Non-Linear Implications of Credit Ratings in the Selection of Capital Providers and their Validity as Hidden Information Indicators

Syed, Zeeshan Ali

Abstract

The Credit Ratings (CR) and Capital Structure (CR-CS) hypothesis asserts that CR influence firms' debt levels. This study argues that CR as an indicator of hidden information is more influential in determining the choice of Capital Providers (CP). Using a sample of 629 firms and 12,580 firm-year observations, we find that firms use their credit ratings to choose their preferred type of capital providers. This study not only establishes that "firms do care about their capital providers," but it also adds CR as a reliable predictor of such considerations.
This study establishes that managers adopt utility maximising behaviour when choosing their capital providers. Firms differentiated by their credit ratings are likely to choose different capital providers. This study finds that higher rated firms prefer public debt. The preference of public debt is valid under different model settings. We also observe that financial distress, indicated by the current rating of firms, is a significant determinant of the choice of private debt over public debt.
In addition to conventional specifications of CR, this study constructs a new CR specification called realised rating change and historical ratings. This study establishes that the realised rating changes and historical credit ratings influence the choice of capital providers. Evidence indicates that after having a rating adjustment which we call realised rating, firms are more likely to use public providers.
This could be indicative of the fact that after a rating upgrade manager expects public capital providers to ask lower premiums. Alternatively, after rating downgrade they want to test the investors' perception about the creditworthiness of their firm. Our results are robust in the presence of other hidden information indicators and other CR variants. These results are controlled for the financial distress concerns.
This study also extends choice modelling in CS and CR discussion. It shows that revealed preference choice modelling can produce more robust results. Choice modelling allows us to study the utility maximising behaviour of firms and managers and identifies the non-linear implications of CR on financing choices. Using such an approach may enable us to bridge the theoretical gap between monetary economics and corporate finance. The first usually concerns relationship lending or bank lending to firms, and the latter focuses on financial innovation and engineering to raise capital. By combining both strands, we may better understand why managers often make financial decisions contrary to the expected pattern.
More research using the advanced choice models may enable us to understand persistent irregularities found in corporate financing choices. As these models allow researchers to relax IID and IIA assumptions; hence, they can enable derivation of predictive models which capture complex managerial behaviour. As firms are moving away from the traditional financing medium and looking to explore options such as crowdfunding and digital assets. Therefore, understanding complex behaviour is needed now more than ever.

• Thesis Type: Thesis
• Deposit Date: Apr 12, 2022
• Publicly Available Date: Apr 12, 2022