Business on the Edge 2024

–Low Climate-Change Scenario (SSP1-2.6): Aggressive mitigation scenario in which total greenhouse gas emissions reduce to net zero by 2050, resulting in global average temperatures rising by 1.3-2.4°C by 2100, consistent with the goals of the Paris Agreement. Data is available by decade, from the 2020s to the 2090s. For simplicity, this analysis refers to the decade midpoint for each datapoint (for example, 2035 for the 2030s). Metrics are not intended to represent the percentage of a company’s fixed asset value that will be lost but rather reflect the magnitude of those costs relative to the value of the company’s total fixed assets. Losses include: increased operational expenses, lost revenues due to business interruption, physical damage and costs incurred to repair assets. They exclude other costs, such as value chain disruptions, insurance premium rises or lower consumer spending power. As such, the total climate hazard losses facing companies are likely to be much higher than those presented in the analysis. Note: Climate risk modelling is a rapidly evolving field. The parameters and assumptions used influence both the direction and magnitude of change and can therefore be contested. S&P Global, which is ranked as industry-leading for physical climate data capabilities and a category leader overall for physical risk modelling solutions,151 uses multiple sources to estimate the impact of physical climate hazards on fixed assets. For example, extreme heat is modelled using metrics including annual occurrences of warm days (TX95p), NOAA’s Heat Stress Index, duration- and-intensity heatwave metrics, and extreme values generalized extreme value (GEV) analysis. The data is downscaled using techniques embedded in the NASA NEX-GDDP downscaled data set, augmented with corrections and adjustments. A different downscaling approach could produce different results. In the early forecast period (2025), risk in the high emissions scenario is below that in the low emissions scenario because of the time taken for net increases in longwave radiation caused by higher emissions to manifest as signal above a background natural climate variability when looking at aggregate weather patterns at a local level (see Figure 6). More detail on the methodology behind this dataset – including how the physical climate hazards are defined – is available on the S&P Global website.152 2 Extrapolate analysis to all listed companies To provide a more comprehensive estimate of fixed asset losses, the results were extrapolated to all listed companies. Data on 2023 (or latest available year) business revenues for 55,515 listed companies was sourced from S&P Capital IQ in May 2024, of which the revenues held by the 5,736 large, listed companies analysed in Step 1 already account for a large majority (78.7%). To estimate the financial losses for all listed companies, the extrapolation coefficient is calculated using the formula below: Total 2023 revenues for all listed companies (n=55,155) / Total 2023 revenues for all large, listed companies (n=5,736) The calculation assumes the fixed asset to revenue ratio of all listed companies (n=55,155) is the same as that of the subset (n=5,736). The extrapolation coefficient is assumed to be constant across industries to smooth out the dominance of large companies in specific industries that could skew the results. The results are shown in Figure 3 and Figure 4. Note: Unlisted companies – including small and medium-sized enterprises, start-ups, scale-ups and unicorns – account for a significant proportion of business output across the world and will face climate-related losses, depending on their fixed asset needs and exposure. However, these companies were excluded from the analysis for data availability reasons (see Annex 2: Limitations to the approach). 3 Explore geographic implications Geolocation was used to identify where specific fixed assets held by the 5,736 large businesses are located. The six regions into which fixed assets were geolocated are: United States and Canada, Latin America and the Caribbean, Europe, Middle East, Africa and Asia-Pacific. The analysis calculates the average expected risk to fixed assets in each region from each hazard. The top five are presented in Table 2. Note: Calculating fixed asset losses in US dollars is not possible because companies often hold fixed assets in regions beyond where they are headquartered. Overall fixed asset value data is currently only available at the broader company level. Calculations that assumed all company fixed assets were situated in the same country as their headquarters would have been misleading and were therefore not calculated. 4 Compare fixed asset losses with earnings To contextualize the magnitude of the costs relating to physical climate hazards, fixed asset losses (under different emissions scenarios, across different decades) are compared with earnings (average EBITA 2021-23) across 5,043 companies using the formula below. These companies are a subset of the 5,736 from Step 1 for which sufficient EBITA data is available. The results of this analysis are shown in Figure 6 and Figure 7. ∑ Fixed asset losses for all companies / ∑ EBITA for all companies Business on the Edge: Building Industry Resilience to Climate Hazards 64