## Climate Transition Risk and Financial Stability in France

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---

### Introduction: scope, risks, and institutional context
- Climate change generates both physical and transition risks for the economy and financial system.
- Physical risk: direct exposure of financial institutions to corporates experiencing asset damage; insurers face asset-side and liability-side risks from higher frequency/severity of claims.
- Transition risk: arises from changes in climate policy, technology, and market sentiment; affects corporates with non-transitioning business models and can produce stranded assets (e.g., coal mines, oil reserves, power plants).
- Risk amplification factors:
  - Abrupt or poorly coordinated transition increases financial stability risks when asset prices adjust rapidly.
  - Climate risk endogeneity: financing of high-emitting industries creates negative externalities, capital misallocation, and amplifies climate risk accumulation.
- Institutional responses and exercises:
  - Network of Central Banks and Supervisors for Greening the Financial System (NGFS).
  - Banque de France (BdF) and ACPR bottom-up and top-down exercises: BdF found generally "moderate" exposure of French banks and insurers to climate transition risk by 2050, with concentrated losses in seven sensitive sectors and tripling of cost of risk over the analysis period.
  - BdF insurance-focused assessment (May 2024): Solvency Capital Requirement Coverage Ratios would decline by 60 percentage point between 2022 and 2027.
  - ECB (2023) adopted an eight-year granular approach with three transition risk scenarios and firm-level PD estimation mapped to financial exposures.

### Methodology and modeling framework
- Core model: ENVISAGE — a recursive-dynamic, multi-regional, multi-sectoral computable general equilibrium (CGE) model.
- Key model features:
  - Neo-classical optimization of consumption and production; factors mobile across sectors but not across countries.
  - Nested constant-elasticity-of-substitution (CES) production functions; non-homothetic demand; Armington specification with full bilateral flows.
  - Recursive dynamics: sequence of comparative static equilibria; agents not forward-looking; investment driven by savings, government budget balance, and current account balance.
  - Direct linkage between economic activities and emissions of different greenhouse gases (GHGs); detailed electricity generation by power source.
- ENVISAGE coverage and structure:
  - "12 European countries/regions and other major global economies as well as other regional aggregates, across 36 distinct sectors."
  - Annex lists 24 model countries and 36 CGE sectors aggregated to 8 sectors for the climate stress test.
- Caveats:
  - "ENVISAGE is a real economy model with almost perfect markets for commodities. Therefore, it does not account for adjustment costs when factors of production reallocate across economic activities."
  - Not well suited for short-term dynamics or analysis of monetary policy (model does not have money nor interest rates).

### Scenarios, policy calibrations, and assumptions
- Scenario set:
  - Business-as-usual (BAU): no changes in climate policy; does not account for temperature increases and physical risks.
  - Fit-for-55 (FF55) with two variant paths: Fit-for-55: late-push (1.5°C) and Fit-for-55: delayed (2.6°C). Delayed transition includes "Late start (3 years of lag)".
  - Analysis horizon: 2023-2030 (aligned with ENVISAGE recursive-dynamic calibration).
- FF55 policy instruments and calibrations:
  - FF55 target: EU-wide "55 reduction of the 1990 GHG emission levels by 2030."
  - Carbon pricing: implicit carbon price under the current EU-ETS and UK ETS increases "to US$185 per ton in 2030."
  - Carbon price is endogenously determined to achieve emission reductions in EU-ETS sectors that are "7 percent higher than baseline values."
  - Mitigation coverage assumption: "Only the EU, UK and EFTA are achieving their Nationally Determined Contributions (NDC) targets, while the rest of the world has no mitigation policies."
- Non-pricing policies calibrated in FF55:
  - Energy efficiency regulations: cost calibrated at "5.8 percent of gross annual fixed investment in each European country."
  - Heat pump uptake: reduces household energy demand by "11 percent"; cost "0.6 percent of gross annual fixed investment."
  - Renewable investment easing: yields "10 percent more renewable generation compared to baseline values in 2030."
- Electricity mix and abatement:
  - Electricity mix exogenously adjusted to follow European Commission PRIMES projections: by 2030 for France: "no energy powered by coal or oil, while it has lower gas and nuclear power and higher wind generation."
  - Abatement costs driven by sectoral energy-intensity and substitution possibilities; lower for energy sector, higher for agriculture, transport, and industrial processes.

