Category: 3. Business

The year 2024 was confirmed by the Copernicus Climate Change Service to be the warmest year on record globally, and the first calendar year that the average global temperature exceeded 1.5°C above its pre-industrial level. As climate change intensifies, the financial and regulatory risks facing businesses are under increasing scrutiny. Governments and financial institutions worldwide are aligning corporate reporting requirements with the recommendations of the Task Force on Climate-related Financial Disclosures.

The EU has taken a decisive step by implementing the Corporate Sustainability Reporting Directive (European Commission 2023), mandating around 50,000 companies, including 10,000 foreign companies, to report on climate-related risks from 2025. While disclosure requirements are becoming more stringent, recent studies suggest that corporate climate disclosure is becoming too costly and often a mere box-ticking exercise, with firms engaging in ‘greenwashing’ or selective reporting of non-material risks (Bingler et al. 2022). This raises a crucial question: how can investors, regulators, and consumers ensure they have a clear, standardised, and comparable understanding of climate risks across industries and geographies at a reasonable cost?

In November 2024, European Commission President Ursula von der Leyen announced the Omnibus Environmental, Social, and Governance (ESG) Regulation to consolidate and simplify corporate sustainability reporting obligations. Our background research and this column recommend a methodology that can support the simplification of reporting, while providing comparable and standardised data and maintaining reporting requirements for a large number of companies without extra burden.

A novel and cost-effective approach to measuring climate risk

In our recent research (Erhart et al. 2025), we propose a comprehensive method for assessing corporate climate risks by integrating data from major pollutant release and transfer registers and greenhouse-gas reporting programmes with satellite observations across 30 countries, including Australia, Canada, the EU, and the US. Our study analyses data from 70,000 industrial firms and their 170,000 facilities, offering an unprecedented large-scale approach to evaluating both transition and physical climate risks required by the Corporate Sustainability Reporting Directive and the related European Sustainability Reporting Standard (Figure 1).

Figure 1 Climate change transition and physical risks covered in our study

Notes: ESRS: European Sustainability Reporting Standard. GHG: greenhouse gas.
Data sources: European Environment Agency, EU Pollutant Release and Transfer Register, US Environmental Protection Agency (EPA), EPA Toxic Release Inventory, Facility Level Information from the EPA Greenhouse Gases Tool (FLIGHT), Canadian National Pollutant Inventory, Australian Clean Energy Regulator, National Greenhouse and Energy Reporting, Canadian Greenhouse Gas Reporting Programme, Australian National Pollutant Release Inventory.

Key findings: Climate risks are not uniform

Our research highlights that climate risks manifest differently across industries and locations.

1. Transition risk. Measured through reported greenhouse gas emissions, transition risk is highest for industrial plants in the US. Companies with high emissions may continue to face regulatory and market pressures to decarbonise or risk losing investor confidence in the long run.

2. Physical risk. Assessed via historical data on cooling energy needs (heat risk), flood exposure, and photovoltaic power potential, physical risks are highly location-dependent. For instance, heat risk is more severe for firms in Australia, Southern Europe, and the southern US, while flood exposure is more pronounced in Central Europe and the eastern US (Figures 2 and 3).

Figure 2 Flood exposure (maximum historical water discharge at industrial company sites)

Notes: White bubbles on the map indicate company facilities without historical flood risk, while blue bubbles indicate company facility locations with historical flood risk.
Source: Erhart et al. (2025).

Figure 3 Heat risk of industrial company sites in the sample in cooling degree days

Note: Map colour scale: green is the lowest heat risk (in terms of cooling degree days) and red is the highest. 2019 observations were used.
Source: Erhart et al. (2025).

3. No strong correlation between transition and physical risks. Unlike common assumptions, our findings indicate that transition and physical risks are not necessarily correlated at the company level. Some firms may have low emissions but face high physical risks due to extreme weather exposure, while others with high emissions may operate in less climate-vulnerable locations.

