Like most forms of ESG analysis, governance analysis has traditionally relied almost exclusively on self-reported information, or metrics derived from self-report information. This reliance on self-reported information is likely even greater when it comes to the topic of governance given that there is a lot of governance data already available. For the most part, companies are obligated to publish a lot of information that is relevant to governance analysis, such as board composition, executive compensation, shareholder rights, and audit and oversight information. Section 1 discusses datasets for analysing Corporate Governance, and the subtopics of the board, pay, ownership and control, and accounting. Section 2 provides a deep dive on the topic of corporate behavior, encompassing the subtopics of business ethics, anti-competitive practices, corruption and instability, financial system instability, and tax transparency. Finally, in Section 3 we explore other alternative data approaches to governance analysis, most notably environmental risks scoring and AI & NLP techniques for governance analysis.
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