The authors of this new corporate governance data set, Jens Frankenreiter, Cathy Hwang, Yaron Nili, and Eric L. Talley, should not be blamed for the hyperbolic claims. The University of Virginia’s story about it is. Their headline: Why Everything We Thought We Knew About Corporate Governance Is Wrong. The paper is titled more modestly and soberly: “Cleaning Corporate Governance.”
The UVA headline assumes that “everything we know about corporate governance” is based on an often-cited 2003 data set from Paul Gompers, Joy Ishii and Andrew Metrick called the “Governance Index” or “G-index.” On the contrary, while many institutional shareholders were encouraged by the link that paper made between “good governance” and shareholder value, we are not aware of anyone in the governance world (as opposed to the academic world) who took it seriously enough to, for example, base an index or investment strategy on it. Indeed, the success of commercial products from proxy advisors and firms like GMI Ratings (co-founded by the partners of this firm) are not based on the G-index but on more nuanced and more predictive data points. For example, the CEO pay-performance link. This data set, like the one before it, relies too much on what can be counted instead of what counts.
Although empirical scholarship dominates the field of law and finance, much of it shares a common vulnerability: an abiding faith in the accuracy and integrity of a small, specialized collection of corporate governance data. In this paper, we unveil a novel collection of three decades’ worth of corporate charters for thousands of public companies, which shows that this faith is misplaced. We make three principal contributions to the literature.
First, we label our corpus for a variety of firm- and state-level governance features. Doing so reveals significant infirmities within the most well-known corporate governance datasets, including an error rate exceeding eighty percent in the G-Index, the most widely used proxy for “good governance” in law and finance.
Correcting these errors substantially weakens one of the most well-known results in law and finance, which associates good governance with higher investment returns. Second, we make our corpus freely available to others, in hope of providing a long-overdue resource for traditional scholars as well as those exploring new frontiers in corporate governance, ranging from machine learning to stakeholder governance to the effects of common ownership. Third, and more broadly, our analysis exposes twin cautionary tales about the critical role of lawyers in empirical research, and the dubious practice of throttling public access to public records. [Emphasis added]Cleaning Corporate Governance by Jens Frankenreiter, Cathy Hwang, Yaron Nili, Eric L. Talley :: SSRN