Analysis and optimization of the satellite-to-plane link of an aeronautical global system

En aquest projecte s’ha analitzat i optimitzat l’enllaç satèl·lit amb avió per a un sistema aeronàutic global. Aquest nou sistema anomenat ANTARES està dissenyat per a comunicar avions amb estacions base mitjançant un satèl·lit. Aquesta és una iniciativa on hi participen institucions oficials en l’aviació com ara l’ECAC i que és desenvolupat en una col·laboració europea d’universitats i empreses. El treball dut a terme en el projecte compren bàsicament tres aspectes. El disseny i anàlisi de la gestió de recursos. La idoneïtat d’utilitzar correcció d’errors en la capa d’enllaç i en cas que sigui necessària dissenyar una opció de codificació preliminar. Finalment, estudiar i analitzar l’efecte de la interferència co-canal en sistemes multifeix. Tots aquests temes són considerats només per al “forward link”. L’estructura que segueix el projecte és primer presentar les característiques globals del sistema, després centrar-se i analitzar els temes mencionats per a poder donar resultats i extreure conclusions.

Inequality across countries in energy intensities: an analysis of the role of energy transformation and final energy consumption

This paper analyzes the role of the energy transformation index and of final energy consumption per GDP unit in the disparities in energy intensity across countries. In that vein, we use a Theil decomposition approach to analyze global primary energy intensity inequality as well as inequality across different regions of the world and inequality within these regions. The paper first demonstrates the pre-eminence of divergence in final energy consumption per GDP unit in explaining global primary energy intensity inequality and its evolution during the 1971-2006 period. Secondly, it shows the lower (albeit non negligible) impact of the transformation index in global primary energy inequality. Thirdly, the relevance of regions as unit of analysis in studying crosscountry energy intensity inequality and their explanatory factors is highlighted. And finally, how regions around the world differ as to the relevance of the energy transformation index in explaining primary energy intensity inequality.

A never-ending debate: Demand versus supply water policies. A CGE analysis for Catalonia

Water scarcity is a long-standing problem in Catalonia, as there are significant differences in the spatial and temporal distribution of water through the territory. There has consequently been a debate for many years about whether the solution to water scarcity must be considered in terms of efficiency or equity, the role that the public sector must play and the role that market-based instruments should play in water management. The aim of this paper is to use a Computable General Equilibrium (CGE) model to analyze the advantages and disadvantages associated with different policy instruments, from both a supply and a demand viewpoint, which can be applied to water management in Catalonia. We also introduce an ecological sector in our CGE model, allowing us to analyze the environmental impact of the alternative policies simulated. The calibration of the exogenous variables of the CGE model is performed by using a Social Accounting Matrix (SAM) for the Catalan economy with 2001 data. The results suggest that taking into account the principle of sustainability of the resource, the policy debate between supply and demand in water policies is obsolete, and a new combination of policies is required to respect the different values associated with water. Keywords: Water Policies; Computable General Equilibrium Model; Economic Effects; Environmental Effects.

A correlation sensitivity analysis of non-life underwriting risk in solvency capital requirement estimation

This paper analyses the impact of using different correlation assumptions between lines of business when estimating the risk-based capital reserve, the Solvency Capital Requirement (SCR), under Solvency II regulations. A case study is presented and the SCR is calculated according to the Standard Model approach. Alternatively, the requirement is then calculated using an Internal Model based on a Monte Carlo simulation of the net underwriting result at a one-year horizon, with copulas being used to model the dependence between lines of business. To address the impact of these model assumptions on the SCR we conduct a sensitivity analysis. We examine changes in the correlation matrix between lines of business and address the choice of copulas. Drawing on aggregate historical data from the Spanish non-life insurance market between 2000 and 2009, we conclude that modifications of the correlation and dependence assumptions have a significant impact on SCR estimation.

