Economic structure and key sectors analysis of greenhouse gas emissions in Uruguay

This paper identifies the key sectors in greenhouse gas emissions of the Uruguayan economy through input-output analysis. This allows to precisely determine the role played by the different productive sectors and their relationship with other sectors in the relation between the Uruguayan productive structure and atmospheric pollution. In order to guide policy design for GHG reduction, we decompose sectors liability between the pollution generated through their own production processes and the pollution indirectly generated in the production processes of other sectors. The results show that all the key polluting sectors for the different contaminants considered are relevant because of their own emissions, except for the sector Motor vehicles and oil retail trade, which is relevant in CO2 emissions because of its pure, both backward and forward, linkages. Finally, the best policy channels for controlling and reducing GHGs emissions are identified, and compared with the National Climate Change Response Plan (NCCRP) lines of action.

[The influence of the socio-economic structure of the breeding farms of Franches-Montagnes horses on the conditions of husbandry]

The socio-economic structure of the breeding farms of Franches-Montagnes horses (FM) in Switzerland is evaluated on the basis of an investigation carried out in 2002 by the Swiss FM breeding federation. Questionnaires were sent to 3500 of its members and the results include data from 968 breeding enterprises, housing a total of 3965 FM. The quality of the husbandry of FM varies according to factors such as the altitude and the geographical situation of the farms and studs. Socio-economic parameters, such as the role of FM in the business, their use (breeding, driving, riding) and the age and level of professional education of the owners may also have an effect on standards of husbandry. The results show that the owners for whom FM represent a source of income more frequently keep their horses in standing stalls, but give them more time to exercise at liberty than the horses belonging to amateur breeders. Younger and better educated breeders are more likely to house their animals in groups.

Economic structure and life of the Jews /

Mode of access: Internet.

The economic structure of the southwestern Illinois region.

[pt.1] Introduction and methodology.--[pt.2] The past and the present.--[pt.3] The future.

Clustering and hot spot detection in socio-economic spatio-temporal data

Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.

The role of no-arbitrage on forecasting: lessons from a parametric term structure model

Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.