Working papers – 2021

This paper investigates value relevance of banking capital structure voluntary choices, their determinants, and preferred debt / equity policy models, using a unique survey-based dataset gathered through a face-to-face interview, conducted to a sample of 51 Portuguese banks’ CEOs (89.5% survey response rate), over the 1989-1998 period. Survey participants, elicited ownership structure control rights, growth opportunities, reputation in banking markets, financial flexibility, information signaling, and debt tax-shields, as some of the most relevant capital structure determinants at the bank level. The supervisory and regulatory discipline was indicated as the more influential external determinant for capital structure choice. A majority of 60 percent of state-owned bank CEOs declared a preference for following pre-determined guidelines on bank funding as capital structure policy model. Almost 53 percent of the privately-owned bank CEOs revealed a significant preference for the tradeoff capital structure policy model. The pecking order and the market-timing theories received moderate to weak preference.The paper extends the literature, providing field evidence that banking capital structure choice do matter and may be explained within the framework of the conventional corporate capital structure theory.

The past decade has witnessed a mounting interest in socially responsible mutual funds. In fact, socially responsible investment (SRI) has become quite popular, attracting increasing investment flows and moving from a niche market to a mainstream investment strategy. According to a survey by The Forum for Sustainable and Responsible Investment, the assets under management of SRI mutual funds increased by 1,000% between 1994 and 2013. Recent growth has also been relevant: between 2016 and 2018, the value of investments managed by professional asset managers increased 34%, with sustainable investment accounting for more than 50% of total professionally managed assets in Canada, Australia and New Zealand in early 2018, almost half in Europe, 26% in the United States and 18% in Japan (GSI, 2019).

Algorithms play an increasingly important role in economic activity, as they become faster and smarter. Together with the increasing use of ever larger data sets, they may lead to significant changes in the way markets work. These developments have raised concerns not only over the right to privacy and consumers’ autonomy, but also on competition. Infringements of antitrust laws involving the use of algorithms have occurred in the past. However, current concerns are of a different nature as they relate to the role algorithms can play as facilitators of collusive behavior in repeated games, and the role increasingly sophisticated algorithms can play as autonomous implementers of firms’ strategies, as they learn to collude without any explicit instructions provided by human agents. In particular, it is recognized that the use of ‘learning algorithms’ can facilitate tacit collusion and lead to an increased blurring of borders between tacit and explicit collusion. Several authors who have addressed the possibilities for achieving tacit collusion equilibrium outcomes by algorithms interacting autonomously, have also considered some form of ex-ante assessment and regulation over the type of algorithms used by firms. By using well-known results in the theory of computation, I show that such option faces serious challenges to its effectiveness due to undecidability results. Ex-post assessment may be constrained as well. Notwithstanding several challenges faced by current software testing methodologies, competition law enforcement and policy have much to gain from an interdisciplinary collaboration with computer science and mathematics.