Big Data in Corporate Governance decision

Abstract

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