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The aim of this article is to analyze inequality and inequality of opportunity (IOp) for the Spanish regions Autnomous Communities (CCAA), paying main attention to the situation of foreign immigrants. For this purpose, we use the European Social Survey of Income and Living Conditions database and some variables regarding individuals’ perceptions about immigration from the European Social Survey. We find that both income inequality and IOp increase between 2004 and 2010 for the great majority of the Spanish regions. Moreover, we observe convergence between regions in terms of IOp, while there is not convergence in terms of income inequality. In addition, the contribution of the different variables used as circumstances to estimate IOp varies greatly. The contribution to IOp of being an immigrant experienced a considerable and worrying increase, whereas the importance of family background characteristics is reduced to a great extent. Likewise, the analysis in deep of the situation of immigrants provides some interesting evidence. Firstly, we show that immigrant population experienced a downturn in their situation in terms of income; secondly, we find that, according to individuals’ perceptions about immigration, as the share of immigrants rises, there is an improvement in their impact in cultural life.

The aim of this paper is to shed some light on the behaviour of Inequality of Opportunity (IOp henceforth) in developing countries. The analysis is carried out using microdata collected by national surveys and harmonised by the Luxembourg Income Study (LIS). The LIS database incorporates a wide variety of personal harmonised variables, which allow us to made cross-country comparisons for developing countries. More specifically, we analyse six countries: Brazil, Egypt, Guatemala, India, Peru and South Africa and the periods of time covered vary from 2004 to 2014. In order to analyse the impact of inequality of opportunity we compute relative indicators by comparing IOp with economic inequality for each country analysed. Moreover, to check the robustness of our results we include two sensitivity analyses: first, we test the significance of overtime changes using inferential procedures and second, we assess if different economic indicators lead to different conclusions both in the evolution of IOp and overall inequality and in the relative weights of the circumstances that conform IOp. More specifically, regarding the first aim we focus on the disposable equivalised income to measure IOp and Income Inequality and we test if overtime changes are statistically significant using bootstrapping procedures. With regard to the second objective, to test the robustness of the results we compute IOp and Inequality for four different economic aggregates: Personal Income, Labour Personal Income, Consumption and Monetary Consumption. The empirical results of these analyses lead to two interesting conclusions: most of the overtime changes are found to be statistically significant and the use of a specific economic indicator is not as important as it at first seems, leading in most cases to the same conclusions.

The aim of this article is to shed some light on the behaviour of income inequality and inequality of opportunity over time for 26 European countries. The analysis is carried out using microdata collected by the European Union Statistics on Income and Living Conditions (EU-SILC), which incorporate a wide variety of personal harmonised variables, allowing comparability between countries. The availability of this database for the years 2004 and 2010 is particularly relevant to assess changes over time in the main inequality indices and the contribution of “circumstance” to inequality of opportunity. Bootstrap methodology is used with the aim of testing if the differences between the two years are statistically significant. Results show that observed changes in inequality of opportunity and income inequality are in most cases significant and also prove the robustness of the bootstrap methods to analyse the evolution of income inequality and inequality of opportunity.

The aim of this paper is to contribute both theoretically and empirically to the analysis of Inequality of Opportunity over time, providing some significant findings referred to the Spanish case. The analysis is carried out using microdata collected by the European Union Statistics on Income and Living Conditions (EU-SILC), which incorporate a wide variety of personal harmonised variables, allowing comparability with other countries. The availability of this database for the period 2004 and 2010 is particularly relevant for assessing changes over time in the main inequality indices and the contribution of circumstances to inequality of opportunity. We find that the effect of circumstances on income distribution has significantly intensified between the two years. To test the significance of the differences between years we perform bootstrap estimations.

The aim of this chapter is to shed some light on the behavior of Income Inequality and Inequality of Opportunity over time for 26 European countries. The analysis is carried out using microdata collected by the European Union Statistics on Income and Living Conditions (EU-SILC), which incorporates a wide variety of personal harmonized variables, allowing comparability between countries. The availability of this database for years 2004 and 2010 is particularly relevant to assess changes over time in the main inequality indices and the contribution of circumstances to inequality of opportunity. Furthermore, a bootstrap estimation is performed with the aim of testing whether the differences between both years are statistically significant.

