- Ler AbstractAbstract: We examine the factors that influence nonfinancial firms’ choice of issuing standard corporate
bonds vis-à-vis contracting structured finance transactions, in the form of project finance or
asset securitization deals. Using a data set of deals closed by 4,700 European borrowers between
2000 and 2016, we find that informational and agency problems, and issuance costs, affect
public firms’ borrowing source choices. Findings also suggest that firms choose structured
finance borrowings when they are less profitable and have lower asset tangibility. Our findings
document that transaction cost considerations lead firms that use both structured finance and
corporate bond deals during our sampling period, to choose structured finance for new
borrowings. Additionally, firms resorting to project finance are less creditworthy than corporate
bond issuers are and, on average, asset securitization deals have a funding cost advantage of
87.6 basis points over corporate bond deals.
002 – Does Internal Capital Market Membership Matter for Financing Efficiency? Evidence from the Euro AreaJorge Humberto Mota, Mário Coutinho dos SantosLer AbstractAbstract: The paper investigates the efficiency of firms’ financing behavior, exploring the effect of the internal capital market (ICM) organizational form on the differences in the cost of capital, capital structure, and the speed of adjustment towards preferred capital structure, between ICM participants and stand-alone peer firms, using two balanced comparable panel data sets of euro area firms of 773 firms each, over the 2004–2013 period. Results from univariate parametric and non-parametric testing, indicate that firms operating within an active ICM exhibit, on average, lower costs of capital than their comparable stand-alone counterparts. The paper also documents that on average financial leverage ratios are significantly higher for ICM firms than for stand-alone, and that both ICM and stand-alone firms tend to have preferred target leverage ratios. Bias-corrected dynamic panel data regression estimators, document that subsidiaries of diversified firms adjust dynamically their financial leverage ratios towards their preferred targets, at similar speeds for the two types of organizational form firms. These findings are consistent with the view that ICM membership is linked to information and agency problems, lowering ICM participants’ cost of capital, having target leverage ratios, and adjusting their capital structures similarly to their stand-alone peers.
003 – Does Internal Capital Market Membership Matter for Capital Allocation? Theory and Evidence from the Euro AreaJorge Humberto Mota; Mário Coutinho dos SantosLer AbstractAbstract:This paper investigates the capital allocative behavior of firms’ integrating active internal capital markets (ICM). Specifically, examines the investment-cash flow sensitivity and its relationship with factors, such as, financial flexibility, suboptimality of investment expenditure, and crosssubsidization, using a matched sample design of two comparable panel data sets of 636 subsidiaries and stand-alone firms of the euro area, over the 2004–2013 sampling period.
Results from panel data regression document that ICM firms exhibit lower sensitivity to the availability of internal funding than pure-play stand-alone firms, and that for stand-alone firms the effect of financial flexibility on investment-cash flow sensitivity is larger than for ICM cohorts. Findings also document that, on average, subsidiaries experience lower levels of investment suboptimality, and that subsidiaries with poor growth opportunities, ceteris paribus, invest less than pure-play stand-alone firms, consistent with lower cross-subsidization problems within ICMs.
These findings are consistent with the propositions that centralized capital budgeting systems can potentially mitigate informational and incentive problems associated with investment behavior, and that subsidiary firms may use internal capital markets as a substitute for financial slack.
004 – Controlling Algorithmic Collusion: Short Review of the Literature, Undecidability, and Alternative ApproachesJoão GataLer AbstractAbstract: Algorithms have played an increasingly important role in economic activity, as they becoming 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 been raising concerns not only over the rights 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 pricing strategies, learning 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 face by current software testing methodologies, competition law enforcement and policy have much to gain from an interdisciplinary collaboration with computer science and mathematics.
- Ler AbstractAbstract: This paper proposes a model aiming at quantifying the impact that volume uncertainty may produce on construction projects’ value and on the optimal bid price. Volume uncertainty is present in most construction projects since managers do not know, during the bid preparation stage, the exact volume of work that will be executed during the project’s life cycle. Volume uncertainty leads to profit uncertainty and hence the model integrates a discrete-time stochastic variable, designated as “additional value”, i.e., the value that does not directly derive from the execution of the tasks specified in the bid documents, and which can only be properly quantified by undertaking an incremental investment in human capital and technology. The model determines that, even only recurring to the skills of their own experienced staff, contractors will produce a more competitive bid provided that the expected amount for the additional profit is greater than zero. However, construction managers often need to hire specialized firms and highly skilled professionals in order to quantify the expected amount of additional value and, hence, the impact of such additional value in the optimal bidding price. Based on the option to sign the contract and to perform the project by the selected bidder, identified and evaluated by Ribeiro et al. (2017), the model’s outcome is the threshold value for this incremental investment. A decision rule is then reached: construction managers should invest in human capital and technology provided that the cost of such incremental investment does not exceed the predetermined threshold value.