### Macroeconomic impacts (France)
- GDP:
  - "The real GDP level in 2030 for the FF55 scenario is 1.3 percent below the baseline scenario."
- Sectoral impacts:
  - Most affected sectors: "energy-intensive sectors such as mining, oil & gas, manufacturing, chemicals, and utilities (coal, gas, and oil)."
- Cost channels:
  - Large share of GDP costs related to switching to heat pumps and investments associated with energy efficiency targets for transport and buildings.
  - Costs operate through relocation of productive investments, changes in energy demand (more electricity and less fossil fuels) and energy efficiency parameters.

### Micro-macro linkage: mapping sectoral output to firm defaults and bank exposures
- Integration approach:
  - Sectoral output paths from ENVISAGE are integrated into firm-level corporate balance sheets and risk metrics.
  - Five estimated equations map GVA → Sales → EBIT → Profit & Leverage → Probability of Default (PD).
  - Firm-level changes in profitability and leverage translated into PDs and mapped to granular data on corporate loan and bond instruments to calculate expected losses (aligned with ECB (2023) approach).
- Estimation results (preserve coefficients and statistics exactly):
  - Table 2.1 Linking Sectoral GVA to Sales:
    - Sales on Sector GVA: 1.101*** (0.0783)
    - Constant: 19.89 (14.11)
    - Observations: 64
    - R-squared: 0.761
    - Sectors: 8
  - Table 2.2 EBIT Evolution Estimation:
    - Lagged EBIT: 0.561*** (0.02)
    - Sales: 0.0459*** (0.002)
    - Observations: 2210
    - R-squared: 0.583
  - Table 2.3 Default Probability Estimation:
    - Profitability: -2.18*** (0.58)
    - Lagged LR: 0.192 (0.32)
    - Observations: 2244
- Firm-level data and coverage:
  - Corporate microdata sample: "667 large, medium-sized, and small firms" (2013–2022) from Datastream.
  - Energy-intensive companies: "about 27 percent of all companies in the sample."
  - Asset-size distribution: "75.9 percent" medium-sized (10 million to 1 billion euros), "19.2 percent" large (> 1 billion euros), "4.9 percent" small (< 10 million euros).
  - Forward-looking PD proxy: Moody's EDF in 2022 tailored to France, consolidated into sectoral levels using total assets as weighting factor.
  - Banking coverage: "coverage of the 9 largest French banks which represent 90 percent of total banking assets."

### Firm-level projection mechanics and accounting rules
- EBIT projection equation for t = 2023,...,2030:
  - EBIT(i,t)j = α̂i,0 + α̂1 EBIT(i,t−1)j + α̂2 Sales(i,t) − Carbon Tax Expenditure(i,t)j
- Carbon tax expenditure:
  - Computed as: Carbon Tax Expenditure(t) = Emission(t) * Carbon Price(t).
  - Firm-level emissions sourced from Urgentem.
- Selected balance sheet projection rules (preserved formulas):
  - Profit(t) = EBIT(t) / Total Assets(t)
  - Leverage(t) = Total Debts(t) / Total Assets(t)
  - Cash and Equivalents(t) = max(0, Cash and Equivalents(t−1) + EBIT(t) − Carbon Tax Expenditure(t) − Interest Expense(t))
  - Interest Expense(t) = R(t−1) * Total Debt(t−1)
  - Total Assets and Total Debt evolve via dynamic accounting identities as specified.

### Results: corporate PDs, NPLs, and banking implications
- Sectoral PD dynamics under FF55:
  - "PDs for the mining, chemicals, and manufacturing sectors more than double over the analysis horizon."
  - "PD increases remain contained for utilities (notably coal, gas, and oil-powered electricity) and transport sectors despite an upward path."
- Bank exposure asymmetry:
  - Average bank exposures to selected sectors: "1.7 percent for mining, and 0.8 percent for chemicals, on average."
- NPL projections:
  - "NPLs could increase by about 1.5 percentage points by 2030 under the Fit-for-55 transition central scenario which focuses on the impact on the energy-intensive sectors (ie, chemicals, metals, and other sensitive manufacturing)."
  - "NPLs could increase by about 3 percent in a more severe scenario with a broader impact to all sectors of interest rather than only the energy-intensive ones."
- Capital impairment:
  - "Estimates for capital impairment are not reported given high sensitivity to underlying assumptions, lacking more granular data on banks' exposures to energy-intensive sectors and bank-by-bank loss-given-default rates (LGDs)."
- Comparative exercise highlights:
  - BdF (2021) orderly scenario: "cost of risk is overall 1.2 times higher in 2050 compared to its 2025 level for all sectors. For the energy-intensive sectors, the cost of risk is 2.5 times as high."
  - BdF disorderly scenarios: "GDP loss could be between 2 and 5.5 percent."
  - ECB (2023) accelerated scenario: "average percentage point increase in corporate PDs for the Euro Area between 2022 and 2030 would be around 0.2 and 1.2 percentage points for the lower and upper risk quartiles."

