Abstract
We seek insights into potential benefits for firms adopting strategies to improve business sustainability in a carbon-constrained future. We investigate whether lenders incorporate a firm’s exposure to carbon-related risk into lending decisions through the cost of financing, and if so, importantly whether firms can mitigate the penalty by demonstrating an awareness of their carbon risks. We use a sample of 255 firm-year observations from eight industries over the period 2009–2013. We measure carbon-related risk exposure as the firm’s historical carbon emissions and our primary measure of carbon risk awareness is based on the firm’s willingness to respond to the Carbon Disclosure Project (CDP) survey. We document a positive association between cost of debt and carbon risk for firms failing to respond to the CDP. Further, this association is economically meaningful, with a one standard deviation increase in carbon risk mapping into between a 38 and 62 basis point increase in the cost of debt. Equally, we find that this penalty is effectively negated for firms exhibiting carbon risk awareness. Our results are robust when we consider alternate measures of carbon awareness—disclosure through alternative medium to the CDP and firms’ annual cash investment in new capital assets using “cleaner” technology. Our results highlight not only the importance of carbon awareness as a business strategy for polluting firms, but also its importance to lenders exposed to their clients’ default and reputational risk. The debt market appears to incorporate historical carbon emissions and forward-looking indicators of carbon performance.
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Notes
For example, Hurricane Katrina hit the U.S. in 2005 causing an estimated insured loss of $45 billion, while severe flooding affected Europe in 2002 with an estimated $16 billion of direct losses (Labatt and White 2007). Stern (2007) estimated that a failure to act on climate change could cost the world economy between five and 20 percent of global gross domestic product (GDP) each year, with the potential to limit this cost to around 1 % by acting promptly to avoid the worst impacts of climate change.
MacKenzie (2009) provides an overview of the development of this perspective.
One study that directly examines the association between carbon emission and the cost of debt is Chen and Gao (2012). However, their study relies on emissions data from the Emissions and Generation Resource Integrated Database (EGRID) and hence is restricted in scope to the U.S. electrical utility industry.
The Kyoto Protocol was adopted by the member countries under the United Nations Framework Convention on Climate Change (UNFCCC) in 1997 and came into force in 2005 (UNEP 2006). It is an internationally binding agreement whereby participating countries pledge to reduce GHG emissions to meet national reduction targets (UNEP 2006; Talberg and Swoboda 2013).
Details are available from the Clean Energy Regulator web site (www.cleanenergyregulator.gov.au).
Of direct relevance here, the carbon emissions publishing thresholds are corporate groups with Scope 1 and Scope 2 GHG emissions combined that are equal to or greater than 125 kilotonnes for reporting year 2008–2009, 87.5 kilotonnes for reporting year 2009–2010, and 50 kilotonnes for reporting year 2010–2011 and beyond.
This information is sourced from the UNEP FI web site (http://www.unepfi.org/about/statements/history/index.html).
The Climate Change Governance Checklist was developed by the RiskMetrics Group to analyse corporate responses to climate change. This checklist consists of fourteen indicators to evaluate corporate climate change activities in five main governance areas of board oversight, management execution, public disclosure, emissions accounting, and strategic planning.
Several studies document the negative impact of carbon liabilities on firms. For example, the European-based study by Clarkson et al. (2015) finds that carbon emissions that exceed carbon allowances under the EU ETS negatively affect firm valuation. Similarly, the Australian-based study from Deutsche Bank (2009) estimated that the carbon liability arising from the proposed emissions trading scheme has a potential negative valuation impact on the top 25 emitters in Australia. In a similar vein, a U.S.-based study by Schneider (2011) suggests that for firms in polluting industries, environmental risk is one of the major idiosyncratic risks.
The Australian accounting standard AASB 123 stipulated that a firm is allowed to capitalise borrowing costs (e.g. interest on bank overdrafts and borrowings) that are directly attributable to the acquisition, construction or production of a qualifying asset into the cost of that asset.
The required details are obtained from the notes to the financial statements accessed from the Connect4 database.
The Greenhouse Gas Protocol is the most widely used international accounting tool by government and business leaders to assess GHG emissions. It classifies GHG emissions at three levels: (1) Scope 1: ‘direct GHG emissions caused by a company’s fuel combustion or emitted through industrial processes owned or controlled by a company’; (2) Scope 2: ‘indirect GHG emissions from purchased electricity’; and (3) Scope 3: ‘indirect emissions from other sources not owned or controlled by the company, such as suppliers and products in use’ (Salo and van Ast 2009, p. 6).
