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Climate Reputation and Bank Loan Contracting

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Abstract

We investigate how negative news coverage of borrower’s impacts on climate change affects bank loan contracting. Using a sample of publicly traded US firms for the period 2000–2016, we show that loans initiated following negative news coverage about firm’s adverse climate-related incidents have significantly higher spreads, shorter maturities, more covenant restrictions, and a higher likelihood of collateral security requirements. We find no changes in client firm’s credit fundamentals after such incidents, indicating that lender’s reputational concerns rather than the longer-term environmental impacts of their borrower’s actions are the primary drivers of these changes. This observation highlights the need for increased scrutiny of banks’ lending practices to ensure that they are genuinely committed to sustainability rather than merely engaging in symbolic actions.

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Data Availability

The data used in this study were sourced under license from Dealscan, KLD, RepRisk, and RavenPack, so are not publicly available.

Notes

  1. Andrade and de Oliveira (2015) also emphasize the role of the private sector in implementing mechanisms for mitigating climate change.

  2. Appendix 1 provides three examples of adverse climate reputation incidents categorized by RepRisk.

  3. For example, corporate assets can become stranded in an abrupt transition, while the implementation of a carbon tax could severely impact corporate profitability. Some of these transition risks are already manifesting, forcing some companies and their lenders to write off stranded assets. For instance, British Petroleum recently devalued its assets by $17.5 billion, partly in response to global efforts to tackle climate change (Bousso, 2020).

  4. Hong et al. (2019, p. 265) also note that “climate change risks need not be so narrowly confined to carbon exposures.”

  5. For instance, firms competing in the same industry may see their loan spreads decline if their peer competitor attributes an increase in loan spreads to an adverse climate-related incident.

  6. This model is aligned with the shareholder value model, advocated by Milton Friedman, which asserts that corporations have positive moral obligations and are governed for the exclusive benefit of shareholders.

  7. For example, Konar and Cohen (2001) report that the amount of a firm’s legally emitted toxic chemicals is negatively linked to the value of its intangible assets.

  8. One such initiative is the partnership for carbon accounting financials (PCAF). Banks will also collaborate to establish industrywide standards for measuring the climate reputation risk associated with lending activities. The PCAF, which has nearly 70 members holding more than US$9 trillion of assets worldwide, aims to push the financial industry to meet the goals of the Paris Agreement.

  9. We examine the question of whether the probability of obtaining a loan is reduced after an adverse climate event in “Effect of Climate Reputation Incidents on Other Loan Features” section.

  10. RepRisk uses the following five-step process to collect data: (1) screening, (2) identification and filtering, (3) analysis, (4) quality assurance and (5) quantification. The first step is conducted using a proprietary computer algorithm, and the remaining procedures are conducted by a team of analysts. One unique feature of RepRisk is that its database is updated daily, so incidents are screened, identified, analyzed, and updated whenever new risk information is published.

  11. RepRisk determines severity as a function of three dimensions: (1) the consequences of the incident (e.g., for health and safety incidents: no further consequences, injury, or death); (2) the extent of the impact (e.g., one person, a group of people, or a large number of people); and (3) the causes of the incident (e.g., negligence, intent, or systematic causes). These dimensions are each categorized into three levels of severity: low, medium, and high. Where more than one adverse climate-related incident occurs in the same month as the first incident, the classification of severity is based on the equally weighted severity of each incident.

  12. RepRisk determines its own rating of the influence (or reach) of each source according to the readership/circulation, which is also a proxy for credibility. Each source’s level of influence is pre-classified as low (e.g., local media, local governmental bodies, smaller NGOs and social media); medium (e.g., most regional and national media; international NGOs; and state, national and international governmental bodies); or high (e.g., a small number of truly global media such as the BBC, New York Times, and South China Morning Post).

  13. We apply this restriction because the study’s main purpose is to compare the costs of bank loans before and after a climate-related incident. If we were to consider a firm’s second incident, the pre-incident window of the second incident would overlap with the post-incident window of the first one. This procedure allows us to mitigate potential confounding issues. As a robustness check, we repeat our main test using only firms with just one incident. The results are similar to our main results (reported in column (2) in Panel B of Table 7).

  14. This sample is larger than the bank loan sample because we do not require bank loan originations.

  15. We estimate our regression models using an OLS specification because nonlinear models, such as logit and probit, tend to produce biased estimates in panel datasets with many fixed effects, leading to inconsistent estimates (e.g., Ai & Norton, 2003).

  16. Covenants in bank loan contracts assume various forms, the most common being general covenants, including limits on prepayments, dividends, voting rights and financial covenants, which place financial restrictions on accounting variables and other ratios, such as debt-servicing ratios. Covenants remain binding while the debt is outstanding.

  17. We do not control for the KLD CSR rating in our main model because doing so would have significantly reduced our sample size.

  18. See Greene (2008) for a review of Heckman’s (1979) methodology.

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Acknowledgements

We thank Peter Easton, Russell Lundholm, Rafael Rogo, Jeong-Bon Kim, David Ardia, Bank Research Conference, Hawaii Accounting Research Conference, Canadian Academic Accounting Association Conference, and International Conference of the French Finance Association participants for their helpful comments and suggestions. Hrazdil and Zhang acknowledge the financial support from the Social Sciences and Humanities Research Council of Canada (R832081).

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  1. Deniz Anginer, Karel Hrazdil, Jiyuan Li and Ray Zhang contributed equally to this work.

Authors and Affiliations

  1. Beedie School of Business, Simon Fraser University, Burnaby, Canada

    Karel Hrazdil, Deniz Anginer & Ray Zhang

  2. School of Accounting, Chongqing University of Technology, 69 Hongguang Street, Banan District, Chongqing, 400054, China

    Karel Hrazdil & Jiyuan Li

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Appendices

Appendix 1

Examples of climate reputation incidents provided by RepRisk.

Example 1

An ExxonMobil refinery in Louisiana. More than 40 environmental and other groups called for a federal investigation of the oil-and-gas company.

Source: Gillis, J., & Schwartz, J. Exxon Mobil accused of misleading public on climate change risks. The New York Times, October 30, 2015. https://www.nytimes.com/2015/10/31/science/exxon-mobil-accused-of-misleading-public-on-climate-change-risks.html

Example 2

A Greenpeace report was released, implicating Nestlé in rainforest destruction.

Source: Greenpeace New Zealand. Nestlé products play part in rainforest erosion. Scoop Independent News, March 18, 2010. https://www.scoop.co.nz/stories/PO1003/S00256/nestle-products-play-part-in-rainforest-erosion.htm.

Example 3

Walmart was accused of not reporting climate pollution with its shipping activities.

Source: Mitchell, S., & Wuthmann, W. Walmart spews a huge amount of climate pollution with its shipping, but doesn’t report any of it. Grist, June 2, 2015. https://grist.org/business-technology/walmart-spews-a-huge-amount-of-climate-pollution-with-its-shipping-but-doesnt-report-any-of-it/.

Appendix 2

See Table 9.

Table 9 Definitions of variables
Full size table

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Hrazdil, K., Anginer, D., Li, J. et al. Climate Reputation and Bank Loan Contracting. J Bus Ethics (2023). https://doi.org/10.1007/s10551-023-05517-7

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