Corporate governance and carbon performance and disclosure : Australian experience

Abstract

There has been a global consensus that GHG emissions including carbon dioxide (CO2) are the main cause of climate change and global warming, which can have a significant impact on business activity and behaviour (Saka and Oshika, 2014). Thus, carbon information has become more and more important for stakeholders to make an informed decision about a company's GHG emissions performance (Luo & Tang, 2014a&b; Rankin et al. 2011; Tang & Luo, 2014; Luo et al. 2013; Luo & Tang, 2015). However, there is criticism that companies tend to disclose some unreliable climate change related information (Kolk et al. 2008). It can be argued that corporate governance plays a critical role in determining how companies are responding to climate change. This is because companies that have a high quality of corporate governance are more likely to integrate climate change into their business strategy and are more likely to maintain the long term commitment to effectively address climate change risks and opportunities across their entire operating system. But there is limited empirical evidence about this (Liao et al. 2014). The purpose of this thesis is, therefore, to investigate two empirical issues. First, it investigates the effect of corporate governance mechanisms (board size, board independence, board diversity, board meetings, audit committee independence, environmental committee presence, CEO stock option, CEO long term bonus, ownership concentration and managerial ownership), on carbon performance. Second, this study examines the relationship between corporate governance mechanisms and the extensiveness of carbon disclosure. The sample of this study consisted of an unbalanced panel set of 205 firm-year observations from the largest Australian companies that participated in the Carbon Disclosure Project (CDP) questionnaire survey over a period of four years (2009-2012). Twenty hypotheses are developed and tested using Ordinary Least Squares (OLS) multiple regression analysis to identify the correlation between corporate governance structures and carbon performance and disclosure together with the possible impact of the institutional environment in determining this relationship.

Date of Award	2015
Original language	English