The current European debt crisis has drawn considerable attention to credit-rating agencies' news about sovereign ratings. From a technical point of view, credit rating constitutes a typical ordinal regression problem because credit-rating agencies generally present a scale of risk composed of several categories. This fact motivated the use of an ordinal regression approach to address the problem of sovereign credit rating in this paper. Therefore, the ranking of different classes will be taken into account for the design of the classifier. To do so, a novel model is introduced in order to replicate sovereign rating, based on the negative correlation learning framework. The methodology is fully described in this paper and applied to the classification of the 27 European countries' sovereign rating during the 2007-2010 period based on Standard and Poor's reports. The proposed technique seems to be competitive and robust enough to classify the sovereign ratings reported by this agency when compared with other existing well-known ordinal and nominal methods.

About one third of food produced for human consumption is lost or wasted. For this reason, food losses and waste has become a key priority within worldwide policy circles. This is a major global issue that not only threatens the viability of a sustainable food system but also generates negative externalities in environmental terms. The avoidance of this forbidding wastage would have a positive economic impact on national economies in terms of resource savings. In this paper we look beyond this somewhat traditional resource savings angle and we shift the focus to explore the distributional consequences of food losses and waste reduction using a resource constrained modeling perspective. The impact due to the behavioral shift of each household is therefore explained by two factors. One is the amount of resources saved when the behavioral shift takes place, whereas the other one has to do with the position of households in the food supply chain. By considering the whole supply chain, instead of the common approach based only in reducing waste by consumers, we enrich the empirical knowledge of this issue and improve the quantification of its economic impact. We examine data for three EU countries that present different economic structures (Germany, Spain and Poland) so as to have a broader and more robust viewpoint of the potential results. We find that distributional effects are different for consumers and producers and also across countries. Our results could be useful for policymakers since they indicate that policies should not be driven merely by the size waste but rather on its position within the food supply chain.

Valoración del impacto de la industria automotriz en la economía mexicana: una aproximación mediante matrices de contabilidad social