Although the CPM was subsequently repealed in 2014, it was operational from July 2012 and anticipated from 2007 onward by business as a succession of Labor governments signalled an intention to introduce some form of carbon tax.
Sourced from the CDP website (https://www.cdp.net/en-US/Respond/Pages/companies.aspx).
The CDP divides a firm’s response status into ‘Answered Questionnaire’, ‘Declined to Participate’, ‘Information Provided’ and ‘No Response’. ‘Answered Questionnaire’ indicates that a firm answered some or all of the questions in the questionnaire; ‘Declined to Participate’ indicates that a firm declined to participate in the project: ‘Information Provided’ indicates that a firm provided information relevant to the questionnaire in another form of report (e.g. CSR report) but did not answer the questionnaire; and ‘No Response’ indicates that a firm did not reply to the CDP regarding their request.
We also more narrowly identified non-responding firms that provided the information requested by the CDP in their CSR or annual reports, or on their corporate website, and reran the analyses after reclassifying these 2 firm-year observations as ‘carbon aware’, finding results to be qualitatively identical.
Given our Australian setting, we use an Australian Z-score model from Aldamen and Duncan (2012) to estimate a firm’s default risk, with the calculated Z-score then multiplied by −1 so that higher values represent a higher default risk. Aldamen and Duncan’s (2012) Z-score is computed as: Z-score = −0.38 + 2.05 (Retained Earnings/Total Assets) + 3.06 (EBIT/Total Assets) + 1.09 (Sales/Total Assets) − 2.91 (Book Value of Total debt/Total Assets) + 0.16 (Working Capital/Total Assets).
Chen and Gao (2012) interpret their finding as implying that if firms with newer equipment have relatively high carbon emission rates, required additional future capital expenditures on equipment with improved carbon emission rates will reduce cash flows available for debt payments and increase default risk. In contrast, Schneider (2011) attributes his finding to the fact that firms with new equipment may exhibit superior environmental performance thereby lowering the cost of debt.
While Goss and Roberts (2011) use the 3-month U.S. dollar LIBOR rate, given our Australian setting, we use the official Reserve Bank of Australia (RBA) cash rate. While the 90-day bank bill swap rate (BBSW) is widely used as a benchmark interest rate for floating rate financial instruments, due to the inaccessibility of the historical BBSW data, we revert to official RBA cash rate which has been shown to be highly correlated with the BBSW (Morningstar 2013).
The following sources were used: Google Search (http://www.google.com.au); ABN Lookup (http://www.abr.business.gov.au); and ASIC Company Search (https://creditorwatch.com.au/express/asic/search/false/company).
Firms in the Financial sector were excluded because they are subject to industry-specific regulations, which may result in their capital market decisions being fundamentally different from those of non-financial firms (Pittman and Fortin 2004).
The mean values of CARBON are 0.0031, 0.0189, 0.0034 and 0.0013 tonnes of Scope 1 GHG emissions per $1000 of sales for Consumer Discretionary, Consumer Staples, Health Care and Telecommunication Services, respectively, and 1.0314, 0.1869, 0.4080 and 2.2885 tonnes of Scope 1 GHG emissions per $1000 of sales for Energy, Industrials, Materials and Utilities, respectively.
Gray et al. (2009) reported mean and median values of 8.7 and 7.1 %. Here, differences are likely attributable to the relatively low interest rate environment during our study period compared with theirs.
Arguably, in addition to providing assurance that our results and conclusions are not sensitive to our choice of proxy for carbon risk awareness, the use of these alternative proxies also addresses the potential concern that our CDP measure may be capturing the effect of an omitted, correlated variable associated with the firm’s decision to respond to the CDP survey rather than the firm’s carbon awareness.
These results are based on the 252 firm-year observations with the required data on investments in property, plant and equipment. The variables SIZE, TANG and NEW were removed from the model because of their high correlations with PPE.
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Acknowledgments
This study is based on Juhyun Jung’s ‘Graduate Diploma in Research Methods’ thesis completed within the UQ Business School at The University of Queensland. We would like to thank workshop participants at the Australian National University, Swinburne University of Technology, University of Technology Sydney and Victoria University of Wellington for their comments on previous versions of the study.
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Jung, J., Herbohn, K. & Clarkson, P. Carbon Risk, Carbon Risk Awareness and the Cost of Debt Financing. J Bus Ethics 150, 1151–1171 (2018). https://doi.org/10.1007/s10551-016-3207-6
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DOI: https://doi.org/10.1007/s10551-016-3207-6