### Policy considerations and recommendations
- Prudential and disclosure actions:
  - Increase banks' compliance with the Corporate Sustainability Reporting Directive (CSRD), EU taxonomy regulatory requirements and Pillar 3/ESG risks reporting and disclosures; integrate climate-related risks into governance, strategy, and risk management processes.
  - Banks should "publish information based on the CSRD, the EU Taxonomy regulation, and the EBA’s Pillar 3 rules."
- Supervisory actions:
  - ECB requires banks to reach full alignment with supervisory expectations on climate and environment-related risks "by end 2024."
  - ECB supervisors have included bank-specific climate and environmental findings in SREP and "have imposed binding qualitative requirements on more than 30 banks in their annual SREP."
  - SREP outcomes "will impact banks’ Pillar 2 capital requirements which will need to be boosted if banks’ exposures to energy-intensive corporates are high."
- Prudential planning and diversification:
  - The revised Capital Requirements Directive includes a new legal requirement for banks to prepare prudential plans to address climate-related and environmental risks arising from the process of adjustment towards climate neutrality by 2050.
  - Supervisors can "require banks to reduce their exposure to these risks and to reinforce targets, measures and actions included in their plans."
- Data and methodological improvements:
  - Need for sustained efforts to publish reliable and comparable data on exposures of banks to energy-intensive firms and on firms’ and banks’ transition plans.
  - Recommendation to continue updating and expanding climate risk analysis, including by combining top-down with more granular bottom-up approaches.

*IMF Working Paper — Climate Transition Risk and Financial Stability in France (wpiea2024144-print-pdf)*

### REFERENCES _______________________________________________________________________________________ 24

### Climate Transition Risk and Financial Stability in France

### Introduction: scope and risks
- Climate change generates both physical and transition risks for the economy and financial system.
- Physical risk: direct exposure of financial institutions to corporates experiencing asset damage; insurers face asset-side and liability-side risks from higher frequency/severity of claims.
- Transition risk: arises from changes in climate policy, technology, and market sentiment; affects corporates with non-transitioning business models and can produce stranded assets (e.g., coal mines, oil reserves, power plants).
- Regulatory frameworks mentioned: carbon pricing, emissions regulations, renewable energy mandates.
- Risk amplification factors:
  - Abrupt or poorly coordinated transition increases financial stability risks when asset prices adjust rapidly.
  - Climate risk endogeneity: financing of high-emitting industries creates negative externalities, capital misallocation, and amplifies climate risk accumulation.
- Institutional responses and initiatives:
  - Network of Central Banks and Supervisors for Greening the Financial System (NGFS) works to integrate climate-related risks into supervision and financial stability monitoring.
  - Banque de France (BdF) and ACPR have conducted both bottom-up and top-down exercises; BdF found generally "moderate" exposure of French banks and insurers to climate transition risk by 2050, with concentrated losses in seven sensitive sectors and tripling of cost of risk over the analysis period.
  - BdF insurance-focused assessment (May 2024) indicates in the short-term scenario Solvency Capital Requirement Coverage Ratios would decline by 60 percentage point between 2022 and 2027.
  - ECB (2023) adopted an eight-year granular approach with three transition risk scenarios and firm-level PD estimation mapped to financial exposures.

### Literature and comparative framing
- This paper situates itself among recent FSAPs (Japan (2024), Ireland (2022), Mexico (2022), Kazakhstan (2024)) and supplements existing scenario-based analyses by using a micro-macro approach and the Fit-for-55 scenario.
- Table comparison highlights:
  - ECB (2023): Top-down, Three scenarios, Transition risk, Horizon 2023-2030, No general equilibrium model, 11 sectors, Static balance sheet assumption, Coverage: Corporate + Households + Financial system.
  - BdF (2021): Bottom-up, Three scenarios (Orderly, Disorderly, Sudden transition), Physical & transition risk, Horizon 2020-2050, General equilibrium model used, 20 sectors, Dynamic balance sheet, Labor tax reductions fiscal policy choice, Focus: Financial sector.
  - This paper: Top-down, Two scenarios (Fit-for-55 with late-push (1.5°C) and delayed (2.6°C)), Transition risk, Horizon 2023-2030, General equilibrium model used, 8 sectors (Agriculture, mining, utility, construction, manufacturing, metals, chemicals, transportation), Static balance sheet assumption, Fiscal policy choice: Income tax reductions and reduction in government debt, Coverage: Corporate + Financial sector, Type of financial risk: Credit exposure, Country focus: France.

