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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 role of uncertainty has become increasingly important in economic forecasting, due to both theoretical and empirical reasons. Although the traditional practice consisted of reporting point predictions without specifying the attached probabilities, uncertainty about the prospects deserves increasing attention, and recent literature has tried to quantify the level of uncertainty perceived by different economic agents, also examining its effects and determinants. In this context, the present paper aims to analyze the uncertainty in economic forecasting, paying attention to qualitative perceptions from confidence and industrial trend surveys and making use of the related ex-ante probabilities. With this objective, two entropy-based measures (Shannon&rsquo, s and quadratic entropy) are computed, providing significant evidence about the perceived level of uncertainty. Our empirical findings show that survey&rsquo, s respondents are able to distinguish between current and prospective uncertainty and between general and personal uncertainty. Furthermore, we find that uncertainty negatively affects economic growth.

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.

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.

Our research was initiated in an attempt to analyse the digital gap between nations. With this aim, we approached the measurement of digital disparities between countries by means of multivariate statistical methods. In particular we used factor and cluster analysis to obtain a classification of the levels of digital development. This framework was applied to the European Union (EU) before its last increase in number of nations. The analysis led to the identification of two factors and four groups of countries in the EU, showing asymmetry in the development of the information society.