These studies show interesting results about the realization of climate risk in the credit market. As a result, several studies have expressed the need to isolate the impact of climate risk on creditworthiness (Mathiesen, 2018; Monnin, 2018). It is during this search that climate risk disclosure in 10,000 filings emerges as a reasonable proxy.
First, climate risk affects the level of future cash flows of climate-relevant companies through a change that appears in the bottom line (revenue), bottom line (EBIT) and balance sheet (assets become liabilities with cash flow consequences for these liabilities). However, a generic climate risk score is no longer available in the online tool, and this measure combines several dimensions of climate risks. Based on previous literature (Bauer & Hann, 2010; Capasso et al., 2020), we formulate this relationship in the following generalized equation: 4) This model considers the generic effect of the climate risk profile (Climate) on the distance to default of company i at the end of year t ( DD).
To estimate the above equation, most previous studies on the association of climate risk (or any other type of environmental risk for that matter) and default risk use pooled ordinal least square regression [OLS] (Bauer & Hann, 2010; Capasso et al. . , 2020). Unobserved heterogeneity: There may be unobserved variations that may affect the relationship between credit risk and climate risk. 𝐷𝐷𝑖𝑡= 𝛼 + 𝛽𝑜𝐷𝐷𝑖𝑡−𝑞+ 𝛽1 𝑪𝒊𝒊𝒎𝒂𝑖 𝑚😊 (𝐷𝐷𝑖𝑡−𝑞), its climate risk profile, a vector of k firm characteristics.
The system GMM is appropriate if the conceptual relationship between firm-level default risk and climate risk is characterized using a 'level' model.
RESULTS
- Data collection
- Descriptive analysis
- The generic impact of climate risks on Merton distance to default
- The temporal effect of the Paris Agreement on the climate distress risk
- The realization of climate distress risks on issuer rating
We note that the senior unsecured rating is updated more frequently than the issuer's long-term rating. More importantly, we observe a consistent negative relationship between the different types of climate risk and distance to default, as we see that climate is more frequent. Another interesting finding is around 2015, where we observe that the gaps between firms with higher climate risk disclosure and their peer group have widened both physically and regulatoryly.
In this section, we examine the overall impact of climate risk on corporate default risk. The test is performed based on the distance to default on various climate risk measures and company characteristic variables, using lagged dependent and independent variables as instruments. These results show that the forward-looking nature of the carbon footprint may not be a good indicator of climate risk realization for companies' overall creditworthiness.
As we move into disclosure in annual filings, we continue to observe a negative relationship between climate risk profile and company financial health. However, for the rest of climate risk metrics, the full set of instruments is valid, and the validity of these sets of instruments is not driven by the deployment of instruments. It is possible that the effect of climate problems is moderated by climate regulation events.
We perform this analysis by interacting the climate risk indicators with the dummy indicator indicating the year 2015. Essentially, this is a diff-in-diff setup that effectively establishes the causality relationship between climate risk and default risk. We test for three dimensions of climate risk disclosure, namely physical risk, regulatory risk and non-specific risk.
We find that the evolving regulation strengthens the negative relationship between climate risk and distance to default. We repeat our analysis of climate risk disclosure metrics on two types of Standard and Poor's rating, that is, the long-term issuer rating and senior unsecured bond rating. We continue to find that the mention of climate risk keywords only has a weakly significant negative effect on the long-term issuer rating, and this significance disappears when the regression is carried out on the senior unsecured rating.
CONCLUSIONS
A possible explanation is that a long-term issuer rating is more about long-term consequences, while a higher unsecured rating is more about short-term effects (and therefore less persistent over time). Interestingly, rating agencies penalize companies for mentioning non-specific climate change issues in their annual filings. This may be because credit rating agencies are slow to adapt to new risks or because long-term ratings are more persistent over time.
A proposed climate stress test scenario Available at https://2degrees-investing.org/wp-content/uploads/2019/02/Stress-test-report_final.pdf. Available at https://www.wsj.com/articles/pg-e-wildfires-and-the-first-climate-change-bankruptcy. Available at https://www.reuters.com/article/us-britain-boe-carney/boes-carney-warns-of-bankruptcy-for-firms-that-ignore-climate-change-idUSKCN1UQ28K.
Integrating climate risks into credit risk assessment: current methodologies and the case of central banks' corporate bond purchases. World Resources Institute and World Business Council for Sustainable Development Available at http://www.ghgprotocol.org/sites/default/files/ghgp/standards/ghg-protocol-revised.pdf.
Panel A: Breakdown distance to default by regulatory climate risks
Panel B: Breakdown distance to default by physical climate risks
Explanation: The test is based on the levels of the business distress risk (DD) on the climate risk and the business variables. The instruments are the delayed differentiated emergency risk (L.D.DD), the delayed differentiated climate risk (L.D.Climaterisk) and the delayed differentiated business characteristics. The test statistics follow a chi-square distribution with p degrees of freedom, where p is the number of regressors tested for endogeneity.
Notes: This table provides the results of the regression of climate risks in the Merton distance model with the benchmark using the GMM system. Second and third lags of distance to default and second lags of other variables are included as instruments. The variable of interest includes the interaction term of the 2015 dummy variables with all climate risk proxies.
Notes: This table provides the regression results of climate risks Standard & Poor's Long-Term Issuer Rating and Senior Unsecured Rating on ordered probit model.
Panel B: Breakdown distance to default by regulatory climate risks
Standard & Poor's long-term issuer rating rating_spi Refinitiv Eikon Standard and Poor's long-term domestic issuer credit rating that represents the forward-looking opinion about the firm's overall creditworthiness at year-end. Standard & Poors'ssu Refinitiv Eikon Standard and Poor's Senior Unsecured Rating The long-term domestic issuer credit rating assigned to the firm's year-end senior unsecured senior unsecured debt. CI1 (CO2e-ton /mil USD revenue)1 ci1 Refinitiv ESG Field 1 emissions normalized by the firm's total revenue.
CI2 (CO2e-ton /mil USD revenue)1 ci2 Refinitiv ESG Field 2 emissions normalized by the firm's total revenue. Physical hazard keyword counts keyword_physical Ceres/CookESG Number of climate-related physical hazard keywords in 10k files. Regulatory risk keyword counts keyword_regulatory Ceres/CookESG Number of climate regulation related risk keywords in 10k files.
Non-specific risk words count keyword_non_specific Ceres/CookESG The number of climate generic-related risk keywords in 10K filing. Size - total assets (mil USD)1 ln_assets Refinitive Eikon The book value of the company's assets. Size- market value (mil USD)1 ln_market_cap Refinitiv Eikon The market value of the company's equity Capital expenditure (mil USD)1 ln_capex Refinitiv Eikon The company's capital expenditure.
Market to book (time) mtb Refinitiv Eikon The ratio of the firm's market capitalization to the book value of the firm's equity. ROA (%) roa Refinitiv Eikon The ratio of firms' net income before tax divided by. Leverage Debt Ratio (%) Refinitiv Eikon The ratio of a firm's total debt divided by the firm's total assets.
Cash ratio (%) cash ratio Refinitiv Eikon The ratio of the firms total cash and investment instrument divided by the firm's total assets Retained earnings / Assets (%) retained ratio Refinitiv Eikon The ratio of the firms total cash and investment. Idiosyncratic risk (%) idio_risk Self-calculation The variation of the residuals of the rolling 48-month window linear regression of the firm's monthly excess stock return on that of the market. Notes: This table provides the regression results of climate risks on Merton distance to default model with OLS.
