Determinants of Corporate Governance Performance Based on Disclosures in Published Reports: Evidence from India

Abstract

This paper investigates the state of Corporate Governance (CG) performance in India. The main goal is to ascertain the determinants of CG through content analysis. As part of this investigation, statistical significance of categories based on CG performance index (CGPI), possibility of selective improvement of themes and analysis for ascertaining scoping and focusing of limited attributes within a theme for improvement. While at a macro level categories used mean with standard deviation rules, but at micro level homogenous clusters were identified with k mean cluster analysis within a category to enable deeper profiling. For scoping of attributes; factor analysis with Principal Component Analysis and Varimax rotation is employed. Ordinary Least Squares (OLS) regression and Ordinal Logistic Regression (OLR) are utilized in this study for econometric modeling. This study help rate the progress of reforms, plan further reforms and enable investors to choose the right firms. Major findings of the paper are; there exists statistically significant differences among categories and across theme indices. High adjusted R square linear regressions and subsequent sensitivity analysis short listed critical attributes to focus. The above findings suggest high predictive ability of OLR-OLS system of equations highlighting the possibility of focusing on limited attributes within a theme, but need for holistic approach on CG with all themes as a requirement are the inferences.

Keywords: Corporate Governance Performance Index, Themes, Attributes

JEL Classification: G34