Modelos de viento aplicados a la mejora en la predicción de incendios forestales

La predicción de incendios forestales es uno de los grandes retos de la comunidad científica debido al impacto medioambiental, humano y económico que tienen en la sociedad. El comportamiento de este fenómeno es difícil de modelar debido a la gran cantidad de variables que intervienen y la dificultad que implica su correcta medición. Los simuladores de fuego son herramientas muy útiles pero, actualmente, los resultados que obtenemos tienen un alto grado de imprecisión. Desde nuestro grupo se ha trabajado en la predicción en dos etapas, donde antes de realizar cualquier predicción, se incorpora una etapa de ajuste de los parámetros de entrada para obtener mejores predicciones. Pese a la mejora que supone este nuevo paradigma de predicción, las simulaciones sobre incendios reales tienen un alto grado de error por el efecto de las condiciones meteorológicas que, usualmente, varían de manera notable durante el transcurso de la simulación. Uno de los factores más determinantes en el comportamiento de un incendio, junto con las características del terreno, es el viento. Los modelos de predicción son extremadamente sensibles al cambio en los componentes de dirección y velocidad del viento por lo que cualquier mejora que podamos introducir para mejorar la calidad de estas componentes influye directamente en la calidad de la predicción. Nuestro sistema de predicción utiliza la dirección y velocidad del viento de forma global en todo el terreno, y lo que proponemos con este trabajo es introducir un modelo de vientos que nos permita generar vientos locales en todas las celdas en las que se divide el terreno. Este viento local dependerá del viento general y de las características del terreno de dichas celdas. Consideramos que la utilización de un viento general no es suficiente para realizar una buena predicción del comportamiento de un incendio y hemos comprobado que la inclusión de un simulador de campo de vientos en nuestro sistema puede llegar a mejorar nuestras predicciones considerablemente. Los resultados obtenidos en los experimentos sintéticos que hemos realizado nos hacen ser optimistas, puesto que consideramos que la inclusión de componentes de viento locales permitirá mejorar nuestras predicciones en incendios reales.

Evaluation of subsidies programs to sell green cars: Impact on prices, quantities and efficiency

During the recent period of economic crisis, many countries have introduced scrappage schemes to boost the sale and production of vehicles, particularly of vehicles designed to pollute less. In this paper, we analyze the impact of a particular scheme in Spain (Plan2000E) on vehicle prices and sales figures as well as on the reduction of polluting emissions from vehicles on the road. We considered the introduction of this scheme an exogenous policy change and because we could distinguish a control group (non-subsidized vehicles) and a treatment group (subsidized vehicles), before and after the introduction of the Plan, we were able to carry out our analysis as a quasi-natural experiment. Our study reveals that manufacturers increased vehicle prices by the same amount they were granted through the Plan (1,000 €). In terms of sales, econometric estimations revealed an increase of almost 5% as a result of the implementation of the Plan. With regard to environmental efficiency, we compared the costs (inverted quantity of money) and the benefits of the program (reductions in polluting emissions and additional fiscal revenues) and found that the Plan would only be beneficial if it boosted demand by at least 30%.

Productivity and human capital: a business-level analysis

This paper aims to analyse the impact of human capital on business productivity, focusing the analysis on the possible effect of the complementarity that exists between human capital and new production technologies, particularly advanced manufacturing technologies (AMTs) for the specific case of small and medium enterprises (SMEs) in Catalonia. Additionally, following the theory of skill-biased technological change, the paper analyses whether technological change produces bias exclusively in the skills required for managers, or whether the bias extends to the skills required of production staff. With this objective, we have compared the possible existence of complementarity between AMTs and the level of human capital for different occupational groups. The results confirm the complementary relationship between human capital and new production technologies. The results by occupational group confirm that to maximise the productivity of new technologies, skilled staff are needed both in management and production, with managers and professionals as well as skilled operatives playing a vital role. Keywords: human capital, process technologies, complementarity, business productivity. (JEL D24, J24, O30).

Workers cooperation within the firm: an analysis using small and medium size firms

We investigate the determinants of teamwork and workers cooperation within the firm. Up to now the literature has almost exclusively focused on workers incentives as the main determinants for workers cooperation. We take a broader look at the firm's organizational design and analyze the impact that different aspects of it might have on cooperation. In particular, we consider the way in which the degree of decentralization of decisions and the use of complementary HRM practices (what we call the .rm.s vertical organizational design) can affect workers'collaboration with each other. We test the model's predictions on a unique dataset on Spanish small and medium size firms containing a rich set of variables that allows us to use sensible proxies for workers cooperation. We find that the decentralization of labor decisions (and to a less extent that of task planning) has a positive impact on workers cooperation. Likewise, cooperation is positively correlated to many of the HRM practices that seem to favor workers'interaction the most. We also confirm the previous finding that collaborative efforts respond positively to pay incentives, and particularly, to group or company incentives.