Figure 4 No strong correlation between transition and physical risks

Notes: Combined figure of Pearson correlation ratios and significance levels (upper right cells), indicator histograms (diagonal cells), pairwise scatter plots of indicators (lower left cells). (a) Heat risk (cooling degree days, cdd). (b) Flood risk, maximum historical water discharge (metres). (c) Photovoltaic potential, long-term average daily total of kilowatt-hour (kWh) from optimally tilted 1kWp panel. (d) greenhouse gas (equivalent in kilogrammes, Co2eqKg). 2019 observations were used for the greenhouse gas emissions.
Source: Erhart et al. (2025).

Policy and investment implications

These findings have critical implications for policymakers, investors, and corporate managers.

• Standardising risk disclosure. The lack of correlation between transition and physical risks underscores the need for a more comprehensive risk-assessment framework that captures both dimensions. Current reporting standards should evolve to reflect this complexity.
• Investor strategy and portfolio diversification. Investors need to look beyond headline emissions figures and assess the physical climate risks embedded in their portfolios. Firms with high flood or heat exposure may require additional adaptation investments.
• Corporate risk management. Businesses must develop holistic climate-risk strategies that integrate both mitigation (reducing emissions) and adaptation (enhancing resilience to climate impacts).

A call for better data integration

Our study demonstrates that publicly available pollution registers and satellite observations of physical climate risks offer a valuable, yet underutilised, resource for regular climate-risk assessments. However, these datasets remain fragmented across jurisdictions, limiting their effectiveness for global risk evaluation. We recommend greater international coordination in environmental reporting and data integration to enhance transparency and comparability.

With upcoming regulatory changes, companies, investors, and regulators must adopt more rigorous and data-driven approaches to climate-risk assessment. By leveraging pollution registers and satellite imaging and radar observations, we can gain a clearer and more actionable picture of industrial climate risks, ultimately fostering a more resilient and sustainable global economy.

References

Bingler, J A, M Kraus, M Leippold and N Webersinke (2022), “Cheap talk and cherry-picking: What ClimateBert has to say on corporate climate risk disclosures”, Finance Research Letters 47(Part B).

Copernicus Climate Change Service (2025), Copernicus: 2024 is the first year to exceed 1.5°C above pre-industrial level, Global Climate Highlights 2024.

Erhart, S, S Szabó, and K Erhart (2025), “Integrating pollutant registers for the climate change risk evaluation of industrial companies in Australia, Europe and North America”, Nature Scientific Reports 15(1207).

European Commission (2023), “New rules on corporate sustainability reporting: The Corporate Sustainability Reporting Directive”.

EU (2023), “Regulation of the European Parliament and of the Council of 27 November 2019 on sustainability-related disclosures in the financial services sector”, PE/87/2019/REV/1.

As global trade has expanded – especially with the ascent of China – concerns about job losses and deindustrialisation in high-income countries have grown. While many studies document the level of impact of import competition on employment, we know less about how firms adapt. Do they downsize, switch product lines/industries, or reorganise production through offshoring to cushion the blow? In a recet paper (Ito and Matsuura 2025), we address these questions using a uniquely rich panel of Japanese firms spanning 1997–2014, focusing on three margins of adjustment: employment (especially production workers), industry switching, and offshoring (imports of intermediates from Asia). We also ask when these adjustments occur – either immediately or with a lag.

Figure 1 documents a clear rise in Chinese import penetration into Japan from the late 1990s onward, with only a crisis-era pause. Over the same period, Japan’s manufacturing share of employment fell from 20.8% in 1995 to 15.3% in 2015) (Figure 2), providing prima facie evidence of structural pressure.

Figure 1 Import penetration ratio from China

Note: Chinese import penetration is computed as Import from China/Domestic demand, where Domestic demand = Domestic production + Imports from the world – Exports to the word.
Source: Authors’ calculations based on System of National Accounts (Cabinet Office) and JIP database (RIETI).

Figure 2 Share of manufacturing employment in Japan

Source: Authors’ computation from the System of National Accounts (Cabinet Office of Japan).

