Symmetrical Information and Credit Rationing: Graphical Demonstrations

As this article shows, the pro-debtor U.S. Bankruptcy Code alone can cause credit rationing, even without asymmetrical information in the market, because the code entails substantial costs to lenders if borrowers file for bankruptcy. In the absence of bankruptcy cost, lenders are always justified in raising interest rates and clearing markets. If the bankruptcy cost is nontrivial, however, lenders' profits are concave in the relevant range of interest rates. Thus, lenders cannot always clear the market by using higher rates. The study reported here also found that the use of collateral in debt contracts can reduce rationing but that even 100 percent collateral does not eliminate all rationing possibilities. A positive relationship was found between credit risk and the amount of pledged collateral, which is not necessarily true with models based on asymmetrical information. Credit rationing describes a situation in which lenders do not raise interest rates to clear excess demand. Since the pioneering work on credit rationing in the early 1980s, most theoretical studies of credit rationing have assumed ex ante asymmetrical information between borrowers and lenders to be the underlying cause of credit rationing. The purpose of this article is to demonstrate that credit rationing can take place even if information is symmetrical. This approach is important because the current literature's partial treatment of this subject may lead practitioners and government agencies to overlook non-information-related factors that cause credit rationing when they are seeking to correct the problem. I use a simple model to demonstrate that credit rationing can take place even if information regarding investment projects and managerial behavior is symmetrical, both ex ante and ex post, between borrowers and lenders. A helpful feature of the article is that a graphical approach is used to demonstrate credit rationing. The model can be seen as a generalized version of earlier models that assumed no ex ante asymmetrical information and attributed credit rationing to bankruptcy costs. Unlike most other studies, in which credit rationing exists under sets of propositions and lemmas, the graphical representation used here has the advantage of simplicity and clarity, which should be particularly appealing to practitioners. In addition, in this article, bankruptcy costs are motivated by the design of the U.S. Bankruptcy Code, which should be of particular interest to practitioners. I specifically highlight problems in the Bankruptcy Code and practices in the bankruptcy courts in explaining the credit-rationing phenomenon. The substantial costs imposed on creditors through this channel are well established in the literature. The discussion in this article shows that pro-debtor bankruptcy proceedings often entail substantial costs to lenders when borrowers file for bankruptcy and that such costs give rise to a nonlinear function of lenders' profits with respect to interest rates. I show that credit rationing is more likely to happen when, in the presence of bankruptcy costs, a proposed investment project has a low expected return or high variance of expected return and when the opportunity cost of funds is high. The results indicate the existence of a role for government intervention in redesigning the Bankruptcy Code. The model presented in the article was also used to investigate the role of collateral in credit rationing. The results indicate that collateral in debt contracts can usually mitigate rationing problems because it compensates lenders in the event of bankruptcy and also reduces the probability of default. The model also demonstrates, however, that given nontrivial bankruptcy costs, even 100 percent collateral does not necessarily eliminate all the rationing possibilities. Another finding of using this model is that riskier borrowers pledge more collateral, which is opposite to the predictions of many asymmetrical-information-based theories. The existence of this positive relationship between collateral and credit risk draws empirical support from the literature.