Corporate Governance and Performance: New Evidence Using Nonlinear Principal Component Analysis

Abstract

This study revisits the link between corporate governance and performance using a carefully assembled dataset of UK-listed companies. A key aspect of our study is the use of Nonlinear Principal Component Analysis (NLPCA), which is preferred to standard principal component analysis as a more effective method to distill the complex dimensions of corporate governance into reliable summary scores. Our analysis suggests that there are two important dimensions of corporate governance. The first relates to the nature of the internal board processes within a corporation and the incentives of managers to expropriate wealth from shareholders. The second relates to the ability of large/controlling shareholders to exert a monitoring role and provide strong oversight of management performance. Using a GMM-based framework, we find that the first dimension of governance has a modest association with operating measures of performance (i.e. ratio of earnings to total assets, ROA) but not with market-based measures of performance (i.e. Tobin’s Q). On the other hand, the second dimension of governance strongly explains market-based but not operating measures of performance. The empirical findings also indicate that the magnitude of the economic significance of the governance proxies in the performance models, as well as the ranking of firms in terms of corporate governance quality, critically depends on the method utilized to measure corporate governance.

Keywords: Corporate Performance, Corporate Governance, Nonlinear Principal Component Analysis, UK Firms

JEL Classification: G3, G32