What are the key debates on BeZero’s risk-adjusted approach to using carbon credits?
Here are some key takeaways
BeZero’s risk-adjusted approach to using carbon credits provides end buyers with a practical tool to build and maintain carbon portfolios in-line with their risk tolerances.
We address feedback and questions from stakeholders including the role of buyers vs issuers, the scale of discounts, and the impact on lower-quality credits.
BeZero took a conservative approach to defining the discount schedule, and we intend to adjust the discount schedule on an annual basis as new data and research emerges.
In September of 2023, BeZero published a white paper introducing our methodology for constructing risk-adjusted, net zero-aligned portfolios of carbon credits using the BeZero Carbon Rating. We introduced a new unit of account, a risk-adjusted tonne of CO2e, that takes into account the inherent risk of a carbon credit, as assessed through its BeZero Carbon Rating. The primary motivation is to provide a framework that gives end buyers a tool to make credible claims when buying and retiring carbon credits
In recent weeks we have discussed the discounting framework with stakeholders across the voluntary carbon market (VCM). This included a webinar on September 28, 2023, presented by Sebastien Cross, BeZero’s co-founder and Chief Innovation Officer presented alongside David Stead, the Head of Technological Carbon Removal from Vertree on the topic.
Feedback from these conversations include a number of interesting questions and debates. Here we lay out our thoughts on some of the most common topics and questions we have encountered.
Is there a risk that this system ends up rewarding bad projects?
a. On the contrary, it penalises lower quality projects. The framework implies that lower rated credits need to be purchased in significantly greater quantities to achieve the same credible claim. In the absence of a price differential this incentivises buyers to purchase higher rated credits.
b. The discount schedule increasingly (in a non-linear way) handicaps poor-quality projects. Moreover, our expectation is that users are also likely to apply a minimum threshold. This would most likely eliminate the worst projects entirely from the claims made by many purchasers.
The case for "discounting" credits at the cost of the buyer means that market pricing should be correlated with ratings - is this the case?
a. We have found evidence that the correlation between price and quality is increasing. However, this is an ongoing process. Ratings are relatively new - the BeZero Carbon Markets platform only launched 18 months ago in April 2022 - and the transition to efficient pricing of quality is not complete. As ratings adoption increases, the market should become more efficient and more accurately reflect quality in the price.
b. We also found some indications that the price to ratings correlation tended to be higher when volumes were stronger. Given the decline in market activity this year, price discovery in the VCM has been weaker too.
c. We should also acknowledge that other factors can drive price such as co-benefits, vintage, regulatory labels, and geographical preference. Nevertheless, the core tenet of quality for a carbon credit should be its carbon efficacy.
This solution applies to the buy side but is this not a supply side problem to be solved by better methodologies and lower issuance? Why are you implying a tonne is not a tonne when a carbon credit has already been certified?
a. Carbon credits are a risk asset. We argue that quality is not binary in the VCM and it is not possible to know with 100% certainty that a tonne is a tonne.
b. Ratings provide an additional risk management layer post-accreditation. The goal is not to relitigate that process. Rather the aim of the proposed discounting framework is to provide a mechanism for ratings to be employed in practice. It recognises that quality and carbon efficacy operate on a spectrum, rather than a binary, which standards by definition cannot.
c. New market standards and improved methodologies are to be welcomed. However, they frequently mask the divergence seen between projects which can drive meaningful differences in ratings. As the market adjusts to price carbon quality properly and the discount schedule is further calibrated the price mechanism should afford an increasing premium to quality. This should lead to a similar outcome as haircutting the supply. We need a market that rewards quality not quantity.
How did you arrive at the values for the discount factors? Rather than take a conservative approach, isn’t it best to aim for accuracy?
a. We have taken a conservative approach to defining the discount schedule, which we believe to be appropriate given the nascency of ratings in the market and the lack of the same historical data to use for calibration. As data on project performance expands, we will be able to calibrate further the discount schedule. Moreover as methodologies, monitoring, reporting, and verification (MRV) and disclosure improve increasingly lower discounts may become more justifiable.
b. However, there will continue to be certain limitations in terms of the empirical data available within carbon markets, as some values cannot be directly measured (e.g. estimating counter-factual scenarios and baselines that cannot be observed empirically). This presents a level of statistical uncertainty, which we take into account via a conservative estimate in the discount factors.
How does discounting in this way solve additionality or leakage risk? Should buyers feel comfortable buying non-additional projects if they are cheap, for example?
a. In reality, applying the discount factor methodology will become increasingly inappropriate as you go further down the rating scale. We note for example that 97% of the projects rated BB or lower to date have notable or significant additionality risk scores. Discounting cannot overcome the risk that a project is non-additional and buyers should continue to use the BeZero Carbon Rating for a full risk assessment of the credits.
b. The non-linear over-purchasing factor implied by the discount rates means it is likely optimal to incorporate a cut off at which point credits of that rating or lower are not considered for the portfolio. This can be introduced as specific labelling (similar to investment grade versus speculative in financial markets) once more data is available to derive it from. In the meantime users should be guided by their own risk tolerance.
In the event of a project being downgraded - do you suggest corporates purchase more for past claims? Or is it just forward looking?
a. Any risk-adjusted claim made using the BeZero Carbon rating discount factors can be adjusted dynamically in line with any subsequent ratings changes. A portfolio used to make a risk-adjusted claim can be rebalanced in the case of an upgrade or downgrade within the portfolio.
b. Over-purchasing single credit types is only one part of the equation for calculating risk-adjusted tonnes. Risk is a dynamic concept for carbon projects. New information can change either current or previous assumptions about a credit’s carbon quality. In order to ensure that a given claim is not overly exposed to changes in a single credit’s risk profile, it is prudent to diversify.
c. The evolution of corporate net zero frameworks, environmental reporting rules, carbon taxes and compliance regimes may over time dictate the extent or period of time over which past claims are adjusted.
What are your next steps for this work?
a. We have published the white paper outlining the current framework and will revisit the topic in an annual report. As new data and research becomes available, we will continue to refine the discounting values.
b. We are actively working to incorporate discounting into the BeZero Carbon Markets Platform which will provide our users with an easy tool to apply discounting to their carbon portfolios.
c. In preparing the paper we have consulted with stakeholders in the market. We are also keen to engage with other interested parties. We will continue to refine both the approach and underlying inputs. We welcome any proposals for collaboration on this topic, either from participants who have inputs or datasets valuable to calibrating the model or those who would like to explore its implementation. Please email email@example.com to get in touch.