On finite-size Lyapunov exponents in multiscale systems

We study the effect of regime switches on finite size Lyapunov exponents (FSLEs) in determining the error growth rates and predictability of multiscale systems. We consider a dynamical system involving slow and fast regimes and switches between them. The surprising result is that due to the presence of regimes the error growth rate can be a non-monotonic function of initial error amplitude. In particular, troughs in the large scales of FSLE spectra is shown to be a signature of slow regimes, whereas fast regimes are shown to cause large peaks in the spectra where error growth rates far exceed those estimated from the maximal Lyapunov exponent. We present analytical results explaining these signatures and corroborate them with numerical simulations. We show further that these peaks disappear in stochastic parametrizations of the fast chaotic processes, and the associated FSLE spectra reveal that large scale predictability properties of the full deterministic model are well approximated whereas small scale features are not properly resolved.Comment: Accepted for publication in Chao

The Europe 2020 Regional Index

We develop a composite index to measure regional progress in meeting objectives set forth by the Europe 2020 strategy. Performance along the thematic areas of the Europe 2020 strategy was computed via an appropriately normalized shortfall measure. The final composite scores were calculated by assigning equal weight to each dimension of the index and taking their arithmetic average. While we should be mindful not to overstate the reach of this analysis, a few general patterns are worth noting. First, we see that southern and central European countries such as Spain, Bulgaria, Greece, Portugal, Poland, Hungary and Romania fall behind Scandinavian and other northern European countries, despite the latters’ more ambitious targets. Second, our analysis makes plain the significant inter-regional heterogeneity of Europe 2020 performance for many countries. The cases of Spain and Italy are particularly suggestive in this regard. We investigated the robustness of index ranks via a rigorous uncertainty and sensitivity analysis. While the ranks of a handful of regions were sensitive to changes in weights and aggregation, index ranks as a whole were quite robustJRC.DDG.01-Econometrics and applied statistic

EU Regional Competitiveness Index RCI 2013

To measure the different dimensions of competitiveness at the regional level, the European Commission has developed the Regional Competitiveness Index – RCI. The RCI was published in 2010 and this is the 2013 edition, which includes most recent data and implements improvements and refinements. RCI 2013 reveals a strong regional dimension of competitiveness, which national level indicators cannot capture, and a polycentric pattern with strong capital and metropolitan regions in many parts of Europe. Some capital regions are surrounded by similarly competitive regions, but in many countries, particularly in the less developed Member States in Central and Eastern Europe, regions neighboring the capital are less competitive.JRC.G.3-Econometrics and applied statistic

Trust, local governance and quality of public service in EU regions and cities

The aim of this report is to present the within-country variability in the EU citizens’ perceptions of the generalised and institutional trust, quality of public service and local governance based on their experiences and opinions expressed in three surveys. By within-country variability we understand differences in citizens’ perceptions between cities or between (1) cities and (2) towns, suburbs and rural areas. We deal with the citizens’ opinions expressed in the surveys we used. The within-country variability in EU citizens’ perceptions of the trust, corruption, local governance and quality of public service and governance are investigated using several composites presenting the differences in citizens’ perceptions from three different perspectives and using three different data sets. First, with the European quality of life survey, we explore the level of (1) general trust, (2) institutional trust and (3) quality of public service in different with respect to degree of urbanisation areas in the EU countries. Second, with the Social Diagnosis survey, we examine the level of general trust and attitude towards free riding in 27 of the largest Polish cities. Finally, using data from the World Justice Project we investigate perceptions of law enforcement, generalised and institutional trust, corruption, bribing and performance of the local government in 58 of the largest EU cities. Our results showed that in general, there are differences in measured phenomena between EU countries, and especially within EU countries in relation to the degree of urbanisation and at city level.JRC.DDG.01-Econometrics and applied statistic

