Exploring the inter-industry wage premia in Portugal along the wage distribution: evidence from EU-SILC data

In this article we investigate whether inequality in the inter-industry wage premia may be explained by unobserved differences in workers' educational skills. We use the last 2007 wave of EU-SILC data set for Portugal, a nation which can be considered a case-study, due to its traditional high inter-industry wage dispersion. Applying both OLS and Quantile Regression techniques, our results suggest that quality differences across workers still remain an irrelevant matter in the wage premia determination, even after many noteworthy educational reforms adopted in that country since the beginning of the 1990s.Returns to education, inter-industry wage inequality, quantile regression, Portugal

Wage inequality and returns to schooling in Europe: a semi-parametric approach using EU-SILC data

In this paper we apply a semi-parametric approach (quantile regression - QR) to the last 2007 wave of the EU-SILC data set, in order to explore the connection between education and wage inequality in 8 European countries. We find that wages increase with education and this holds true across the whole distribution. Furthermore, this effect is generally more important at the highest quantiles of the distribution than at the lowest, implying that schooling increases wage dispersion. This evidence is found to be rather robust as showed through tests of linear hypothesis. We also corroborate the idea that, although OLS coefficients estimates are substantially in line with the QR’s, the former technique really misleads relevant information about cross-countries heterogeneity in the impact of education on within group inequality at different points of the wage distribution. Hence this paper confirms that a semi-parametric QR approach is more interesting, as well as more appropriate, because it measures the wage effect of education at different quantiles, thus describing relevant cross-countries changes or bounces not only in the location, but also in the shape of the distribution.Returns to education; Wage inequality; Quantile regression; Europe

Inequality in workers’ lifelong learning across european countries: Evidence from EU-SILC data-set

The primary purpose of this paper is to explore the potential for EU-SILC data to deepen our understanding of the determinants of inequality in workers’ formal life-long learning (LLL) in Europe. In particular we investigate the incidence of personal, job-specific and firm-specific characteristics on the workers’ probability to undertake adult learning. To do so, we first estimate LLL incidence in the whole sample for men and women. Then we estimate separate 21 country-specific equations, for both sexes. This method allows to investigate cross-country gender differences and avoid unobserved heteroscedasticity due to sex, which we clearly find in the data. For the whole sample the results show that, for both men and women, formal LLL incidence is significantly higher among young, better educated, part-time and temporary workers, and lower among those who changed current job in the last year, employed in small firms and having low-skilled occupations. Furthermore, some gender differences for the whole sample emerge. When estimating separate equations for each country and for both sexes, a significant cross-country heterogeneity and a weaker significance of the coefficients come to light. In particular, a couple of relevant results emerge for Scandinavian countries with regard to the complementarity between past level of education and current adult learning. Finland is the only country in the sample in which, for both men and women, less educated workers are more likely to undertake formal LLL, thus making adult learning system able to avoid, for both men and women, existing inequality in human capital, as it results from education levels. Denmark is the only country where, for women, being less educated turns out to be the predictor with the greatest significant magnitude of the effect in the variation of the probability.education, training, lifelong learning, human capital, inequality, Europe

Inter-industry Wage Premia in Portugal: Evidence from EU-SILC data

In this paper we investigate whether inequality in the inter-industry wage premia may be explained by unobserved differences in workers’ educational skills. We use the 2007 EU-SILC data set for Portugal, a nation which can be considered a case-study, due to its high inter-industry wage dispersion. Applying both OLS and quantile regression techniques, our results suggest that this unobserved heterogeneity is not a relevant matter in the wage premia determination. We thus corroborate the previous empirical contribution to Economic Letters performed by Martins (2004).Returns to education; inter-industry wage inequality; Quantile regression; Portugal

Education and wage inequality in Europe

In this paper we apply a quantile regression (QR) approach to the EU-SILC data set, in order to explore the connection between education and wage inequality in eight European countries. Our results corroborate the positive relation between wage increase and education and it holds true across the whole distribution. This effect is generally stronger at the highest quantiles of the distribution than at the lowest, implying that schooling increases wage dispersion. This evidence is found to be rather robust like the applied tests of linear hypothesis show.Returns to education, Wage inequality, Quantile regression, Europe.

Constraint of Void Bias on Primordial non-Gaussianity

We study the large-scale bias parameter of cosmic voids with primordial non-Gaussian (PNG) initial conditions of the local type. In this scenario, the dark matter halo bias exhibits a characteristic scale dependence on large scales, which has been recognized as one of the most promising probes of the local PNG. Using a suite of $N$-body simulations with Gaussian and non-Gaussian initial conditions, we find that the void bias features scale-dependent corrections on large scales, similar to its halo counterpart. We find excellent agreement between the numerical measurement of the PNG void bias and the general peak-background split prediction. Contrary to halos, large voids anti-correlate with the dark matter density field, and the large-scale Gaussian void bias ranges from positive to negative values depending on void size and redshift. Thus, the information in the clustering of voids can be complementary to that of the halos. Using the Fisher matrix formalism for multiple tracers, we demonstrate that including the scale-dependent bias information from voids, constraints on the PNG parameter $f_{\rm NL}$ can be tightened by a factor of two compared to the accessible information from halos alone, when the sampling density of tracers reaches $4 \times 10^{-3} \, h^3 \mathrm{Mpc}^{-3}$.Comment: 7 pages, 4 figures; dn/dlnsigma_8 prediction implemented and excellent agreement with simulation results obtained. Matched to published versio

Possible Signatures of Inflationary Particle Content: Spin-2 Fields

We study the imprints of a massive spin-2 field on inflationary observables, and in particular on the breaking of consistency relations. In this setup, the minimal inflationary field content interacts with the massive spin-2 field through dRGT interactions, thus guaranteeing the absence of Boulware-Deser ghostly degrees of freedom. The unitarity requirement on spinning particles, known as Higuchi bound, plays a crucial role for the size of the observable signal.Comment: 24 pages, 6 figure

Molecular Pathways in Prolactinomas: Translational and Therapeutic Implications

Dopamine; Lactotroph tumour; ProlactinomaDopamina; Tumor lactòtrof; ProlactinomaDopamina; Tumor lactotrofo; ProlactinomaProlactinoma has the highest incidence rate among patients with functional pituitary tumours. Although mostly benign, there is a subgroup that can be aggressive. Some clinical, radiological and pathology features have been associated with a poor prognostic. Therefore, it can be considered as a group of heterogeneous tumours. The aim of this paper is to give an overview of the molecular pathways involved in the behaviour of prolactinoma in order to improve our approach and gain deeper insight into the better understanding of tumour development and its management. This is essential for identifying patients harbouring aggressive prolactinoma and to establish personalised therapeutics options.This research received no external funding