Integrating sustainability into climate finance by quantifying the co-benefits and market impact of carbon projects

The paper addresses how sustainability co-benefits, particularly at the local/community level, are valued by climate finance markets. While climate finance is crucial for achieving both emissions reductions and broader sustainable development goals (SDGs), the valuation of non-carbon co-benefits by market actors remains poorly understood. Co-benefits such as improved air quality, livelihoods, and local jobs are often more tangible to communities than carbon benefits and can motivate political support. However, co-benefits are difficult to measure, reporting is inconsistent, and comprehensive global assessments are lacking. Prior work focuses either on qualitative identification of co-benefits or on a narrow set of quantitative indicators, leaving a gap in understanding investor valuation. Using the Clean Development Mechanism (CDM) as an empirical setting with nearly 8000 projects and tradable CERs, the study asks: (1) Do potential local co-benefits from CDM projects lead buyers to pay higher prices? (2) Do externally certified projects (Gold Standard) command a price premium reflecting higher likelihood of co-benefits? The authors propose an SDG-aligned co-benefit framework and econometric analyses to quantify how markets value co-benefits.

The literature identifies multiple challenges in integrating sustainability into climate finance: co-benefits are often intangible and hard to monetize; standards for measuring distributed, bottom-up co-benefits are inconsistent; and global reporting is incomplete. Prior methodologies range from simple checklists and qualitative profiles of project co-benefits to multi-attribute assessments combining qualitative and quantitative indicators. Quantitative evaluations exist but typically focus on specific, measurable environmental or socioeconomic indicators, limiting scope. Research on CDM’s sustainable development contributions includes case studies and qualitative analyses, but empirical evidence on market valuation of co-benefits is sparse. Work on sustainability labels (e.g., Gold Standard) suggests potential to signal higher co-benefits, yet rigorous causal estimates of associated price premiums are limited. The study builds on SDG interaction scoring approaches (e.g., McCollum 2018; IPCC SR1.5) and fills gaps by systematically mapping co-benefits to SDGs and testing how these relate to CER prices, including the impact of third-party certification.

- Framework development: The authors develop a two-layer SDG co-benefit framework focused on local co-benefits. Layer 1 defines five local co-benefit categories: enhanced local infrastructure; access to cleaner/affordable energy for heating/cooking; improved income and employment; improved access to electricity and/or energy-efficient lighting; and improved natural resource and environmental services. Layer 2 maps these categories to relevant SDG targets. Using structured literature review (84 studies) and guidance from McCollum (2018) and IPCC SR1.5, they assign SDG-interaction scores on a seven-point scale capturing positive (limited/medium/high impact) and negative (minor/medium/massive damage) interactions, with evidence confidence levels. Scores are aggregated to co-benefit criteria, assuming equal weights across SDGs. - Data: Primary data come from UNEP DTU CDM/JI Pipeline. Additional Emission Reduction Purchase Agreement (ERPA) dates were extracted from UNFCCC CDM PDFs via Python and validated (per Supplementary Note 2). The sample includes 2,259 CDM projects across 20 types and two sizes; for the main co-benefit analysis, 2,195 projects were grouped into eight co-benefit levels. Gold Standard (GS) analysis covers 64 GS CDM projects and 2,195 regular CDM projects (subsamples used per model). CDM afforestation/reforestation projects (66 total) were excluded due to distinct cost structures and small sample size. - Main econometric model: Regress CER price (or log price) on co-benefit level indicators controlling for project location fixed effects, credit buyer fixed effects, project type fixed effects, year fixed effects, and project size. Multiple specifications estimated: three linear models (levels) and one log-linear model. - Gold Standard causal analysis: Estimate treatment effect of GS certification on CER price using five models: (1) OLS with nine covariates; (2) propensity score matching (PSM) with nine covariates; (3) PSM with five continuous covariates; (4) exact matching on buyer country plus regression adjustment; (5) exact matching on buyer country and project location plus regression adjustment. Standard errors clustered at buyer company level. Balance diagnostics and common support checks conducted. Placebo tests performed by randomly assigning treatment within controls. - Heterogeneity and hedonic pricing: At the buyer company level (218 companies across 21 countries), regress average CER price on buyer characteristics (industry, profit status, number of projects), GS share, project portfolio by region, and buyer location fixed effects, to assess heterogeneous valuation patterns. - Robustness: Excluding 2008 ERPA-signed projects (financial crisis year) yields similar co-benefit price gradients. Alternative controls using macroeconomic indicators for buyer country produce consistent GS effects. Placebo tests show no spurious effects.