### Methodology overview
- Modeling framework: ENVISAGE model, a recursive-dynamic, multi-regional, multi-sectoral computable general equilibrium (CGE) model.
- Key model features:
  - Neo-classical optimization of consumption and production by households and firms.
  - Circular flow with firms, households, and markets; factors of production mobile across sectors but not across countries.
  - Nested constant-elasticity-of-substitution (CES) production functions to capture input substitution.
  - Non-homothetic demand; Armington specification for differentiated goods by origin with full bilateral flows, prices, and trade costs by commodity.
  - Recursive dynamic: solved as a sequence of comparative static equilibria; agents are not forward-looking; investment driven by savings determined by household savings, government budget balance, and current account balance.
  - Direct linkage between economic activities and emissions of different greenhouse gases (GHGs).
  - Detailed representation of electricity generation by power source.
- Integration with micro-level analysis:
  - Sectoral output paths from the ENVISAGE model are integrated into firm-level corporate balance sheets and risk metrics.
  - Firm-level changes in profitability and leverage are translated into firm-level probabilities of default (PDs) and mapped to granular data on corporate loan and bond instruments to calculate expected losses (methodology aligned with ECB (2023) approach).

### Scenarios and horizon
- Scenarios referenced:
  - Fit-for-55 scenario used in this analysis with two variant paths:
    - Fit-for-55: late-push (1.5°C)
    - Fit-for-55: delayed (2.6°C)
  - Comparators in literature include ECB’s three scenarios (including an Accelerated 1.5°C compatible) and BdF’s Orderly, Disorderly, and Sudden transition across 2020-2050.
- Analysis horizon: 2023-2030 (aligned with the ENVISAGE recursive-dynamic calibration and scenario focus).

### Key model and comparison facts (preserved numerics)
- Horizon comparisons and model coverage:
  - ECB (2023): Horizon 2023-2030.
  - BdF (2021): Horizon 2020-2050.
  - This paper: Horizon 2023-2030.
- Sectoral coverage in comparative table:
  - ECB (2023): 11 sectors listed.
  - BdF (2021): 20 sectors.
  - This paper: 8 sectors: Agriculture, mining, utility, construction, manufacturing, metals, chemicals, transportation.
- Notable result from BdF insurance assessment: Solvency Capital Requirement Coverage Ratios would decline by 60 percentage point between 2022 and 2027.
- Fit-for-55 scenario variants specified: late-push (1.5°C) and delayed (2.6°C).
- Fit-for-55 timing detail referenced in methodological choices: delayed transition includes "Late start (3 years of lag)".

### Paper scope and exclusions
- Focus: credit transition risks, firm vulnerability metrics (including carbon emissions), and mapping to bank exposures (credit exposure).
- Not a climate Value-at-Risk (VaR) assessment; it is an integrated micro-macro stress analysis mapping sectoral CGE outputs to firm and bank credit risk.
- Physical risks: not incorporated in this analysis because damages from chronic and acute physical risks are expected to be less significant by 2030 than over the long-term and are difficult to predict and calibrate into overall GDP and sector-specific losses.

*Source: wpiea2024144-print-pdf (IMF Working Paper — Climate Transition Risk and Financial Stability in France).*

### introduction of mitigation policies that can be GHG- and activity-specific. Hence, the model allows for

### wpiea2024144-print-pdf - introduction of mitigation policies that can be GHG- and activity-specific. Hence, the model allows for

### Modeling framework and scenarios
- ENVISAGE model coverage:
  - "12 European countries/regions and other major global economies as well as other regional aggregates, across 36 distinct sectors."
- Policy scenario constructed:
  - Stylized modeling of the Fit-for-55 policy package calibrated to reach the target of an EU-wide "55 reduction of the 1990 GHG emission levels by 2030."
  - Two scenarios: business-as-usual (BAU) and Fit-for-55 (FF55).
  - BAU assumes no changes in climate policy and does not account for the impact of temperature increases and physical risks.
- Carbon pricing:
  - Implicit carbon price under the current EU-ETS and UK ETS increases "to US$185 per ton in 2030."
  - "The value of the implicit carbon price is endogenously determined by the model to achieve emission reduction in the EU-ETS sectors that are 7 percent higher than baseline values."
- Assumptions on mitigation coverage:
  - "Only the EU, UK and EFTA are achieving their Nationally Determined Contributions (NDC) targets, while the rest of the world has no mitigation policies."