Environmental sustainability was established by the United Nations as a Millennium Development Goal (MDG7), including a wide variety of targets referred to the access to safe drinking water, the reduction of biodiversity loss, the improvement of lives of slum dwellers and the integration of principles of sustainable development into the country policies. Despite some progress towards meeting this goal, new challenges have appeared, endangering the development and environmental achievements. Therefore, United Nations and the international community are working on the Sustainable Development Goals (SDG) as a new framework placing environmental sustainability at its core. In this context, the analysis of environmental forecasts plays a main role. More specifically, taking into account that the carbon dioxide emissions have increased by almost 50 per cent since year 1990, special attention must be paid to the evolution and projections of emissions for different countries. In this paper we focus on environmental forecasting, based on the extended Environmental Kuznets Curve (EKC) and the Environmental Logistic Curve (ELC). Considering a sample of 175 countries we perform a competition between both methods, analysing their goodness of fit and their forecasting accuracy. The empirical results provide significant evidence about the adequacy of EKC and ELC for explaining CO2 emissions in different countries, also allowing us to obtain some ex-ante projections.

As more and more daily activities take place online, data on internet behaviour is becoming a key information source. In this sense, several papers have explored the usefulness of internet search data in order to improve the nowcasting and forecasting of economic indicators. Special attention has been paid to predicting unemployment. Nonetheless, most of the empirical evidence on this field has focused in countries with low/moderate rates of unemployment. This paper follows this line of research and explores the use of Google Trends data in order to improve the forecasting of the figures of unemployment in Spain. This country reveals as a very interesting case due to the sharp increases in unemployment caused by the economic crisis. With the aim of providing an extensive approach on the Spanish unemployment, we use ARIMA models, also introducing as explanatory variables the Google searches for “job offers” and a business confidence indicator referred to employment perspectives. In this way we combine the time series perspective with qualitative indicators from the supply and the demand sides, leading to a more comprehensive description and also improving forecasting performance.

The environmental costs of economic development have received increasing attention during the last years. According to the World Energy Outlook (2013) sustainable energy policies should be promoted in order to spur economic growth and environmental protection in a global context, particularly in terms of reducing greenhouse gas emissions that contribute to climate change. Within this framework, the European Union aims to achieve the "20-20-20" targets, including a 20% reduction in EU greenhouse gas emissions from 1990 levels, a raise in the share of EU energy consumption produced from renewable resources to 20% and a 20% improvement in the EU's energy efficiency. Furthermore, the EU "Energy Roadmap 2050" has been recently adopted as a basis for developing a long-term European energy framework, fighting against climate change through the implementation of energy efficiency measures and the reduction of emissions. This paper focuses on the European context and attempts to explain the impact of economic growth on CO2 emissions through the estimation of an Environmental Kuznets Curve (EKC) using panel data. Moreover, since energy seems to be at the heart of the environmental problem it should also form the core of the solution, and therefore we provide some extensions of the EKC by including renewable energy sources as explanatory variables in the proposed models. Our data sets are referred to the 27 countries of the European Union during the period 1996-2010. With this information, our empirical results provide some interesting evidence about the significant impacts of renewable energies on CO2 emissions, suggesting the existence of an extended EKC.

espanolLa obtencion de predicciones para series temporales economicas y financieras es una tarea de gran dificultad. En un contexto de disponibilidad creciente de predicciones y debate sobre las alternativas metodologicas para su obtencion, resulta recomendable dedicar nuevos esfuerzos a las medidas utilizadas para su evaluacion. Este trabajo analiza dos indicadores de precision basados en medidas de informacion: el indice U de Theil y la Medida de Informacion Cuadratica de Precision (QIAM), cuya aplicacion a la M-Competicion de Makridakis and Hibon (2000) permite reexaminar los resultados empiricos obtenidos por estos autores para el conjunto de la base de datos y mas concretamente para las series macroeconomicas y financieras. El calculo de las medidas propuestas proporciona un nuevo ranking de tecnicas predictivas, que muestra coincidencias y diferencias con las conclusiones obtenidas por Makridakis & Hibon a partir de cinco medidas de precision basadas en errores. Los resultados obtenidos permiten tambien un analisis de complejidad versus precision. EnglishEconomic and financial time series are widely considered as one of the most challenging applications of modeling and forecasting. The increasing in forecasting availability and the controversial debate about the advantages of alternative forecasting procedures suggest the need of further research on the forecasting evaluation metrics. In this context, this paper focuses on two information-based accuracy measures: Theil´s U Index and the Quadratic Information Accuracy Measure (QIAM), and aims to re-examine the empirical results of the M3-Competition by Makridakis and Hibon (2000), and specifically those referred to the subset of macroeconomic and financial series. The computation of the proposed accuracy indicators leads to new rankings of forecasting techniques, showing some similarities and disagreements with the main conclusions by Makridakis & Hibon (2000), found on five error based accuracy measures. The obtained results also allow a complexity–accuracy analysis

