Spatial Localization in Manufacturing: A Cross-Country Analysis

This paper employs a homogenous firms database to investigate industry localization in European countries. More specifically, we compare, across industries and countries, the predictions of two of the most popular localization indices, i.e., the Ellison and Glaeser (1997) index and the Duranton and Overman (2005) index. We find that, independently from the index used, localization is a pervasive phenomenon in all countries studied, but the degree of localization is very uneven across industries in each country. Furthermore, we find that the two indices significantly diverge in predicting the intensity of the forces generating localization within each industry. Finally, we perform a cross-sectoral analysis of localized industries. We show that, in all countries, localized sectors are mainly ``traditional'' sectors (like jewelery, wine, and textiles) and sectors where scale economies are important. However, once one controls for countries' industrial structures science-based sectors turn out to be the most localized ones.Industry Localization; Manufacturing Industries; Localization Indices; Spatial Concentration; Spatial correlation; Cross-country studies

Spatial Localization in Manufacturing: A Cross-Country Analysis

This paper employs a homogenous firms' database to investigate industry localiza- tion in European countries. More specifically, we compare, across industries and countries, the predictions of two of the most popular localization indices, i.e., the Ellison and Glaeser index (Ellison and Glaeser, 1997) and the Duranton and Over- man index (Duranton and Overman, 2005). We find that, independently from the index used, localization is a pervasive phenomenon in all countries studied, but the degree of localization is very uneven across industries in each country. Furthermore, we find that the two indices significantly diverge in predicting the intensity of the forces generating localization within each industry. Finally, we perform a cross- sectoral analysis of localized industries. We show that, in all countries, localized sectors are mainly "traditional" sectors (like jewelery, wine, and textiles) and sec- tors where scale economies are important. However, once one controls for countries' industrial structures science-based sectors turn out to be the most localized ones.Industry Localization, Manufacturing Industries, Localization Indices, Spatial Concentration, Spatial correlation, Cross-country studies

Testing the "weak form efficient market" hypothesis: an analysis on european and italian equity markets

The purpose of the thesis is testing the EMH in the weak form on Ftse Mib and Stoxx Europe 600 indexes using econometric and statistical tools. a comparison among the methodologies and a critical analysis of the results lead to empirical evidence that both indexes are weak efficent in the examined time frame ( jan. 1999 to feb. 2016)ope

The relation between mass and concentration in X-ray galaxy clusters at high redshift

Galaxy clusters are the most recent, gravitationally-bound products of the hierarchical mass accretion over cosmological scales. How the mass is concentrated is predicted to correlate with the total mass in the cluster's halo, with systems at higher mass being less concentrated at given redshift and for any given mass, systems with lower concentration are found at higher redshifts. Through a spatial and spectral X-ray analysis, we reconstruct the total mass profile of 47 galaxy clusters observed with Chandra in the redshift range $0.4<z<1.2$, selected to have no major mergers, to investigate the relation between the mass and the dark matter concentration, and the evolution of this relation with redshift. The sample in exam is the largest one investigated so far at $z>0.4$, and is well suited to provide the first constraint on the concentration--mass relation at $z>0.7$ from X-ray analysis. Under the assumptions that the distribution of the X-ray emitting gas is spherically symmetric and in hydrostatic equilibrium, we combine the deprojected gas density and spectral temperature profiles through the hydrostatic equilibrium equation to recover the parameters that describe a NFW total mass distribution. The comparison with results from weak lensing analysis reveals a very good agreement both for masses and concentrations. Uncertainties are however too large to make any robust conclusion on the hydrostatic bias of these systems. The relation is well described by the form $c \propto M^B (1+z)^C$, with $B=-0.50 \pm 0.20$, $C=0.12 \pm 0.61$ (at 68.3\% confidence), it is slightly steeper than the one predicted by numerical simulations ($B\sim-0.1$) and does not show any evident redshift evolution. We obtain the first constraints on the properties of the concentration--mass relation at $z > 0.7$ from X-ray data, showing a reasonable good agreement with recent numerical predictions.Comment: A&A accepted, 18 pages, 13 figures, 1 Appendi

A software architecture for the analysis of large sets of data streams in cloud infrastructures

System management algorithms in private andpublic cloud infrastructures have to work with literally thousands of data streams generated from resource, applicationand event monitors. This cloud context opens two novel issuesthat we address in this paper: how to design a softwarearchitecture that is able to gather and analyze all informationwithin real-time constraints; how it is possible to reduce theanalysis of the huge collected data set to the investigationof a reduced set of relevant information. The application ofthe proposed architecture is based on the most advancedsoftware components, and is oriented to the classification of thestatistical behavior of servers and to the analysis of significantstate changes. These results guide model-driven managementsystems to investigate only relevant servers and to applysuitable decision models considering the deter

A new tool for the evaluation of the rehabilitation outcomes in older persons. a machine learning model to predict functional status 1 year ahead

