Productivity Polarization and Sectoral Dynamics in European Regions

We show that the distribution dynamics of productivity in European regions displays polarization with a nonlinear growth path. We investigate the factors explaining this behavior focusing in particular on sectoral composition. The beta-convergence analysis reveals that initial shares of Manufacturing and Other Market Services have a nonlinear impact on growth, while spatial effects are not statistically significant. By decomposing the dynamics of aggregate productivity in terms of sectoral dynamics, we show that productivity in Manufacturing, Non Market Services, and Other Market Services does not converge, for the complex interaction of technological spillovers and specialization effects

Productivity Dynamics across European Regions: the Impact of Structural and Cohesion Funds

This paper analyzes the impact of the European Union regional policy of the three programming periods 1975-1988, 1989-1993 and 1994-1999 on the dynamics of productivity of European regions. On average, funding had a positive, but concave, e\ufb00ect on productivity growth. In particular, a share of funds on GVA of 10% GVA is estimated to raise the regional growth rate of about 0.9% per year. However, by separately considering the three programming periods and the composition of the funds according to the objectives de\ufb01ned by the EU, we \ufb01nd that: i) only the funds allocated in the second and third programming periods, when they remarkably increased, had a signi\ufb01cant impact; and ii) only Objective 1 and Cohesion funds played a signi\ufb01cantly positive impact, while funds devoted to Objectives 2, 3, 4 and 5 had a negative or non signi\ufb01cant impact. The results are robust to potential endogeneity of funds and spatial dependence

On the Determinants of Distribution Dynamics

n this paper we propose a novel approach to identify the impact of growth determinants on the distribution dynamics of productivit y. Our approach integrates counterfactual analysis with the estima tion of stochastic kernels. The counterfactuals are constructed from a semi-parametric growth regression, in which the cross-section heterogeneity in the growth determinants is removed. The methodology also allows us to test for potential distributional effects in the residuals. We illustrate the usefulness of the proposed methodology by an application to a cross-section of countries, which highlights the significant impact on inequality and polarization in the world productivity distribution of growth determinants from an augmented Solow model

Counterfactual Distribution Dynamics across European Regions

This paper proposes a methodology which combines elements of parametric regression analysis with the nonparametric distribution dynamics approach in order to analyse the role of some variables in the convergence of productivity across European regions over the period 1980-2002. We find that the initial productivity crucially accounts in the convergence process across European regions. Differently, employment growth seems not to play a role, while the Structural and Cohesion Funds seem to play a positive role, even though such effect seems to be very low and statistically significant only at the low bound of the range of initial productivity. The structural change of regional economies plays a positive role, but such effect is statistically significant only for the least productive regions. The output composition of a region in 1980 affects the convergence process of productivity growth in several ways. In particular, the share of non market services on output acts like a source of convergence from 1980 to 2002 but in the long-run it plays a negligible role. Finally, the share of finance acts like a force of divergence across European regions, especially for the least productive regions

On the Determinants of Distribution Dynamics

n this paper we propose a novel approach to identify the impact of growth determinants on the distribution dynamics of productivit y. Our approach integrates counterfactual analysis with the estima tion of stochastic kernels. The counterfactuals are constructed from a semi-parametric growth regression, in which the cross-section heterogeneity in the growth determinants is removed. The methodology also allows us to test for potential distributional effects in the residuals. We illustrate the usefulness of the proposed methodology by an application to a cross-section of countries, which highlights the significant impact on inequality and polarization in the world productivity distribution of growth determinants from an augmented Solow model

Deep and Proximate Determinants of the World Income Distribution

This paper studies the deep and proximate determinants of the evolution of the cross-country distribution of GDP per worker in the period 1960–2008 by a novel method based on an information criterion. We find that countries of our sample follow three distinctive growth regimes identified by two deep determinants, namely life expectancy at birth in 1960 and the share of Catholics in 1965, and that each regime is characterized by non-linearities. Growth regimes appear to be the main cause of the increased inequality and polarization, while technological catch-up, proxied by the initial level of GDP per worker, acts in the opposite direction. Finally, human capital marginally reduces polarization, while investment rates and employment growth have no distributional effect

Assessing clinical and psychological features: who are patients showing a nocebo re-action during the drug challenge test?

The nocebo reaction, namely the undesirable effect of an inert substance (placebo), is a phenomenon rarely investigated in literature. A better knowledge of this reaction may help clinicians in the management of these patients in clinical practice. Patients with drug adverse reactions (ADR) undergoing the drug challenge test are an ideal model for studying the nocebo effect, and the study aims to investigate their clinical and psychological features. One hundred and twenty patients (Mage = 46.59, SD = 15.5; 82% female), of which 90 non responders and 30 with nocebo reactions (25%) were recruited, and completed a battery of psychological measures: State-Trait Anxiety Inventory X1-X2, Beck Depression Inventory II, Symptoms Checklist-90-R, Difficulties in Emotion Regulation Scale, Toronto Alexithymia Scale. Clinical features (individual characteristics and ADR clinical history) were collected by clinicians. The results show that older age (p = 0.002), low level of education (p = 0.039) and a depressive tendency (p = 0.030) appear to be potential risk factors for nocebo effects. Although none of the features related to the previous clinical history appear to represent a risk factor for the nocebo reactions (p minor 0.05), significant correlations between some of the clinical and psychological characteristics considered (p values from 0.005 to 0.042) help to better delineate the profile of these reactive patients. A specific training of the sanitary team about psychological aspects is recommendable