High Growth Firms and Innovation: an empirical analysis for Spanish firms

This paper analyzes the effect of firms’ innovation activities on their growth performance. In particular, we observe how important innovation is for high-growth firms (HGFs) for an extensive sample of Spanish manufacturing and services firms. The panel data used comprises diverse waves of Spanish CIS over the the period 2004-2008. First, a probit analysis determines whether innovation affects the probability of being a high-growth firm. And second, a quantile regression technique is applied to explore the determinants and characteristics of specific groups of firms (manufacturing versus service firms and high-tech versus low-tech firms). It is revealed that R&D plays a significant role in the probability of becoming a HGF. Investment in internal and external R&D per employee has a positive impact on firm growth (although internal R&D presents a significant impact in the last quantiles, external R&D is significant up to the median). Furthermore, we show evidence that there is a positive impact of employment (sales) growth on the sales (employment) growth. Keywords: high-growth firms, firm growth, innovation activity JEL Classifications: L11, L25, O30

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Error and complexity of random walk Monte Carlo radiosity

The author studies the error and complexity of the discrete random walk Monte Carlo technique for radiosity, using both the shooting and gathering methods. The author shows that the shooting method exhibits a lower complexity than the gathering one, and under some constraints, it has a linear complexity. This is an improvement over a previous result that pointed to an O(n log n) complexity. The author gives and compares three unbiased estimators for each method, and obtains closed forms and bounds for their variances. The author also bounds the expected value of the mean square error (MSE). Some of the results obtained are also shown

Do Fiscal and Political Decentralization Raise Students’ Performance? A Cross-Country Analysis

The low quality of education is a persistent problem in many developed countries. Parallel to in the last decades exists a tendency towards decentralization in many developed and developing countries. Using micro data from the Programme for International Student Assessment (PISA) referred to 22 countries, we test whether there exists an impact of fiscal and political decentralization on student performance in the areas of mathematics, reading skills and science. We observe that fiscal decentralization exerts an unequivocal positive effect on students’ outcomes in all areas, while the effect of political decentralization is more ambiguous. On the one hand, the capacity of the subnational governments to rule on its region has a positive effect on students’ performance in mathematics. On the other hand, the capacity to influence the country as a whole has a negative impact on mathematics achievement. As a general result, we observe that students’ performance in Mathematics is more sensible to these exogenous variations than in Sciences and reading skills. Keywords: School outcomes, PISA, fiscal decentralization, political decentralization JEL codes: H11, H77, I21

The Common Strategy on the Mediterranean Region: Evidence and Analysis

The present working paper aims at assessing the Common Strategy on the Mediterranean, taking into account its possible articulation as a coherent instrument of the European Foreign Policy. The study wants to answer some questions related to this instrument. The Common Strategy on the Mediterranean is an excellent case study and is a potential source of several questions about the external action of the European Union. Specifically, the present study has in mind two main questions to answer. Firstly, which are the main reasons behind the adoption of this instrument of the European Foreign Policy? In other words, which was/is the rationale for the existence of this Common Strategy? Secondly, which is the real impact of the Common Strategy? Which are its real achievements?

Basis set superposition error-counterpoise corrected potential energy surfaces : application to hydrogen peroxide ... X (X=F-, Cl-, Br-, Li+, Na+) complexes

Møller-Plesset (MP2) and Becke-3-Lee-Yang-Parr (B3LYP) calculations have been used to compare the geometrical parameters, hydrogen-bonding properties, vibrational frequencies and relative energies for several X- and X+ hydrogen peroxide complexes. The geometries and interaction energies were corrected for the basis set superposition error (BSSE) in all the complexes (1-5), using the full counterpoise method, yielding small BSSE values for the 6-311 + G(3df,2p) basis set used. The interaction energies calculated ranged from medium to strong hydrogen-bonding systems (1-3) and strong electrostatic interactions (4 and 5). The molecular interactions have been characterized using the atoms in molecules theory (AIM), and by the analysis of the vibrational frequencies. The minima on the BSSE-counterpoise corrected potential-energy surface (PES) have been determined as described by S. Simón, M. Duran, and J. J. Dannenberg, and the results were compared with the uncorrected PES