Cointegration with structural changes between per capita product and income inequality in Mexico

The long-run relationship between per capita product and income inequality in Mexico is assessed for the period 1963–2010. The methodology consists of stochastic unit root techniques with structural changes. The integration and cointegration tests suggest that it is not possible to understand this link if the possibility of structural changes is not taken into account. Causality, running from per capita product to income inequality, and a negative and significant overall effect are estimated. However, after the regime shifts – mainly estimated to occur in the 1980s – the connection is no longer meaningful. This result seems to be linked to the slow growth of the Mexican economy after these structural breaks, affecting, in turn, the reductions in income inequality.     

Actors' Heterogeneity in Innovation Networks

Several interpretations converge in defining innovation networks as formed by heterogeneous actors, mainly identified in universities, research centers, and business companies. While the issue of actors' heterogeneity has generated active debate in strategy and organization studies, there has been little discussion so far in exploring the role of this diversity in innovation networks.Drawn from previous literature, we identify six attributes of actors' heterogeneity which seem to matter for the development of collaborative innovation: goals, knowledge bases, capabilities and competences, perceptions, power and position, culture. This paper is aimed at pursuing issues in need of further investigation. In particular 1. how the interplay of diverse actors' attributes shapes the interaction process in the development of collaborative innovation; 2. if and how combinations of their attributes are more likely to generate certain consequences in interaction; and 3. the degree to which heterogeneity is preferable to homogeneity for the effectiveness of innovation networks. In a recursive relationship, we also call for more research on the mechanisms that lead actors' attributes to change as an effect of interaction as well as on the interaction capabilities actors apply to manage heterogeneity.     

An extension to the classical mean–variance portfolio optimization model

Abstract

The purpose of this study is to find a portfolio that maximizes the risk-adjusted returns subject to constraints frequently faced during portfolio management by extending the classical Markowitz mean–variance portfolio optimization model. We propose a new two-step heuristic approach, GRASP & SOLVER, that evaluates the desirability of an asset by combining several properties about it into a single parameter. Using a real-life data set, we conduct a simulation study to compare our solution to a benchmark (S&P 500 index). We find that our method generates solutions satisfying nearly all of the constraints within reasonable computational time (under an hour), at the expense of a 13% reduction in the annual return of the portfolio, highlighting the effect of introducing these practice-based constraints.