The Limits of Carbon Metrics in Pricing Transition Risk

A review of the lecture “Carbon Transition Risk” Professor Marcin Kacperczyk 13th January 2026.

Carbon transition risk has moved from the margins of sustainability reporting to the centre of financial decision-making. For investors, boards, and regulators, the challenge is no longer whether the transition matters financially, but how to measure its risks in a way that is relevant for pricing, portfolio construction, and governance, rather than merely for disclosure. This tension framed the first public lecture in the 2026 NBS-PRI-ECGI Public Lecture Series, delivered by Marcin Kacperczyk,  who argued that the search for a single “best” carbon metric is misguided and that transition risk is inherently multi-dimensional.

Transition Risk as a Financial, Not Just Environmental, Challenge

The climate transition is a first-order economic issue. Delays in decarbonisation are costly because time matters, while the path forward remains uncertain. Transition risk reflects uncertainty along three closely linked dimensions: technological progress, policy tightness, and timing. These uncertainties affect asset values through two channels. The first is a cash-flow effect, as regulation, innovation, or demand shifts can strand assets or erode revenues. The second is a discount-rate effect, as investor beliefs and preferences evolve and carbon-intensive cash flows are discounted more heavily as climate risk becomes economically and politically salient.

Both channels are forward-looking. Yet much of the measurement infrastructure used in practice relies on backward-looking indicators. This disconnect, between the nature of transition risk and the way it is commonly measured, sits at the heart of many current debates in sustainable finance.

When Emissions Intensity Fails to Capture Priced Risk

Emissions intensity is the most widely used carbon metric. It features prominently in regulatory guidance, disclosure regimes, and portfolio screens, and its appeal is intuitive. By measuring emissions per unit of revenue, intensity captures efficiency and aligns naturally with carbon taxes, technology standards, and regulatory thresholds. For policy implementation, it often makes sense.

Problems arise when emissions intensity is treated as a sufficient measure of financial risk. Implementation metrics are not the same as pricing metrics. A firm can appear “green” on an intensity basis while remaining a very large absolute emitter, and therefore highly exposed to transition shocks. Rankings based on intensity improvements have, at times, included some of Europe’s largest emitters, illustrating how efficiency gains can coexist with rising total emissions.

Recent research by Prof Kacperczyk tests this distinction directly by examining whether emissions intensity alone spans priced transition risk in asset markets. The answer is no. For intensity to fully capture transition risk in prices, several strong conditions would need to hold: firm scale would have to be irrelevant; firms with identical intensity would face identical risk regardless of size; and no other firm characteristics would matter. The evidence shows that these assumptions do not hold empirically. The relationship between carbon exposure and returns varies systematically with firm size, and absolute emissions contain information beyond efficiency. What matters for pricing is not only how clean firms are per dollar of revenue, but how exposed their total cash flows are to transition shocks.

The broader lesson is not that emissions intensity is useless. Rather, it answers a different question. It is well suited to regulatory design and implementation, but insufficient on its own for measuring financial risk.

Averages, Backward-Looking Data, and Hidden Portfolio Exposure

Recognising that multiple firm-level characteristics matter raises a second challenge: aggregation. Portfolio-level transition risk is often summarised using weighted average carbon intensity, a measure that is easy to compute, intuitive, and widely recommended. But averages can be misleading.

Two portfolios can display the same average intensity while having very different risk profiles. One may consist of firms clustered around the mean, while another combines very low- and very high-intensity firms. The latter is more exposed to tail risk from abrupt policy changes or asset stranding, even though the headline number appears identical. Portfolio exposure also depends on correlation structures, sectoral concentration, and geographic clustering, features that averages tend to obscure.

A further complication is that most commonly used metrics are backward-looking, while transition risk is about the future. Practitioners therefore turn to forward-looking proxies, such as green revenue shares, capital expenditure alignment, net-zero commitments, or implied temperature pathways. Each captures a different aspect of expected transition dynamics, and each comes with limitations. Revenue classifications depend on contested definitions of what qualifies as “green”. Capital expenditure data are slow-moving and noisy. Net-zero pledges vary widely in credibility. Temperature alignment metrics are model-dependent and sensitive to assumptions. None can stand alone.

From One-Number Scores to a Dashboard Approach

The lecture ultimately reframed transition-risk measurement as a structural problem rather than one of metric selection. In simplified benchmarks, a single indicator such as emissions intensity can appear sufficient. In real-world markets, however, climate risk is not fully spanned, beliefs about policy and damages differ, and adjustment occurs through multiple channels. Under these conditions, no single firm characteristic can capture equilibrium pricing of transition risk.

This has direct implications for practice. Transition-risk measurement cannot be reduced to compliance or disclosure scores. Metrics must be matched explicitly to decisions, whether the objective is pricing near-term policy shocks, identifying long-term stranding risk, constructing portfolios, or prioritising engagement. The relevant information depends on the horizon, the scenario, and the question being asked.

A dashboard approach follows naturally. Rather than relying on a single headline indicator, investors need to combine measures of scale, exposure, and concentration with forward-looking information on trajectories and credibility. Portfolio-level risk depends not just on averages, but on distributions, correlations, and tail exposure. The task is not to eliminate uncertainty, but to manage it transparently and in a decision-relevant way.

Implications for Practice

The discussion, led by Sara Rosner, broadened the focus from metric design to the wider economic forces reshaping the transition. The debate highlighted how developments over the past five years have complicated earlier transition narratives, including de-globalisation, geopolitical fragmentation, the surge in energy demand linked to artificial intelligence, and the growing economic salience of physical climate risk. Together, these dynamics challenge assumptions embedded in many transition pathways, particularly those relying on sustained policy support and stable incentives. The discussion underscored that transition risk arises precisely because economies are attempting to move away from carbon-intensive activity under these constraints, making it relevant even when viewed narrowly as a financial risk-management problem rather than a purely environmental objective.

A second strand of the discussion examined how forward-looking scenarios and transition frameworks should adapt to tightening carbon budgets and increasing evidence that the 1.5°C target may be missed. Rather than lowering ambition, the debate emphasised the role of ambitious reference targets in sustaining momentum, even if outcomes fall short. Physical risk featured prominently, both as a direct source of economic damage and as a potential catalyst for shifting beliefs and political demand for action. 

Examples from China illustrated this dynamic: early prioritisation of growth gave way to public pressure for cleaner air and water as environmental conditions deteriorated, contributing to policy change and rapid deployment of cleaner technologies. China’s role as a leading producer of low-cost renewables was also discussed as emblematic of the transition’s geopolitical trade-offs, combining cost reductions with new dependencies. The discussion concluded by framing transition risk as inseparable from governance and political economy, reinforcing the need for flexible, multi-dimensional frameworks rather than reliance on any single metric.

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This lecture is part of the NBS-PRI-ECGI Public Lecture Series, a global initiative on sustainable business. Nanyang Business School (NBS), in collaboration with the Principles for Responsible Investment (PRI) and the European Corporate Governance Institute (ECGI), launched this series to foster knowledge exchange between academics, practitioners, and policymakers. As part of this initiative, leading academics present cutting-edge research on sustainability topics, while industry experts moderate discussions, providing real-world insights and facilitating dialogue between research and practice.