Medición y comprensión del comercio de tareas en el sector de los servicios

La revolución de las TIC ha generado un alto riesgo de deslocalización de las tareas más comercializables en el sector de los servicios. Se revisan aquí estudios que proponen indicadores de comerciabilidad de los servicios, exploran las implicaciones de su deslocalización y desarrollan modelos teóricos al respecto. Tanto el nivel de calificación requerido como la comerciabilidad podrían ser determinantes clave de los efectos sobre los salarios y el empleo. Sin embargo, la falta de definiciones consensuadas de comerciabilidad y de datos fiables sobre el comercio de servicios, junto con la dificultad de evaluar la competencia de las importaciones a niveles desagregados, obstaculizan el avance de los estudios empíricos y descubren áreas para futuras investigaciones.     

Sparse Partial Least Squares in Time Series for Macroeconomic Forecasting

Factor models have been applied extensively for forecasting when high‐dimensional datasets are available. In this case, the number of variables can be very large. For instance, usual dynamic factor models in central banks handle over 100 variables. However, there is a growing body of literature indicating that more variables do not necessarily lead to estimated factors with lower uncertainty or better forecasting results. This paper investigates the usefulness of partial least squares techniques that take into account the variable to be forecast when reducing the dimension of the problem from a large number of variables to a smaller number of factors. We propose different approaches of dynamic sparse partial least squares as a means of improving forecast efficiency by simultaneously taking into account the variable forecast while forming an informative subset of predictors, instead of using all the available ones to extract the factors. We use the well‐known Stock and Watson database to check the forecasting performance of our approach. The proposed dynamic sparse models show good performance in improving efficiency compared to widely used factor methods in macroeconomic forecasting. Copyright © 2014 John Wiley & Sons, Ltd.     

Product Market Competition,Monetary Policy Regimes and Inflation Dynamics: Evidence from a Panel of OECD Countries

We empirically analyze the impact of product market competition on the responsiveness of inflation to macroeconomic imbalances. If competition is high the response of inflation to lagged inflation, unemployment and import prices is reduced, while inflation is more responsive to changes in productivity growth in countries in which competition is above the OECD average. Given the (‘good luck’) macroeconomic trajectories of the 1990s–2000s, the structural reforms that made goods markets more competitive improved the ability of OECD economies to smooth (dis)inflationary shocks, while changes in the monetary policy framework had a modest role in taming inflation during the Great Moderation.     

Can environmentally oriented CEOs and environmentally friendly suppliers boost the growth of small firms?

The core question addressed in the natural resource‐based view (NRBV) of the firm is how to develop and exploit resources beneficial for both the natural environment and firm performance. Due to the resource constraints and increased competition facing small manufacturing firms, achieving this is a challenge for such companies. Building on the NRBV and resource orchestration literatures, we examine the relationship between green purchasing capabilities (GPCs), CEO's environmental orientation (EO), and firm growth. Results from 304 Swedish small manufacturing firms indicate a significant relationship between GPC and growth, and this relationship is positively moderated by the EO of the CEO.     

The evolution of world trade from 1995 to 2014: A network approach

This paper employs network analysis to study world trade from 1995 to 2014. We focus on the main connective features of the world trade network (WTN) and their dynamics. Results suggest that countries’ efforts to attain the benefits of trade have resulted in an intertwined network that is increasingly dense, reciprocal, and clustered. However, these features do not correspond to a linear aggregation of the characteristics of its constituents (trade sectors). Trade linkages are distributed homogeneously among countries, but their intensity (i.e. their value) is highly concentrated in a small set of countries. The main connective features of the WTN were not affected by the 2007–2008 international financial crisis. However, we find that the crisis marks a turning point in the evolution of the WTN from a two-group (led by the US and Germany) to a three-group (led by the US, Germany, and China) hierarchical structure.     

Subsidiary-specific advantages for inter-regional expansion: The role of intermediate units

This paper explores the distinctive deployment of resources and capabilities by subsidiaries in order to develop an intermediate role within the MNC. Based on the regional management perspective, we focus on a specific intermediate role—the springboard subsidiary—that helps overcome the liability of inter-regional foreignness. Our results, which are based on a dataset covering 188 subsidiaries, show that the probability of taking on this role is contingent upon experiential knowledge about the target region, as well as a rich knowledge base derived from a wide range of activities and a broad geographical scope. Our findings also show that possession of slack resources does not necessarily mean that a subsidiary will take on this role, as such slack must be combined with experiential knowledge. This paper serves as a first step in helping MNCs plan resource allocation to handle inter-regional expansion.     

Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix

This paper studies a robust continuous‐time Markowitz portfolio selection problem where the model uncertainty affects the covariance matrix of multiple risky assets. This problem is formulated into a min–max mean‐variance problem over a set of nondominated probability measures that is solved by a McKean–Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman–Isaacs equation in the Wasserstein space of probability measures. We provide explicit solutions for the optimal robust portfolio strategies and illustrate our results in the case of uncertain volatilities and ambiguous correlation between two risky assets. We then derive the robust efficient frontier in closed form, and obtain a lower bound for the Sharpe ratio of any robust efficient portfolio strategy. Finally, we compare the performance of Sharpe ratios for a robust investor and for an investor with a misspecified model.