Monitoring multidimensional poverty in the regions of the European Union

In this study, we measure the area-specific poverty in the European Union (EU). To this end, we measure poverty at the sub-national level in two ways: (i) using the EU nomenclature of territorial units (NUTS 1 mostly); (ii) using different with respect to the degree of urbanisation areas within countries. The measurement of poverty is based on the Multidimensional Poverty Index (UN MPI) by Alkire and Santos (2010, 2013). With the data from the European Union Survey on Income and Living Conditions (EU SILC), we formulate the Index of Multidimensional Poverty at the regional level, namely the Multidimensional Poverty Index (MPI-reg). The MPI-reg framework comprises three dimensions — health, education, and standard of living — quantified by three sub-indexes: Multidimensional Poverty in Health Index (MPI–H), Poverty in Education Index (MPI–E) and Multidimensional Poverty in Living Standards Index (MPI–L), respectively. The MPI-reg was computed for 23 EU countries in 2010, 24 EU countries in 2007 and 2011, and 25 countries in 2008 and 2009. Our results show that the level of poverty in the EU ranges from 2–3 % to 15–25 %, with Denmark and Sweden being unequivocally the least poor countries and Latvia, Bulgaria and Romania, the poorest countries. We also indicate that there is a positive relationship between the stratification level and all adjusted headcount ratios, headcount ratios and intensity of poverty scores. This positive relationship implies that there are countries where there is no stratification with respect to poverty (e.g. Sweden, Denmark, the Czech Republic, and Finland) and countries, usually poor ones, such as Romania, Bulgaria and Lithuania, but also Belgium and Italy, where considerable stratification with respect to poverty occurs. In general, in poor and moderately poor countries, the worst situation with respect to poverty is observed in sparsely populated areas, and the best situation occurs in densely populated areas. On the other hand, in the best scoring countries, poverty is relatively higher in the densely populated areas compared to the less well-populated areas. Additionally, our analysis showed that between 2005–07 and 2009–11, changes in inequality with respect to poverty occurred. We demonstrated that a decrease in inequality most often occurred in Poland and Spain, whereas Belgium and Italy we most often spotted as countries with growing regional differences. The results indicated that the European Union regions are strongly diversified with respect to poverty. This implies that regardless of the spatial location of the region and the definition of the region, considerable within-country differences are indicated if only sub-national levels are available. Therefore, relying only on countrywide estimates may be misleading when properly assessing the relative standing of a region with respect to poverty.JRC.DDG.01-Econometrics and applied statistic

The geography of EU discontent and the regional development trap

While in recent times many regions have flourished, many others are stuck—or are at risk of becoming stuck—in a development trap. Such regions experience decline in economic growth, employment, and productivity relative to their neighbors and to their own past trajectories. Prolonged periods in development traps are leading to political dissatisfaction and unrest. Such discontent is often translated into support for antisystem parties at the ballot box. In this article we study the link between the risk, intensity, and duration of regional development traps and the rise of discontent in the European Union (EU)—proxied by the support for Eurosceptic parties in national elections between 2013 and 2022—using an econometric analysis at a regional level. The results highlight the strong connection between being stuck in a development trap, often in middle- or high-income regions, and support for Eurosceptic parties. They also suggest that the longer the period of stagnation, the stronger the support for parties opposed to European integration. This relationship remains robust whether considering only the most extreme Eurosceptic parties or including parties with more moderate levels of Euroscepticism

Mi región, mi Europa, nuestro futuro: séptimo informe sobre la cohesión económica, social y territorial

etadatos de publicación El Séptimo Informe sobre la Cohesión proporciona los datos y la información necesarios para verificar el grado de cohesión (o división) de Europa desde el punto de vista económico, social y territorial; de ese modo, nos permite comprobar con mayor claridad y objetividad lo que se ha conseguido y qué medidas es necesario adoptar en el período financiero posterior a 2020. El informe sienta las bases, por tanto, para diseñar la política de cohesión del futuro

Quality of Life at the sub-national level: an operational example for the EU

This study is the outcome of the European Commission joint project DG JRC / DG REGIO on the measure of quality of life of European regions. European Union cohesion policy supports the economic and social development of regions, especially lagging regions, throughout an integrated approach with the ultimate goal of improving citizens' wellbeing. In this setting, measuring quality of life at the sub-national level is the first step for assessing which regions can assure or have the potential to assure good quality of life and which cannot. The project simultaneously features three innovative points. First the attempt to measure QoL for the European Union regions (NUTS1/NUTS2). Second, the adoption of a type of aggregation, at the lowest level of QoL dimensions, which penalizes inequality across indicators, for mitigating compensability. Third, the inclusion of housing costs in the computation of individual's.JRC.G.3-Econometrics and applied statistic

The Cosmic Crystallinity Conundrum: Clues from IRAS 17495-2534

Since their discovery, cosmic crystalline silicates have presented several challenges to understanding dust formation and evolution. The mid-infrared spectrum of IRAS 17495$-$2534, a highly obscured oxygen-rich asymptotic giant branch (AGB) star, is the only source observed to date which exhibits a clear crystalline silicate absorption feature. This provides an unprecedented opportunity to test competing hypotheses for dust formation. Observed spectral features suggest that both amorphous and crystalline dust is dominated by forsterite (Mg\_2 SiO\_4) rather than enstatite (MgSiO\_3) or other silicate compositions. We confirm that high mass-loss rates should produce more crystalline material, and show why this should be dominated by forsterite. The presence of Mg\_2 SiO\_4 glass suggests that another factor (possibly C/O) is critical in determining astromineralogy. Correlation between crystallinity, mass-loss rate and initial stellar mass suggests that only the most massive AGB stars contribute significant quantities of crystalline material to the interstellar medium, resolving the conundrum of its low crystallinity.Comment: 12 pages, 2 figure

Age, gender, and territory of COVID-19 infections and fatalities

In this note we explore the main demographic differentials in the spread and impact of COVID-19 paying special attention to the combined effect of age and gender, and to the differences at territorial level where population density plays a large role in the diffusion and outcome of the disease in terms of morbidity and mortality. The information is important for designing an exit strategy from COVID-19 and anticipating the rebound for certain segments of the population with differential medical needs, particularly those living in high-density locations.JRC.E.6-Demography, Migration and Governanc