Selection bias in corporate governance, accounting & finance research – board composition, CSR disclosure and ratings in critical perspective
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Corporate governance is an institutional framework that aligns firm behavior and decision-making with business objectives, ensuring transparency, accountability, and efficiency. It shapes key corporate decisions, including financing, disclosure, and board composition, making it central to accounting and finance research. A major methodological challenge in this field is sample selection bias, which arises when only observed outcomes or non-random samples are analyzed. Such bias occurs, for example, when alternative decisions are unobservable, when only rated firms are studied, or when variables are censored. This dissertation systematically examines these biases and proposes appropriate econometric techniques to address them. It consists of five contributions focusing on board gender diversity, credit ratings, and corporate social responsibility (CSR) reporting. The first study analyzes determinants of female board representation using a Tobit model to address censoring. The second investigates credit rating determinants and corrects for self-selection using a Heckman model. The remaining studies examine CSR reporting across countries and firms, applying matching techniques and addressing selection bias in large-company samples. Overall, the results highlight the crucial role of corporate governance and institutional environments in shaping corporate decisions and demonstrate the importance of correcting selection bias for reliable empirical findings.
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This item has been published with the following license: In Copyright