La predicción económica es una actividad tan apasionante como controvertida. A pesar del consenso generalizado sobre su necesidad, existe un amplio debate sobre la idoneidad de las técnicas y métodos para elaborar predicciones, las medidas para evaluar su precisión e incluso el papel que los organismos de prospectiva deben desempeñar en un entorno socioeconómico cambiante e incierto.Todos estos temas han sido abordados en el presente número monográfico “Predicción económica: métodos y herramientas”, elaborado como homenaje al profesor Antonio Pulido San Román y que pretende reconocer su indudable contribución al desarrollo de la predicción económica en nuestro país.

The relationship between income inequality and economic growth has been widely studied, lea- ding to a controversial debate. Regarding the effect of economic growth on inequality, Kuznets’ inverted-U hypothesis (1955) suggests that inequality first rises with growth and then falls after a turning point. This model has been extended by Anand and Kanbur (1993), and its empirical applications have provided a wide variety of results, depending on the statistical information, the indicators and the estimation techniques. With regard to the effects of inequality on growth, on a theoretical basis the relationship could be of any sign and thus the initial works by Lewis (1954) and Kaldor (1956) defend the existence of positive effects while Alesina & Rodrick (1994), Persson & Tabellini (1994), and Deininger & Squire (1998) assume a negative relationship.The diversity of theoretical assumptions and empirical evidence has stimulated the debate without achieving a consensus about the existence of vicious or virtuous circles. In this context the present paper aims to provide new evidence about the growth-inequality relationship, paying attention to the income level in a double sense. First, we introduce a classification of countries according to their income le- vels, and second we distinguish between inequality relating to low and high incomes.

La utilització de programari lliure i obert (*FOSS) aporta nombrosos avantatges en l'àmbit universitari, que resulten encara més patents en el marc de l'Espai Europeu d'Educació Superior (EEES). Les principals característiques del *FOSS (llibertat d'ús de programes, accés al codi font, estudi i adaptació, distribució de còpies i implementació de millores que beneficien a tota la comunitat) apareixen relacionades amb competències com a creativitat, treball en equip o adaptació a noves situacions. Aquest treball examina el paper del programari lliure en l'àmbit universitari i el seu potencial per a reduir la bretxa digital, presentant també algunes experiències recents.

Resumen La utilizacion de software libre y abierto (Free Open Source Software: FOSS) aporta numerosas ventajas en el ambito universitario, que resultan au n mas patentes en el marco del Espacio Europeo de Educacion Superior (EEES). Las principales caracteristicas del FOSS (libertad de uso de programas, acceso al codigo fuente, estudio y adaptacion, distribucion de copias e implementacion de mejoras que beneficien a toda la comunidad) aparecen relacionadas con competencias como creatividad, trabajo en equipo o adap tacion a nuevas situaciones. Este trabajo examina el papel del software libre en el ambito universitario y su potencial para reducir la brecha digital, presentando tambien algunas experiencias recientes.

In the last few years there has been a tendency towards the study of statistical techniques and economic applications which provide more flexible methods than the traditional ones, such as the study of nonlinear models, the use of fuzzy sets, the development of fractional ARIMA models (ARFIMA) or the proposition of autoregressive conditional heteroskedasticity models (ARCH). This last contribution provides new methods of analyzing economic time series with time-varying volatility and his author R. Engle has been distinguished with the 2003 Nobel Prize in Economic Sciences.