On 23rd January 2026, 35 experts from economics, ecology, finance, and policy convened to discuss the integration of nature into macroeconomic models. The workshop addressed the structural problem that current models assume nature is abundant and stable, often treating environmental issues as external to core decision-making. Participants agreed on five foundational points: nature is economically foundational, risks can be macro-critical, GDP is insufficient, no single model is universal, and the primary challenge is integration rather than measurement. Failing to account for nature risks overstating economic resilience and understating the value of preventive investment.

Introduction and framing of the workshop

Macroeconomic frameworks were largely built when natural capital seemed abundant. Consequently, nature is either excluded or siloed in parallel satellite accounts that rarely shape fiscal rules or growth projections. This architecture embeds systematic distortions, allowing the depletion of natural assets to be misinterpreted as growth and therefore mispricing both risks and opportunities. The workshop advocated for a hybrid approach: using parallel systems to make nature visible and legible, while selectively integrating it into macroeconomic models where it materially affects growth, risk, resilience, and investment decisions.

Why this is important

Macroeconomic models are not neutral analytical devices; they structure policy debates, define what is considered feasible, and influence the allocation of financial resources. They underpin medium-term fiscal frameworks, debt sustainability analyses (DSAs), and monetary policy. Omitting nature from these baselines implicitly assumes ecological stability, potentially embedding optimistic growth paths that ignore the degradation of productive ecosystems and the erosion of natural disaster buffers.

Macro-criticality of nature-related risks

Macro-criticality serves as an institutional filter for organisations like the IMF and World Bank. Nature-related risks meet these criteria through four dimensions: persistent growth and productivity effects, fiscal impacts (such as increased disaster response costs), volatility and tail risks, and financial sector transmission. Participants highlighted that these risks are context-specific, particularly affecting low-income ecosystem-dependent economies, small island states, and middle-income economies in transition.

Case studies and empirical applications

Empirical evidence demonstrates that nature-macro linkages are observable. In Belize, healthy mangroves and reefs reduce hurricane damages; excluding these services understates resilience to Category 4 storms. In Ghana, continued ecosystem degradation could materially lower medium-term growth trajectories. Uganda’s forest loss increases the frequency and severity of floods, raising public infrastructure repair costs and volatility in agricultural output. In advanced economies, the UK faces cumulative impacts on productivity and prices, while France has experienced water stress that constrained nuclear power cooling and hydroelectric production, impacting electricity prices. China’s work on Gross Ecosystem Product (GEP) and Ecuador’s 2024 debt-for-nature swap represent alternative integration pathways.

Transmission channels between nature and the macroeconomy

Transmission channels provide a pragmatic bridge between ecological processes and economic outcomes. Key channels include production and input dependency (e.g. agriculture’s reliance on soil quality and pollination), labour productivity and health, and fiscal channels. Risk buffering is also critical, as the loss of natural buffers functions as a form of endogenous risk amplification, increasing the likelihood of extreme GDP contractions and fiscal stress events following shocks.

Differentiating macroeconomic models and their purposes

The workshop emphasised a pluralistic modelling ecosystem. Stylised models clarify core mechanisms and thresholds. Exploratory research models, such as integrated assessment models (IAMs), represent biodiversity loss and ecosystem services. Applied policy models, including Dynamic Stochastic General Equilibrium (DSGE) and Computable General Equilibrium (CGE) models, are constrained by transparency requirements but can incorporate nature-related shocks through productivity and supply constraints. Models such as GTAP-InVEST illustrate pathways for incremental integration within existing frameworks.

Provocations, unresolved debates, and points of tension

Significant debate centred on the “equilibrium bias” of standard models, which often assume mean reversion rather than permanent regime changes. The “satellite account problem” remains a hurdle, where natural capital accounts (NCA) sit alongside rather than inside decision frameworks. Participants argued that the challenge is no longer measurement, but translating these figures into growth projections and debt dynamics to ensure they are perceived as decision-relevant rather than merely descriptive.

Use cases for macroeconomic modelling of nature and implications for model design

Model requirements depend on the specific use case. Financial stability assessments must prioritise tail risks and non-linear responses. Macroeconomic surveillance requires integrating nature into baselines to identify effects on debt dynamics. Development planning demands an emphasis on opportunity and long-term growth paths. No single model can meet all these needs; therefore, integration must be purpose-driven and dictated by the decision context, ensuring transparency about what is included or omitted.

Synthesis, implications, and agreed next steps

The meeting established that nature is foundational to production and welfare. Future priorities include clarifying macro-criticality criteria to include tail risks and long-term growth effects, advancing transmission-channel mapping, and prioritising integration into debt sustainability analyses and macro-fiscal frameworks. Participants agreed on developing modular modelling approaches and strengthening empirical data linking ecosystem conditions to economic outcomes, including through geospatial analysis and case-study validation, to support robust, forward-looking economic strategies.