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Purpose: Regionalised characterisation factors (CFs) for watersheds around the world are available to assess water-use-related environmental impacts. The main problem with using the watershed regionalisation level arises when a single CF is generated for large watersheds in countries where water availability and demand are not uniform. Additionally, water availability and use vary over time because of the effects of climate change and changing human lifestyles. These two factors are currently not taken into account in CFs, but should be included for the sake of the accuracy of LCA results. The aim of this research was to provide water stress index CFs at the sub-watershed spatial level for three temporal scenarios (present, short-term future and mid-term future) for Spain (Southern Europe), a country with considerably variability in water availability that is especially vulnerable to climate change effects. Methods: CFs were calculated following the water stress index (WSI) definition of Pfister et al. (2009). The WSI was calculated on a yearly basis for 117 sub-watersheds - compared to 56 regionalisation units provided in the original method - and for (i) the current situation: current water use and availability; (ii) short-term future: projections for 2015; and (iii) mid-term future: projections for 2030. The uncertainties of the CFs were calculated for each sub-watershed. Results and discussion: Temporal trend analysis of the CFs showed a general relaxation of water stress over the short-term when compared to the current situation, followed by a new increase. Major differences were noticed in the WSIs calculated by Pfister et al. (2009) using global data and maps and the WSIs calculated in this study using national and regional data. The WSIs under consideration of uncertainty were higher than the deterministic result for intermediate WSIs. Conclusions and outlook: The CFs generated are useful compared with the CFs previously available because they improve evaluation of the water-use-related impacts of present and future technologies with the life cycle stages located in Spain. We encourage LCA developers to update WSIs for other countries using information at the national level that is usually freely accessible. / Dans l'Analyse de Cycle de Vie (ACV), il y a des facteurs de caractérisation (FC) à l'échelle du bassin-versant pour le monde entier et basés sur des données des années 1990. Dans ce travail, des facteurs de caractérisation de stress hydrique à l'échelle du sous-bassin versant pour trois scénarios temporels (présent, futur à court terme et futur à moyen terme) ont été développés pour l'Espagne.

We measure volatility spread among countries and summarize it into a volatility spillover index to provide a measurement of such interdependence. Our spillover index is based on the forecast error variance decomposition (FEVD) for a VAR model at h-step ahead forecast, and we construct it using both the orthogonalized FEVD and the generalized FEVD (GFEVD); both of them provide similar results, but the generalized version is easier to handle when a data set with more than 6 variables is involved and non theory in available to impose the restrictions needed by the orthogonal version; this is true since the GFEVD does not depend on the restrictions imposed by the Choleski decomposition. This fact makes it attractive when economic theory does not fit well with variables relationship. An R package for reproducing this chapter estimations is entirely developed.

We analyze whether the crisis sourced in US is spread over the world by contagion or through interdependence. Within this work, contagion is defined as a significant increase in cross-correlations after a crisis hits a country, we assumed that correlations are not constant over time and also evolve according to a GARCH(1,1)-type structure which give rise to the use of the popular DCC model introduced by Engle (2002) and extended in Colacito et al. (2011) to disentangle the short and long run component of the total correlation of the portfolio under study. We link interdependence with long-run fluctuations in correlations and contagion is associated with the short-run correlations.