### Additional non-pricing policies calibrated in FF55
- Energy efficiency regulations:
  - Target: reduce related emissions in households, transportation services and other services (includes most non-residential buildings).
  - Cost calibration: "5.8 percent of gross annual fixed investment in each European country."
- Heat pump uptake:
  - Calibrated to "reduce household energy demand by 11 percent, by switching away from natural gas and coal energy demand to increased electricity demand."
  - Associated cost calibration: "0.6 percent of gross annual fixed investment."
- Renewable investment easing:
  - Assumed to increase total factor productivity of wind and solar power.
  - Leads to "10 percent more renewable generation compared to baseline values in 2030."

### Model mechanics and caveats
- Energy-capital interactions:
  - Short-run complementarity (elasticity < 1) and long-run substitutability (elasticity > 1).
  - New capital is modeled as more energy efficient than old capital.
- Electricity mix:
  - "The electricity mix is exogenously adjusted to follow closely the projections of the European Commission using the PRIMES energy model."
  - By 2030 for France: "no energy powered by coal or oil, while it has lower gas and nuclear power and higher wind generation."
- Abatement cost drivers:
  - Determined by sectoral energy-intensity and substitution possibilities between energy sources.
  - Lower abatement costs for the energy sector (given renewable electricity generation) and higher abatement costs for agriculture, transport, and industrial processes.
- Key caveats of ENVISAGE:
  - "ENVISAGE is a real economy model with almost perfect markets for commodities. Therefore, it does not account for adjustment costs when factors of production reallocate across economic activities."
  - "The model is not well suited to analyze short-term dynamics nor transition paths –as the model dynamics move from one general equilibrium to another."
  - "Nominal values are also not well represented since the model does not have money nor interest rates, and thus, monetary policy assessments are not possible."

### Macroeconomic and sectoral impacts (France)
- GDP and sectoral effects:
  - "The real GDP level in 2030 for the FF55 scenario is 1.3 percent below the baseline scenario."
  - Most affected sectors: "energy-intensive sectors such as mining, oil & gas, manufacturing, chemicals, and utilities (coal, gas, and oil)."
- Channeling of costs:
  - Large share of GDP costs related to "the costs of switching to heat pumps and the investments associated with the energy efficiency targets for transport and buildings."
  - These costs operate through "relocation of productive investments, changes in energy demand (more electricity and less fossil fuels) and energy efficiency parameters."

### Linking macro output to corporate defaults and banking exposures
- Mapping approach:
  - Five estimated equations connecting GVA → Sales → EBIT → Profit & Leverage → Probability of Default (PD) using historical data.
- Estimation highlights (preserve estimated coefficients and statistics):
  - Table 2.1 Linking Sectoral GVA to Sales:
    - Sales on Sector GVA: 1.101*** (0.0783)
    - Constant: 19.89 (14.11)
    - Observations: 64
    - R-squared: 0.761
    - Sectors: 8
  - Table 2.2 EBIT Evolution Estimation:
    - Lagged EBIT: 0.561*** (0.02)
    - Sales: 0.0459*** (0.002)
    - Observations: 2210
    - R-squared: 0.583
  - Table 2.3 Default Probability Estimation:
    - Profitability: -2.18*** (0.58)
    - Lagged LR: 0.192 (0.32)
    - Observations: 2244
- Firm-level data and weighting:
  - Corporate microdata sample: "667 large, medium-sized, and small firms" sourced from Datastream, covering 2013 to 2022.
  - Energy-intensive companies represent "about 27 percent of all companies in the sample."
  - Asset-size distribution: "75.9 percent" medium-sized (10 million to 1 billion euros), "19.2 percent" large (> 1 billion euros), "4.9 percent" small (< 10 million euros).
  - Forward-looking PD proxy: Moody's EDF in 2022 tailored to France, consolidated into sectoral levels using total assets as weighting factor.
  - Banking coverage: "coverage of the 9 largest French banks which represent 90 percent of total banking assets."

