Board of Governors of the Federal Reserve System

Figure 1. Climate risk drivers manifest as prudential risks

Figure uses a flowchart to describe climate risk drivers. The first column is climate risk drivers. The second column is transmission channels. The third column is microprudential risks. Under climate risk drivers are three classifications: physical risks, acute; physical risks, chronic; and transition risks. Examples of physical risks, acute are hurricanes, droughts, floods, wildfires. Examples of physical risks, chronic are higher temperature, sea level rise, environmental degradation. Examples of transition risks are climate policy, technology, regulation, market sentiment, consumer preferences. An arrow points right from the climate risk drivers column to transmission channels column. Under transmission channels are two classifications: micro channels and macro channels. Under micro channels are two list types: nonfinancial corporates and households. Examples under nonfinancial corporates are profitability; balance sheets, e.g., commercial property values, stranded assets. Examples under households are income and spending; balance sheets, e.g., residential property values. Under macro channels are two list types: economic and financial, and socioeconomic. Examples under economic and financial are government policy, capital investment and labor productivity, and sectoral reallocation of output. Examples under socioeconomic are population migration and changes in consumption patterns. An arrow points right from the transmission channels column to the microprudential risks column. Under microprudential risks are four classifications: credit risk, market risk, operational risk, and liquidity risk. Examples of credit risk are higher probability of default or loss given default, collateral values. Examples of market risk are repricing of financial instruments, fire sales. Examples of operational risk are business disruptions, legal and liability risk. Examples of liquidity risk are high-quality liquid asset demand, refinancing risk.

Figure 2. Stylized modeling approach for climate-related risks

Figure uses a flowchart to describe modeling approach for climate-related risks. The first box on the left is climate shocks (inputs). An arrow points right to two stacked boxes. The top box is macroeconomic variables (inputs); the bottom box is loan-level variables (inputs). From the two stacked box an arrow points right to a box labeled credit risk models. From the credit risk models box, an arrow points right to a box labeled climate-adjusted credit risk parameters (probability of default, loss given default, and risk rating grade) (outputs).

Figure 3. Stylized modeling approach for physical risk estimation

Figure uses a flowchart to describe modeling approach for physical risk estimation. The first box on the left is physical risk shock (hazard) (inputs). An arrow points right to a second box labeled property damage estimates (inputs). An arrow points right to a third box labeled credit risk models. From the credit risk models box, an arrow points right to a box labeled climate-adjusted credit risk parameters (probability of default, loss given default, and risk rating grade) (outputs).

Figure 4. Stylized inputs for RRE credit risk models in the physical risk module

On the far left is a box labeled RRE credit risk models. From RRE credit risk models are brackets pointing to two boxes. The top box is macroeconomic variables. The bottom box is loan-level inputs. Across from the macroeconomic variables is a list that reads: regional real income, regional gross domestic product, regional house price index, regional unemployment. Across from loan-level inputs is a list that reads: current loan-to-value. Under current loan-to-value is a two-item sub list: loan amount, property value. A second list reads: debt-to-income. Under debt-to-income is a two-item sub list: debt, income.

Figure 5. Stylized inputs for CRE credit risk models in the physical risk module

On the far left is a box labeled income-producing CRE credit risk models. From income-producing CRE credit risk models are brackets pointing to two boxes. The top box is macroeconomic variables. The bottom box is loan-level inputs. Across from the macroeconomic variables is a list that reads: regional commercial real estate price index, regional house price index, regional unemployment. Across from loan-level inputs is a list that reads: current loan-to-value. Under current loan-to-value is a two-item sub list: loan amount, property value. A second list reads: debt service coverage ratio. Under debt service coverage ratio is a two-item sub list: net operating income, total debt service.

Figure 6. Average of participant estimates of probability of default in the physical risk module, common shock

Figure 7. Average of participant estimates of probability of default in the physical risk module, idiosyncratic shock

Figure 8. Distribution of participant loan-level estimates of the change in probability of default in the physical risk module, 200-year, no insurance, common and idiosyncratic shocks, CRE

Figure 9. Stylized modeling approach for transition risk estimation

Figure uses a flowchart to describe modeling approach for transition risk estimation. The first box on the left is NGFS Scenario Variables: NiGEM and REMIND (inputs). An arrow points right to two stacked boxes. The top box is variable expansion to other macroeconomic variables (inputs); the bottom box is downscaling to sectoral and regional variables (inputs). From the two stacked box an arrow points right to a box labeled credit risk models. From the credit risk models box an arrow points right to a box labeled climate-adjusted credit risk parameters (probability of default, loss given default, and risk rating grade) (outputs).

Figure 10. Average of participant estimates of probability of default in the transition risk module

Figure A. Stylized representation of transition risk impact

Figure 11. Distribution of transition risk impact across corporate loans

Figure 12. Distribution of range in participant loan-level estimates of transition risk impact for common obligors