Steven L. Schwarcz is the Stanley A. Star Distinguished Professor of Law & Business at Duke University School of Law and Senior Fellow of the Centre for International Governance Innovation. This post is based on his recent paper.
Recent bank failures have spurred widespread demands to impose greater penalties on corporate managers that engage in excessive risk-taking. This is not surprising; politicians and the media tend to attribute virtually every dramatic business failure to excessive risk-taking or fraud.
In part, these responses reflect at least two cognitive biases: hindsight bias, the tendency to believe that a past event was predictable or inevitable; and ultimate attribution error, in this context, the tendency to assign responsibility for a failure to individuals, as bad actors, rather than to external factors. The result is that legislatures, including Congress, often react to failures by enacting laws that focus on preventing excessive risk-taking (and fraud) by imposing harsh managerial performance standards, without addressing the actual causes or consequences of the failures.
My article, Corporate Governance and Risk-taking: A Statistical Approach (available at http://ssrn.com/abstract=4542464), makes three related claims about corporate risk-taking. Prudent corporate governance requires managers to take business risks, much of which is data-driven and statistically based. Although excessive risk-taking and fraud cause some corporate failures, even good faith statistically based risk-taking can result in failure. The article’s first claim, therefore, is that managers should not automatically be presumed to be responsible for corporate failures that result from risk-taking decisions based on statistical methodologies that reasonably justify the decisions ex ante.