Purpose To date, the assessment of disability in older people is obtained utilizing a Comprehensive Geriatric Assessment (CGA). However, it is often difficult to understand which areas of CGA are most predictive of the disability. The aim of this study is to evaluate the possibility to early predict—1year ahead—the disability level of a patient using machine leaning models. Methods Community-dwelling older people were enrolled in this study. CGA was made at baseline and at 1year follow-up. After collecting input/independent variables (i.e., age, gender, schooling followed, body mass index, information on smoking, polypharmacy, functional status, cognitive performance, depression, nutritional status), we performed two distinct Support Vector Machine models (SVMs) able to predict functional status 1year ahead. To validate the choice of the model, the results achieved with the SVMs were compared with the output produced by simple linear regression models. Results 218 patients (mean age = 78.01; SD = 7.85; male = 39%) were recruited. The combination of the two SVMs is able to achieve a higher prediction accuracy (exceeding 80% instances correctly classified vs 67% instances correctly classified by the combination of the two linear regression models). Furthermore, SVMs are able to classify both the three categories, self sufficiently, disability risk and disability, while linear regression model separates the population only in two groups (self-sufficiency and disability) without identifying the intermediate category (disability risk) which turns out to be the most critical one. Conclusions The development of such a model can contribute to the early detection of patients at risk of self-sufficiency loss

Green compressive sampling reconstruction in IoT networks

In this paper, we address the problem of green Compressed Sensing (CS) reconstruction within Internet of Things (IoT) networks, both in terms of computing architecture and reconstruction algorithms. The approach is novel since, unlike most of the literature dealing with energy efficient gathering of the CS measurements, we focus on the energy efficiency of the signal reconstruction stage given the CS measurements. As a first novel contribution, we present an analysis of the energy consumption within the IoT network under two computing architectures. In the first one, reconstruction takes place within the IoT network and the reconstructed data are encoded and transmitted out of the IoT network; in the second one, all the CS measurements are forwarded to off-network devices for reconstruction and storage, i.e., reconstruction is off-loaded. Our analysis shows that the two architectures significantly differ in terms of consumed energy, and it outlines a theoretically motivated criterion to select a green CS reconstruction computing architecture. Specifically, we present a suitable decision function to determine which architecture outperforms the other in terms of energy efficiency. The presented decision function depends on a few IoT network features, such as the network size, the sink connectivity, and other systems’ parameters. As a second novel contribution, we show how to overcome classical performance comparison of different CS reconstruction algorithms usually carried out w.r.t. the achieved accuracy. Specifically, we consider the consumed energy and analyze the energy vs. accuracy trade-off. The herein presented approach, jointly considering signal processing and IoT network issues, is a relevant contribution for designing green compressive sampling architectures in IoT networks

L’effetto della liberalizzazione ferroviaria sulle politiche di prezzo delle compagnie aeree e ferroviarie. Evidenze preliminari sui principali collegamenti ad Alta Velocità in Italia

Il mercato italiano del trasporto ferroviario passeggeri è stato recentemente caratterizzato dall'ingresso di un nuovo operatore nel settore dell'Alta Velocità, Nuovo Trasporto Viaggiatori (NTV). L'ingresso di NTV ha stimolato sia la concorrenza intramodale con l’incumbent Trenitalia sia la concorrenza intermodale con le compagnie aeree. Il presente lavoro si propone di studiare le strategie di pricing nel mercato del trasporto passeggeri, con il duplice l'obiettivo di esplorare l'effetto della concorrenza intramodale sulle tariffe degli operatori ferroviari - applicate sulle principali rotte Italiane servite dall’Alta Velocità (AV) - e di analizzare l'effetto della concorrenza intermodale sulle strategie di prezzo delle compagnie aeree. I risultati dell'analisi evidenziano che le due compagnie ferroviarie che operano nel segmento AV pongono in essere una politica di prezzo strategica, sebbene eterogenea fra le rotte. Inoltre, le compagnie aeree riducono in misura consistente le tariffe quando operano in concorrenza diretta con i servizi ad AV

The impact of open access on intra- and inter-modal rail competition. A national level analysis in Italy

During 2012 the Italian passenger market has experienced the entry of a new operator, Nuovo Trasporto Viaggiatori (NTV) on the high speed rail (HSR) market segment, in competition with the incumbent Trenitalia. The Italian market is the first and most extensive case in Europe where two railway companies compete for HSR services on open access basis. In this paper we empirically explore the competitive effects of the newcomer’s entry in the passenger market tackling two issues. First, we study price and capacity effects of the stemming intra-modal competition. Second, we measure the impact of inter-modal competition by HSR on airline pricing behaviour. The results show that the two railway companies engage in strategic pricing, although to a different degree on different routes and that capacity and frequency are strategic variables. We also find that airlines significantly reduce fares when flights are in direct competition with HSR services