Big Data in Corporate Governance decision

Abstract

[EN] Progress in Big Data in recent years has grown exponentially, which has allowed the detection and processing of a large amount of data. Until recently, this fact was unattainable by the lack of mechanization of the corporate governance reports. This paper investigates the relationship between corporate governance decisions affect the indebtedness policies of 1,956 industrial companies listed in Europe and the USA over the period 2016–2018 (5,868 observations). To measure corporate governance decisions, we use detailed information on the expertise of audit committees, the proportion of independent directors, board structures and women's presence on corporate boards. Our findings, which are based on a static panel data analysis, show that there is a strong negative relationship between Audit Committees expertise and indebtedness level in European and North American companies. There are also evidence that European and American companies with a onetier board structure and Audit Committees expertise are less likely to have lower level of indebtedness. Our results shed new light on corporate governance in relation to the experience of audit committees and the influence of their characteristics on indebtedness policy.