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.     

Has the CSR engagement of electrical companies had an effect on their performance? A closer look at the environment

Even though electrical companies attain a top ranking in the publication of CSR reports, they are often accused of 'green‐washing' due to their bad environmental reputation. The current economic crisis is testing their real CSR commitment more than ever, especially when this goes beyond its economic consequences. Based on a worldwide sample of electrical companies, we are going to study why companies are being socially responsible. We wish to know if it is due to the impact on the firms' performance or whether there are other motives (legitimation, improving their reputation) that lead companies to carry out these practices. We will also consider if it changes across the kind of CSR action considered. The results show that there is an economic justification beyond the socially responsible behaviour of the electrical companies. Additionally, most kinds of CSR action (community, diversity, corporate governance, product responsibility) are also carried out looking for economic rewards. However, the CSR actions oriented to the environment are mainly motivated by their need to improve their image and reverse their negative impact. Copyright © 2014 John Wiley & Sons, Ltd and ERP Environment     

Sales forecasting in financial distribution: a comparison of quantitative forecasting methods

This paper deals with the issue of forecastability of sales activities of independent financial advisers (agents). Employing the most common quantitative methods on a diverse sample of timelines from multiple advisory companies, we have found that under most settings, these methods offer sub-par performance with high relative errors and no statistical differences between them. When a more granular approach is applied (reflecting sales unit size), ARIMA and the simple moving average emerge as significantly less accurate. This outcome is true for all sales units regardless of their size, when relative error is concerned. Thus, our analysis confirms the difficult forecastability of financial sales, speaking against the utilisation of more sophisticated forecasting methods, which mostly fail when compared to their much simpler and less costly counterparts.