital is 19 percent per year. The Inclusive Wealth Report (Managi and Kumar 2018, on which Dasgupta draws, estimates that the ratio of the total stock of natural capital to the annual cost of carbon depletion is roughly 20:1. Multiplying that by annual consumption yields an estimated ratio of 4:1 between the total cost of our use of nature and the cost of our depletion of our carbon budget. Since the total stock of natural capital includes the carbon budget, that ratio is inclusive. Carrying that ratio over to the carbon-affected WACC estimates above results in a fully loaded “natural capital factor” of 12 percent per annum, of which the non-carbon portion would be 9 percent (the three-fourths over and above carbon).

A theoretical natural capital factor of 12 percent per year is very high, sufficient to zero-out almost all current returns to assets—but that is precisely Dasgupta’s argument; namely, that inclusive wealth has not grown in the past few decades.

Figure 2: Calculations for overall efffect and illustrative projects.

For the CFO, the response to a possible shock of this magnitude, consistent with fiduciary duty, is to make an explicit estimate of its probability (even if small) and then include the probability-weighted effect in financial calculations. For example, if there is only a 5 percent chance that the full cost of nature will be priced by policymakers or capital markets in the lifetime of a project under consideration, then the expected effect of the non-carbon cost of nature on the cost of capital would be 5 percent multiplied by 9 percent, or roughly 0.5 percent. For a long-term project, lasting several decades, that probability might rise to 20 percent or more, and hence an expected capital premium of 2 percent. Adding that to the carbon WACC adjustment of 3-5 percent estimated above yields a full cost of nature effect on the WACC of 5-7 percent for many projects. That is an effect large enough to motivate significant restructuring of a portfolio or a re-think about the type of investments a company undertakes.

Conclusion

Measuring the true cost of nature is a complex and imperfect process. Nevertheless, carbon markets allow us to model or approximate the cost of debt and capital on an industrial project. While one could argue that carbon markets work imperfectly and do not reflect the true cost of carbon, hence making this measurement artificial, the multiplication of public and private initiatives to support a shift toward less carbon emission indicates that financiers and, probably soon, financial regulators will build in the cost of carbon in all WACC calculations. By extension, we think that as natural public goods become scarce, the other cost of nature (for example, the non-carbon cost) will gradually be counted in financial projections.

Decision makers may continue relegating the cost of nature to non-core decision making, or attempt to silo such costs in multiple “bottom line” statements. While an important first step, this approach will still not address the fundamental issue, which is that we are using WACC rates that are less than what they really are. We may choose to ignore this accounting fact, but as financial regulators will probably remind us, this blinkered approach will lead firms to choose investments that may have looked attractive before 2021, but subsequently prove to be financially unviable. The fiduciary responsibility that ensues should not be overlooked.

Conversely, decision makers may start to bring the cost of nature into their core decision making by accounting for its effect on their current and prospective assets, using the same tools that their providers of capital are starting to use. That may also allow the conversation about sustainability and competitiveness to move from a general frame to a practical, quantitative means for assessing trade-offs in the real-world conduct of business.

Rossignol is a Principal Advisor at DAI. Jordan is a Senior Advisor at DAI.

TECHNICAL ANNEX: STRANDED ASSET SIMULATION

The parameters used for the Monte Carlo simulation are as follows (normal distributions unless stated otherwise):

• Carbon budget: 440 GtCO2 mean; 210 GtCO2 standard deviation. Drawn from Damon Matthews et al.’s quantification of the uncertainties in the most recent IPCC scenarios.
• Carbon price, post-2025 long term average: EUR 60 mean; EUR 20 standard deviation; EUR 20 minimum. Based on current long-dated options contracts and recent trends.
• Forced phase-out date for carbon-positive projects: 2050 mean, 5-year standard deviation. Adjusted for simulation of coal projects to 2034 mean, 2-year standard deviation.
• Probability of public compensation if asset is stranded due to regulatory forced closure/phase-out: 95 percent (samples drawn uniformly at random).
• Probability of public compensation if asset is stranded due to changing costs of inputs (such as carbon prices) rendering asset uncompetitive: 50 percent (uniformly at random).

The procedure for each simulation is as follows:

• A sample of the carbon budget is drawn. Based on its distance from the current mean estimate of the carbon budget, the mean of the carbon price and forced phase out dates are adjusted. For example, if the carbon budget is sampled at 230 GtCO2, the mean of the carbon price distribution is adjusted to EUR 80 (one standard deviation).
• A sample of the carbon price and of the forced phase-out date are then drawn from the adjusted distributions for each (that is, the normal distribution with the same standard deviation and the now-adjusted mean).
• The carbon prices and phase out dates are then compared to the values that render the asset stranded. If the asset remains viable, no further steps are taken. If the asset is stranded, whether there is public compensation is drawn uniformly at random and compared to the relevant threshold rates above (that is, 95 percent/50 percent for regulatory / price-based). If the asset is stranded and there is no public compensation, a default is recorded.

For each type of asset considered in the text, 6,000 samples were drawn and whether a default occurred was recorded for each. The default rates reported were then the proportion of samples in which a default occurred. The results for the full set of simulations are illustrated in Figure 3.

Figure 3: Monte Carlo simulation summary for a project that is unviable above EUR 100 per ton.

REFERENCES

Baker, Malcolm, et al. Financing the response to climate change: The pricing and ownership of US green bonds. No. w25194. National Bureau of Economic Research, 2018.

BlackRock Sustainable Investing. Investment and Fiduciary Analysis for Potential Fossil Fuel Divestment: Survey of Divestments. (2020).

Breitenstein, Miriam, et al. “Stranded asset risk and political uncertainty: the impact of the coal phase-out on the German coal industry.” Available at SSRN 3604984 (2020).

Dasgupta, Partha. The Economics of Biodiversity: the Dasgupta Review. (2021).

Damon Matthews, H., Tokarska, K.B., Rogelj, J. et al. An integrated approach to quantifying uncertainties in the remaining carbon budget. Commun Earth Environ 2, 7 (2021).

Dorfleitner, Gregor, Sebastian Utz, and Rongxin Zhang. “The pricing of green bonds: external reviews and the shades of green.” Review of Managerial Science (2021): 1-38.

Görgen, M., Jacob, A., Nerlinger, M., Riordan, R., Rohleder, M., & Wilkens, M. Carbon risk. Available at SSRN 2930897 (2020).

Managi, Shunsuke, and Pushpam Kumar. Inclusive wealth report 2018. Taylor & Francis, 2018.

Harris, Robert S., et al. Has persistence persisted in private equity? Evidence from buyout and venture capital funds. No. w28109. National Bureau of Economic Research, 2020.

Schnadel, Isabel. From market neutrality to market efficiency. ECB DG-Research Symposium “Climate change, financial markets and green growth”. June 14, 2021.

Footnotes

The Fama-French model is an asset pricing model developed in 1992 that expands on capital asset pricing models by adding size risk and value risk factors to asset pricing. ↩