### Projecting firm-level financials and PDs
- EBIT projection equation for t = 2023,...,2030:
  - EBIT(i,t)j = α̂i,0 + α̂1 EBIT(i,t−1)j + α̂2 Sales(i,t) − Carbon Tax Expenditure(i,t)j
- Carbon tax expenditure:
  - Computed as: Carbon Tax Expenditure(t) = Emission(t) * Carbon Price(t).
  - Firm-level emissions sourced from Urgentem.
- Balance sheet projection rules (selected formulas from Table 3):
  - Profit(t) = EBIT(t) / Total Assets(t)
  - Leverage(t) = Total Debts(t) / Total Assets(t)
  - Cash and Equivalents(t) = max(0, Cash and Equivalents(t−1) + EBIT(t) − Carbon Tax Expenditure(t) − Interest Expense(t))
  - Interest Expense(t) = R(t−1) * Total Debt(t−1)
  - Total Assets and Total Debt evolve via dynamic accounting identities as specified.

### Results: corporate PDs, NPLs, and banking implications
- Sectoral PD dynamics under FF55:
  - "PDs for the mining, chemicals, and manufacturing sectors more than double over the analysis horizon."
  - "PD increases remain contained for utilities (notably coal, gas, and oil-powered electricity) and transport sectors despite an upward path."
- Bank exposure asymmetry:
  - Average bank exposures to selected sectors: "1.7 percent for mining, and 0.8 percent for chemicals, on average."
- NPL projections:
  - "NPLs could increase by about 1.5 percentage points by 2030 under the Fit-for-55 transition central scenario which focuses on the impact on the energy-intensive sectors (ie, chemicals, metals, and other sensitive manufacturing)."
  - "NPLs could increase by about 3 percent in a more severe scenario with a broader impact to all sectors of interest rather than only the energy-intensive ones."
- Capital impairment:
  - "Estimates for capital impairment are not reported given high sensitivity to underlying assumptions, lacking more granular data on banks' exposures to energy-intensive sectors and bank-by-bank loss-given-default rates (LGDs)."
- Comparison with other exercises:
  - BdF (2021) orderly scenario: "cost of risk is overall 1.2 times higher in 2050 compared to its 2025 level for all sectors. For the energy-intensive sectors, the cost of risk is 2.5 times as high."
  - BdF disorderly scenarios: "GDP loss could be between 2 and 5.5 percent."
  - ECB (2023) accelerated scenario: "average percentage point increase in corporate PDs for the Euro Area between 2022 and 2030 would be around 0.2 and 1.2 percentage points for the lower and upper risk quartiles."

### Policy considerations and recommendations
- Prudential and disclosure actions:
  - "Greater efforts will be needed to increase banks compliance with the Corporate Sustainability Reporting Directive (CSRD), EU taxonomy regulatory requirements and Pillar 3/ESG risks reporting and disclosures and integrate climate-related risks into their governance, strategy, and risk management processes."
  - Banks should "publish information based on the CSRD, the EU Taxonomy regulation, and the EBA’s Pillar 3 rules."
- Supervisory actions:
  - ECB requires banks to reach full alignment with supervisory expectations on climate and environment-related risks "by end 2024."
  - ECB supervisors are including bank-specific climate and environmental findings in SREP; "They have imposed binding qualitative requirements on more than 30 banks in their annual SREP."
  - SREP outcomes "will impact banks’ Pillar 2 capital requirements which will need to be boosted if banks’ exposures to energy-intensive corporates are high."
- Prudential planning and diversification:
  - "The revised Capital Requirements Directive includes a new legal requirement for banks to prepare prudential plans to address climate-related and environmental risks arising from the process of adjustment towards climate neutrality by 2050."
  - Supervisors can "require banks to reduce their exposure to these risks and to reinforce targets, measures and actions included in their plans."
- Data and methodological improvements:
  - Need for "sustained efforts ... to publish reliable and comparable data on exposures of banks to energy-intensive firms and on firms’ and banks’ transition plans."
  - Recommendation to "continue to update and expand climate risk analysis, including by combining top-down with more granular bottom-up approaches."

