The Growing Risks of Climate Data Reliability in Central Bank Policy Models

Central banks are increasingly tasked with integrating climate-related financial risks into their policy frameworks. However, the credibility of the climate-economic models underpinning these efforts is coming under intense scrutiny. As physical and transition risks reshape global financial systems, the reliability of data and modeling assumptions has become a critical concern for investors, regulators, and policymakers alike.

The Limits of Traditional Climate-Economic Models

Conventional climate-economic models, such as integrated assessment models (IAMs), are widely used by central banks to project long-term financial risks. Yet, these models struggle to account for the non-linear, path-dependent, and highly uncertain nature of climate impacts. A 2025 study from Harvard Business School's Institute for Business in Global Society (BiGS) underscores this challenge, noting that traditional models systematically underestimate risks by failing to incorporate tipping points, feedback loops, and abrupt shifts in environmental dynamics. For instance, the Network for Greening the Financial System (NGFS) recently updated its climate damage function, projecting a 19% reduction in global real income by 2050 under high-emission scenarios. However, this model has been criticized for lacking a robust statistical basis, with researchers highlighting arbitrary assumptions and a lack of evidence linking temperature variables to material economic damage.

The limitations of these models are further amplified by the retraction of a widely cited climate study used by central banks. Bloomberg reported in December 2025 that a foundational paper underpinning several central bank models was retracted due to methodological errors, raising questions about the credibility of policy frameworks built on such data. This incident underscores a broader issue: the reliance on simplified, linear assumptions in models that fail to capture the complexity of real-world climate systems.

Central Banks' Response: Progress and Persistent Gaps

In response to these critiques, central banks are adopting more transparent and adaptive approaches. The European Central Bank (ECB) has emphasized the need for global disclosure standards to combat greenwashing and improve the accuracy of climate risk assessments. Similarly, institutions like the Bank for International Settlements (BIS) are advocating for modular financial systems, higher equity buffers, and clearer leverage ratios to enhance resilience according to research.

However, implementation remains uneven. A 2025 paper in Financial Stability Review notes that while non-financial corporations have made strides in climate disclosures, banks lag in aligning with supervisory expectations, particularly regarding emission-reduction targets. This gap highlights the risk of "amplification mechanisms," where concentrated exposures and overlapping portfolios among financial institutions could exacerbate systemic vulnerabilities according to ECB analysis.

Implications for Investors

For investors, the reliability of climate-economic models directly affects the accuracy of risk assessments and the valuation of assets. If models underestimate transition risks-such as stranded fossil fuel assets or regulatory shifts-investors may face unexpected losses. Conversely, overestimating risks could lead to misallocation of capital in green sectors.

A 2025 study in a scientific journal provides a nuanced perspective: Central Bank Green Policies (CBGP), including green finance initiatives, can mitigate climate-induced financial risks, but their effectiveness varies by a country's credit risk profile. This suggests that investors must adopt a granular, context-specific approach, rather than relying on broad, model-driven assumptions.

The Path Forward

To address these challenges, central banks and financial institutions must prioritize collaboration with climate scientists and adopt more dynamic modeling techniques. The ECB's push for standardized disclosures and the Harvard study's emphasis on dual strategies-"re-risking" and "de-risking"-offer a roadmap for balancing risk mitigation with sustainable growth. Investors, in turn, should advocate for transparency in model assumptions and diversify portfolios to account for the inherent uncertainties of climate projections.

Conclusion

The credibility of climate-economic models is not merely an academic debate-it is a cornerstone of financial stability in an era of climate uncertainty. As central banks refine their tools, investors must remain vigilant, recognizing that the reliability of these models will shape the future of global capital markets. The path forward demands innovation, collaboration, and a willingness to confront the limitations of current frameworks.