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This study examines how climate change risks affect corporate credit ratings worldwide. Using a comprehensive dataset of 4427 firms across 60 countries, we find that firms in countries more susceptible to climate change receive lower credit ratings. Such a negative relation ensues from inferior firm fundamentals, such as higher default risk and cash flow volatility associated with climate-change-related uncertainties. We also find that the adverse impact of climate change risks on credit ratings impedes firms' access to debt financing and increases the costs of holding credit default swaps. Further analyses reveal that institutional factors and market attention to climate change significantly shape rating agencies' responses to climate change risks.

We study whether firms that are led by chief executive officers (CEOs) with law degrees (lawyer CEOs) have different credit ratings and costs of debt from other firms. Our sample consists of Standard & Poor’s 1500 firms from 1992 to 2020, 9.2% of which have lawyer CEOs. We find that these firms have better credit ratings, compared to other firms. On average, their cost of debt is 10% lower than that of firms led by CEOs without legal backgrounds. Our results are robust to different specifications, sampling methods, and controls, such as firm and CEO characteristics. We identify two ways that CEO expertise translates into higher credit ratings: lawyer CEOs are associated with a lower future volatility of stock returns and a reduction in information risk. The decreased business risk and better financial reporting are associated with 5% lower auditing fees for firms with lawyer CEOs.

Credit ratings play an important role as a gatekeeper of capital markets. Firms with higher credit ratings are likely to access the capital markets at a lower cost. Hence, understanding credit rating properties is essential, and this topic is of great importance for academics, regulators, and practitioners. This thesis includes three essays on credit ratings. Traditional issuer-paid credit rating agencies (CRAs hereafter) such as Standard & Poor’s (S&P hereafter), Moody’s and Fitch Ratings (Fitch hereafter) have faced criticisms about the lack of timeliness and accuracy in negative signals due to the conflict of interest in their business model. However, this is not the case for the positive signals. In contrast, investor-paid CRAs, without conflict of interest in their business model, issue more timely and accurate negative signal. The first essay investigates how institutional investors who have advanced trading skills and knowledge respond to credit rating changes issued by two types of CRAs: issuer- and investor-paid CRAs. I find that investors react asymmetrically: they abnormally sell stocks surrounding rating downgrades by investor-paid CRAs, while abnormally buying stocks around rating upgrades by issuer-paid CRAs. In contrast, they have no significant reaction to positive signals from the investor-paid CRA and negative signals from the issuer-paid CRAs. The first essay suggests that, through their trades, institutional investors do capitalize on value-relevant rating information: negative and positive signals provided by investor- and issuer-paid CRAs respectively. More importantly, I further find that a dynamic trading strategy specifically based on rating downgrades by investor-paid CRA and rating upgrades by issuer-paid CRAs generates significant abnormal returns. The second essay focuses on the relationship between politics and credit ratings. Specifically, I investigate whether political similarities between CRAs and bond issuers impact credit ratings. I find that a higher degree of similarity of political affiliation leads to a decrease in timeliness and accuracy of rating downgrades prior to default events. The findings support the notion that CRAs tend to maintain/assign relative rating advantages to politically similar firms via favourable rating activities. I further show that these politically similar firms tend to increase the proportion of political donations to their favoured party following favourable credit ratings. Interestingly, this result is confined to Republican-leaning firms. The results indicate that CRAs successfully use biased credit ratings as an indirect channel of political party support. The second essay thus contributes to the body of knowledge on the importance of political connections in corporate finance as well as CRAs’ rating behaviours. The third essay examines the effect of natural disasters on credit ratings. Natural disasters are exogenous shocks to CRAs’ rating behaviours. I find that firms located in the disaster states (i.e., affected firms) are downgraded by CRAs. I also find the same patterns in changes in stock returns of affected firms. The findings support hypothesis that credit rating changes are driven by firm’s fundamental changes caused by natural disasters. By using instrumental variable (IV) analysis to extract affected firms’ rating changes caused by natural disasters, I further investigate the spill-over effects of natural disasters on rating changes of non-affected firms (i.e., firms are not located in the disaster states). I find that the affected firms’ rating changes positively spill-over to connected firms’ rating changes which are not directly impacted by natural disasters. Connected firms are selected from the same industry, the adjoining states, or supplier-customer relationships with the affected firms. I also find the negative spill-over effects from the affected firms’ rating changes to their competitors’ rating changes. Finally, I replicate the spill-over channels for stock returns, a proxy for market reactions to natural disasters, and find delays in the stock return spill-over. This is significant evidence on CRAs’ sensitivity to natural extreme events.

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