*IMF Working Paper — Climate Transition Risk and Financial Stability in France*

### References

### References and Annex (from wpiea2024144-print-pdf - References)

### References
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- Bank of Canada (BoC), & Office of the Superintendent of Financial Institutions (OSFI). (2022). Using scenario analysis to assess climate transition risk: Final report. Bank of Canada, January.
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- Caloia, F., Jansen, D.-J., Koo, H., van der Molen, R., & Zhang, L. (2022). Real estate and climate transition risk: A financial stability perspective. Occasional Studies, 19(4), Amsterdam: De Nederlandsche Bank.
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- Dolphin,  G.,  Duval,  R.,  Rojas-Romagosa,  H.,  Sher, G. (2024). Secure Energy in Europe’s Green  Transition. Departmental Paper DP/2024/005. European and Research Departments, International Monetary Fund. Forthcoming.
- Emambakhsh, T., Fuchs, M., Kördel, S., Kouratzoglou, C., Lelli, C., Pizzeghello, R., Salleo, C., & Spaggiari, M. (2023). The Road to Paris: Stress testing the transition towards a net-zero economy. Occasional Paper Series, (328), ECB, September.
- European  Central  Bank.  (2021). Climate-related  risks  and  financial  stability.  Financial Stability  Review, Frankfurt am Main, May.
- European Central Bank. (2022). Climate Risk Stress Test. July.
- European Central Bank (2023). The Road to Paris: stress testing the transition towards a net-zero economy. Occasional Paper Series: No. 328
- European Central Bank, & European Systemic Risk Board. (2021). Climate-related risk and financial stability. European  Central Bank  and European  Systemic Risk Board Project Team on Climate Risk Monitoring, July.
- European Central Bank, & European Systemic Risk Board. (2023). Towards macroprudential frameworks for managing climate risk, December.
- European Central Bank Banking Supervision. (2023). Banks must continue improving climate risk disclosures as new EU rules take effect, ECB report shows, April.
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### Annex — List of the countries in ENVISAGE Model (24)
1. Australia
2. China
3. Japan and Korea
4. India
5. Canada
6. United States of America
7. France
8. Germany
9. Italy
10. Bulgaria, Croatia and Romania
11. Belgium and The Netherlands
12. Czechia, Slovakia and Hungary
13. Poland
14. Rest of EU and EFTA
15. United Kingdom
16. Norway
17. Turkiye
18. Russian Federation
19. Saudi Arabia
20. Rest OPEC, other Middle East and North African countries
21. Other East Asia & Oceania countries
22. Other African countries
23. Other Eurasian countries
24. Other Latin American countries

### Annex — List of the sectors in ENVISAGE Model (36) and Climate Stress Test Aggregation (8)
- CGE Sector Codes — CGE Sector Names — Aggregated Sector Names
- cro-a — All Crops — Agriculture
- lvs-a — Livestock — Agriculture
- frs-a — Forestry — Agriculture
- fsh-a — Fisheries — Agriculture
- coa-a — Coal extraction — Mining
- oil-a — Crude Oil extraction — Mining
- p_c-a — Petroleum and coal products — Mining
- gas-a — Natural gas: extraction, manufacture & distribution — Mining
- clp-a — Coal powered electricity — Utilities
- olp-a — Oil powered electricity — Utilities
- gsp-a — Gas Powered electricity — Utilities
- nuc-a — Nuclear power — Utilities
- hyd-a — Hydro power — Utilities
- wnd-a — Wind power — Utilities
- sol-a — Solar power — Utilities
- xel-a — Other power — Utilities
- etd-a — Electricity transmission and distribution — Utilities
- wts-a — Water supply; sewerage; waste management and remediation activities — Utilities
- cns-a — Construction — Construction
- fdp-a — Food Products — Manufacturing
- mvh-a — Transport Equipment — Manufacturing
- oma-a — Fabricated metal products — Manufacturing
- OMN-a — Minerals n.e.s. — Manufacturing
- nmm-a — Non-metallic minerals — Manufacturing
- crp-a — Chemical products — Manufacturing
- i_s-a — Iron and Steel — Metals
- nfm-a — Non-ferrous metals — Metals
- wtp-a — Water Transport — Transportation
- atp-a — Air Transport — Transportation
- otp-a — Transport n.e.s.: Land transport and transport via pipelines — Transportation

*Climate Transition Risk and Financial Stability in France — Working Paper No. WP/2024/144, INTERNATIONAL MONETARY FUND*

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_Source: https://www.imf.org/-/media/files/publications/wp/2024/english/wpiea2024144-print-pdf.pdf_