How do firms respond to intensifying import competition from China? Table 1 presents the distribution of firms according to their response patterns. Firms are categorised into four groups based on their reactions. The first group consists of firms that neither reduce employment nor switch industries, labeled “NoAdjust”. The second group includes firms that adjust employment only (“EmplAdjustOnly”), while the third group comprises firms that switch industries only (“IndSwitchOnly”). The fourth group consists of firms that adopt both strategies – employment adjustment and industry switching – labeled “BothEmplSwitch”. Employment adjustment is defined as a reduction of 10% or more in the number of production workers over the previous five years. Industry switching refers to a change in a firm’s primary four-digit industry classification.

To assess the impact of Chinese import competition, we compare firms operating in the top and bottom five industries based on the extent of change in Chinese import penetration. Among all firms shown in column (1), 54% made no adjustments (NoAdjust), 30.5% implemented only employment reductions (EmplAdjustOnly), 9.2% switched industries without adjusting employment (IndSwitchOnly), and 6.3% pursued both strategies (BothEmplSwitch). Columns (2) and (3) present firms in the bottom five and top five industries, respectively, based on the degree of change in Chinese import penetration. In the bottom five industries, shown in column (2), 58% of firms did not implement any adjustments (NoAdjust). While the share of firms engaging in industry switching – either alone or in combination with employment reductions – was low, the proportion of firms implementing only employment adjustments was similar to that observed for all firms. By contrast, in the top five industries, presented in column (3), the share of firms that made no adjustments was lower, at 48%. The proportion of firms that engaged only in industry switching or that strategy in combination with employment reduction was notably higher at 11% and 9.7%, respectively. These patterns suggest that firms exposed to greater import competition from China are more likely to respond with a combination of employment adjustment and industry switching.

Table 1 Firm’s reaction patterns

Source: Authors’ computation from the Basic Survey of Japanese Business Structure and Activities　（BSJBSA）and the Census of Manufacture (COM) data of the Ministry of Economy, Trade and Industry (METI).

 Econometric analyses using the multinomial logit model demonstrated the following:

• Rising imports have led many firms to reduce their workforce, with production workers experiencing significant losses, in line with the cases shown for the US in Autor et al. (2013) and Acemoglu et al. (2016).
• Firms that engaged in product switching experienced less severe employment losses than those that did not, suggesting that product switching could be an effective coping strategy. This finding resonates with those found in Iacovone et al. (2013) and Miranda et al. (2011), among others.
• Import competition has an immediate effect on the employment of production workers, whereas overall firm-level employment adjustment and product switching tend to occur with a delay of two to three years.
• Offshoring also plays a crucial role in mitigating the adverse effects of import competition. This finding, which complements that in Hayakawa et al. (2021), highlights the importance of offshoring in sustaining employment and suggests that globalisation should not simply be regarded as a factor that reduces job opportunities.

Author’s note: The main research on which this column is based (Ito and Matsuura 2025) first appeared as a Discussion Paper of the Research Institute of Economy, Trade and Industry (RIETI) of Japan.

References

Acemoglu, D, D Autor, D Dorn, G Hanson and B Price (2016), “Import Competition and the Great US Employment Sag of the 2000s”, Journal of Labor Economics 34(1): S142-S198.

Autor, D, D Dorn and G Hanson (2013), “The China Syndrome: Local Labor Market Effect of Import Competition in the United States”, American Economic Review 103(6): 2121-2168.

Hayakawa, K, T Ito and S Urata (2021), “Impacts of Increased Chinese Imports on Japan’s Labor Market”, Japan and the World Economy 59, 101087.

Ito, T and T Matsuura (2025), “Import Competition and Restructuring Strategies: Evidence from Japanese firm-level data”, RIETI Discussion Paper Series 25-E-059

Iacovone, L, F Rauch and L A Winters (2013), “Trade as an engine of creative destruction: Mexican experience with Chinese competition”, Journal of International Economics 89(2): 379–392.

Miranda, V, M-M Badia and I Van Beveren (2012), “Globalization drives strategic product switching,” Review of World Economics 148: 45-72.