Tax-benefit systems, income distribution and work incentives in the European Union

In this paper we study the impact of tax-benefit systems on income inequality and work incentivesacross the 27 Member States of the European Union (EU). Using EUROMOD, the EU-wide taxbenefitmicrosimulation model, we disentangle the role of taxes, benefits and social insurancecontributions in influencing country specific Gini coefficients and Marginal Effective Tax Rates.The extent to which tax-benefit systems contribute to income redistribution and provide work incentives at the intensive margin is found to vary considerably across the 27 Member States of the EU. Our results further highlight the presence of a trade-off between income redistribution and work incentives across EU-27 countries

Universality of trap models in the ergodic time scale

Consider a sequence of possibly random graphs $G_N=(V_N, E_N)$, $N\ge 1$, whose vertices's have i.i.d. weights $\{W^N_x : x\in V_N\}$ with a distribution belonging to the basin of attraction of an $\alpha$-stable law, $0<\alpha<1$. Let $X^N_t$, $t \ge 0$, be a continuous time simple random walk on $G_N$ which waits a \emph{mean} $W^N_x$ exponential time at each vertex $x$. Under considerably general hypotheses, we prove that in the ergodic time scale this trap model converges in an appropriate topology to a $K$-process. We apply this result to a class of graphs which includes the hypercube, the $d$-dimensional torus, $d\ge 2$, random $d$-regular graphs and the largest component of super-critical Erd\"os-R\'enyi random graphs

ELECTROCHEMICAL CHARACTERIZATION OF NEW 1,5-BENZODIAZEPINE DERIVATIVES

Indexación: Web of Science; Scielo.Cyclic voltammetry was used to study the electrochemical behavior of new 1,5-benzodiazepine derivatives on a glassy carbon electrode. Well-defined oxidation peaks were observed in DMSO. The Electrochemical response of the glassy carbon electrode was evaluated as function of the scan rate, showing that the electron transfer process for compound (5) and (6) resulted to be controlled by diffusion.http://ref.scielo.org/3nfd9

Scaling limits of a tagged particle in the exclusion process with variable diffusion coefficient

We prove a law of large numbers and a central limit theorem for a tagged particle in a symmetric simple exclusion process in the one-dimensional lattice with variable diffusion coefficient. The scaling limits are obtained from a similar result for the current through -1/2 for a zero-range process with bond disorder. For the CLT, we prove convergence to a fractional Brownian motion of Hurst exponent 1/4.Comment: 9 page

How Skillful are the Multiannual Forecasts of Atlantic Hurricane Activity?

The recent emergence of near-term climate prediction, wherein climate models are initialized with the contemporaneous state of the Earth system and integrated up to 10 years into the future, has prompted the development of three different multiannual forecasting techniques of North Atlantic hurricane frequency. Descriptions of these three different approaches, as well as their respective skill, are available in the peer-reviewed literature, but because these various studies are sufficiently different in their details (e.g., period covered, metric used to compute the skill, measure of hurricane activity), it is nearly impossible to compare them. Using the latest decadal reforecasts currently available, we present a direct comparison of these three multiannual forecasting techniques with a combination of simple statistical models, with the hope of offering a perspective on the current state-of-the-art research in this field and the skill level currently reached by these forecasts. Using both deterministic and probabilistic approaches, we show that these forecast systems have a significant level of skill and can improve on simple alternatives, such as climatological and persistence forecasts.The first author would like to thank Isadora Jimenez for providing the necessary material for Fig. 2. The first author would like to acknowledge the financial support from the Ministerio de Economía, Industria y Competitividad (MINECO; Project CGL2014- 55764-R), the Risk Prediction Initiative at BIOS (Grant RPI2.0-2013-CARON), and the EU [Seventh Framework Programme (FP7); Grant Agreement GA603521]. We additionally acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. LPC's contract is cofinanced by the MINECO under the Juan de la Cierva Incorporacion postdoctoral fellowship number IJCI-2015-23367. Finally, we thank the National Hurricane Center for making the HURDAT2 data available. All climate model data are available at https://esgf-index1.ceda.ac.uk/projects/esgf-ceda/.Peer ReviewedPostprint (published version