Outsourcing : the role of debt financing

This paper investigates the effect of capital structure on a firm’s choice between vertical integration and outsourcing. Suppliers use debt as a strategic instrument to collect the surplus from outsourcing, and their wealth constraint or limited liability ensures them more attractive compensation schemes. Investigating the buyer’s capital structure, we find that outsourcing with risky debt is more likely to occur for high values of the outsourcing surplus.N/

Outsourcing and vertical integration : a survey of empirical literature

This paper provides a survey of the empirical literature of outsourcing and vertical integration. This literature shows that outsourcing and integration behave in waves, with periods of greater outsourcing activity and others of a greater activity of vertical integration.N/

The role of cash on the outsourcing decision

This paper investigates the effect of cash on a firm’s choice between vertical integration and outsourcing. We model the production decision in a Principal-Agent framework, and show that what motivates the choice of outsourcing are the firms’ cost differentials in effort and the benefit provided by the supplier’s effort alone. This latter benefit is linked with greater probabilities of reaching high production values in good states of nature. Suppliers use cash as a strategic instrument to collect the surplus from outsourcing, and their wealth constraint or limited liability ensures them more attractive compensation schemes.N/

Outsourcing : a survey of theoretical models

This paper provides a survey of theoretical models of outsourcing and vertical integration. It develops an overview of the models that rely on incomplete contracting and on strategic outsourcing.N/

The impact of capital structure on the decision to outsource with long term contracts

This paper analyzes how capital structure affects the firms’ strategic choice between outsourcing with long term contracts and outsourcing to the spot market. When outsourcing to the spot market firms are exposed to price uncertainty, whereas a long term contract allows them to set in advance the outsourcing price. We show that, to the extent that leverage and uncertainty can lead to financial distress costs in bad states of nature, firms may use long term contracts as a risk management device to hedge input price uncertainty.N/

A survey of structural models of corporate debt pricing

This paper surveys the theoretical and empirical literature on structural models of corporate debt pricing. It provides an understanding of the importance of structural models in predicting credit spreads, and focuses on the role of rating, maturity, asset volatility and sector effects.N/

Mobility and market power in the Portuguese financial system

This paper investigates the level of price and non-price competition in the Portuguese financial system. We study the determinants of market power in banking and discuss the role of switching costs. We show that the degree of customer mobility is low and that price instruments have a higher impact on market share than non-price instruments.N/

Graphic calculators in the classroom: Students’ viewpoints

This paper presents the results of a study about the views and attitudes of students of a low achieving 11th grade class who were involved in an innovative experience with graphic calculators for all academic year. Contrasting the results obtained from a questionnaire and from interviews, it concludes that students tended to point some improvements in the mathematics class, but attributed their origin more to their teacher’ style and personality than to the use of this technology

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.Comment: 32 pages, 3 figure