- Market valuation of co-benefits: Projects with higher likelihood of local co-benefits receive higher CER prices. Preferred model (linear with controls) shows a clear increasing trend across co-benefit levels. Example: co-benefit level 2 vs level 1 yields an average premium of $1.53/tCO2e (~11%). Overall, projects with the highest co-benefits received a 30.4% higher price than those with the lowest co-benefits. - Gold Standard (GS) premium: Across five models, GS certification commands statistically significant premiums: (1) $1.90/tCO2e (≈10.3%); (2) $4.21/tCO2e (≈29%); (3) $2.58/tCO2e (≈14%); (4) $2.33/tCO2e (≈11.2%); (5) $1.13/tCO2e (≈6.6%). Model 5 is most restrictive (exact match on buyer country and project location), reflecting minimal but still significant premium. - Buyer heterogeneity: Buyers pay more for CERs from Africa relative to other regions. A 10% increase in the share of projects located in Asia is associated with a $0.42/tCO2e (≈1.9%) lower price relative to Africa. Buyer industry-specific GS premiums: industrial and materials sector pays $6.50/tCO2e (~32%) more; carbon-related services $2.90/tCO2e (~14%) more; government and foundations $1.60/tCO2e (~15%) more for GS vs regular CDM. By profit status, not-for-profit buyers show significant GS premiums: government entities $2.30/tCO2e (~19%); MDBs $0.60/tCO2e (~7%); for-profit entities show no significant GS premium overall. Buyers in Oceania (e.g., Australia/New Zealand) paid higher prices than Europe and Asia; UK buyers paid on average $8.90 less (≈55%) than Australian buyers. - Investor preferences: Some small-scale technologies (e.g., small wind, solar, biomass) and African locations attracted higher willingness to pay, consistent with higher perceived local co-benefits. - Robustness: Results hold after excluding 2008 and under alternative matching and control strategies; placebo tests show no effect without true GS treatment.

The findings directly address the research questions: (1) Markets value local co-benefits—higher co-benefit levels are reflected in higher CER prices. (2) Third-party quality indicators (Gold Standard) that signal stronger sustainable development outcomes confer significant price premiums, evidencing investors’ willingness to pay for co-benefits. This suggests that aligning climate finance with SDGs can mobilize broader stakeholder support and potentially improve project quality and local impacts. Publicly supported entities (governments, MDBs, foundations) particularly value co-benefits, paying premiums for certified projects, while certain private sectors (industrial/materials and carbon services) also pay more, perhaps due to expertise and reputational considerations. Geographic heterogeneity indicates investor preference for projects in Africa and for certain small-scale technologies, aligning with narratives of stronger community impacts. Policy implications include the importance of integrating co-benefit communication and safeguards into climate finance mechanisms, enhancing transparency and reporting on SDG-aligned outcomes, and using public funding strategically to catalyze private investment toward high co-benefit projects.

The study introduces a comprehensive SDG-aligned framework to categorize and quantify local co-benefits of carbon projects and empirically demonstrates that carbon markets value these co-benefits through higher CER prices. It also provides causal evidence that Gold Standard certification commands meaningful price premiums, indicating market recognition of guaranteed co-benefits. Contributions include: (1) operationalizing co-benefit assessment aligned with SDGs; (2) revealing investor preferences and heterogeneity across buyer types and regions; (3) informing policy design to embed co-benefits and safeguards in climate finance. Future research directions include: refining co-benefit measurement at the individual project level; structured expert elicitation to complement literature-based scoring; extending analyses beyond CDM to voluntary markets and Article 6 sustainable development mechanisms; incorporating qualitative fieldwork to deepen understanding of local impacts and community perspectives; and exploring applications of the framework to broader sustainable infrastructure investments.

- SDG interaction scores rely on authors’ judgment, albeit supported by extensive literature and confidence grading; alternative expert elicitation could yield different weights or assessments. - Co-benefit valuation is inferred at the technology-type level rather than project-specific assessments, potentially masking within-type variation. - The empirical setting is the CDM (compliance market); generalizability to voluntary markets or other mechanisms requires further testing. - CDM afforestation/reforestation projects were excluded due to distinct characteristics, costs, and small sample size, limiting insights for land-use projects.