Commodity Dynamics: A Sparse Multi-class Approach

The correct understanding of commodity price dynamics can bring relevant improvements in terms of policy formulation both for developing and developed countries. Agricultural, metal and energy commodity prices might depend on each other: although we expect few important effects among the total number of possible ones, some price effects among different commodities might still be substantial. Moreover, the increasing integration of the world economy suggests that these effects should be comparable for different markets. This paper introduces a sparse estimator of the Multi-class Vector AutoRegressive model to detect common price effects between a large number of commodities, for different markets or investment portfolios. In a first application, we consider agricultural, metal and energy commodities for three different markets. We show a large prevalence of effects involving metal commodities in the Chinese and Indian markets, and the existence of asymmetric price effects. In a second application, we analyze commodity prices for five different investment portfolios, and highlight the existence of important effects from energy to agricultural commodities. The relevance of biofuels is hereby confirmed. Overall, we find stronger similarities in commodity price effects among portfolios than among markets

ELECTRO-TUNABLE OPTICAL DEVICES FOR MOLECULAR AND CELLULAR STUDIES

In the present scenario of information technology, researchers are looking for new systems able to deal more efficiently with the increasing amount of information produced by modern society. Nowadays, these tasks are accomplished by CMOS transistors and FLASH memories. Despite their wide implementation, these devices are facing serious issues along their road of development, mainly related to stable operation and power dissipation managing. Advancements in this field could boost the application of artificial intelligence and Big Data analysis, as well as enable new data communication protocols. By taking inspiration from the brain, a very powerful system characterized by low power consumption and high interconnectivity, new proposed devices, such as RRAM memories, aim at overcoming these issues. Properly engineered systems of this typology could act moreover as platforms for more precise and comprehensive biomedical studies. In this thesis, a new class of electro-tunable optical devices is presented in the framework of next-generation memory systems. The model device possesses very favorable characteristics, such as high density and interconnectivity. Moreover, the optical readout, performed by a camera, enables parallel operation. Two realizations of this device concept were studied. The first one is a new configuration for Zero-Mode Waveguides (ZMWs), a well-known nanophotonic system used to perform studies on fluorophore dispersion at the single molecule level. In the proposed device, the interplay of an electric voltage allows to control fluorophore concentration and residence time inside the ZMWs. The light intensity coming from the ZMWs gives information about these two parameters. In the second realization, the developed ZMWs platform is used to perform an optical detection of cardiomyocytes action potentials (APs). The cells are cultured on a thin substrate placed above the fluorophore dispersion. The substrate features an array of pass-through electrodes, which allow the electric APs to be transferred from the cells to the fluorophore dispersion. APs were successfully measured with high SNR. Moreover, the device proved able to detect the effects of a drug administered to the cell culture. This device could find application as a new system for in-vitro electrophysiology, including drugs cardiotoxicity studies. Due to the optical readout scheme, it promises to offer very high spatial resolution, orders of magnitude higher than conventional multi-electrode arrays systems

Forecasting Loan Default in Europe with Machine Learning

We use a dataset of 12 million residential mortgages to investigate the loan default behavior in several European countries. We model the default occurrence as a function of borrower characteristics, loan-specific variables, and local economic conditions. We compare the performance of a set of machine learning algorithms relative to the logistic regression, finding that they perform significantly better in providing predictions. The most important variables in explaining loan default are the interest rate and the local economic characteristics. The existence of relevant geographical heterogeneity in the variable importance points at the need for regionally tailored risk-assessment policies in Europe

Detecting Anti-dumping Circumvention: A Network Approach

Despite the increasing integration of the global economic system, anti-dumping measures are a common tool used by governments to protect their national economy. In this paper, we propose a methodology to detect cases of anti-dumping circumvention through re-routing trade via a third country. Based on the observed full network of trade flows, we propose a measure to proxy the evasion of an anti-dumping duty for a subset of trade flows directed to the European Union, and look for possible cases of circumvention of an active anti-dumping duty. Using panel regression, we are able correctly classify 86% of the trade flows, on which an investigation of anti-dumping circumvention has been opened by the European authorities

Forecasting GDP in Europe with Textual Data

We evaluate the informational content of news-based sentiment indicators for forecasting Gross Domestic Product (GDP) and other macroeconomic variables of the five major European economies. Our data set includes over 27 million articles for 26 major newspapers in 5 different languages. The evidence indicates that these sentiment indicators are significant predictors to forecast macroeconomic variables and their predictive content is robust to controlling for other indicators available to forecasters in real-time.Comment: 34 pages, 6 figures, published in Journal of Applied Econometrics (Early view

Electrical behavior of exploding copper wire in ambient air

This work experimentally investigates the electrical behavior of an exploding wire when the initial energy of the system varies from 28 to 709 J. This experiment uses 50-um-diameter, 33-mm-long copper wires. The wire is surrounded by air at normal atmospheric pressure and temperature. The experiment monitored the current derivative, voltage between wire ends, total visible radiation emitted, and the shadow image of the wire to study how the electrical parameters vary as a function of initial energy. The results indicate a change in the initial discharge mechanism.Fil: Barbaglia, Mario Oscar. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Física Arroyo Seco; ArgentinaFil: Rodriguez Prieto, Gonzalo. Universidad de Castilla-La Mancha; Españ

A model of hard X-rays emission from free expanding Plasma-Focus discharges

A planar-piston model of the hard x-ray production in Plasma-Focus devices is presented. The model applies Von Karman approximations to represent the inner structure of the pinch. The hard x-ray emission is calculated assuming Bremsstrahlung from the collision on the anode base of an electron current running away from the pinch.. The model was applied to analyse the experimental data of a small Plasma Focus without surrounding cathode, finding good agreement.Fil: Fogliatto, Ezequiel Oscar. Comisión Nacional de Energía Atómica. Gerencia del Area de Energía Nuclear. Instituto Balseiro; ArgentinaFil: Gonzalez, Jose Hector. Comisión Nacional de Energía Atómica. Gerencia del Area de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil; ArgentinaFil: Barbaglia, Mario Oscar. Comision Nacional de Energi­a Atomica. Centro Atomico Bariloche; ArgentinaFil: Clausse, Alejandro. Comision Nacional de Energi­a Atomica. Centro Atomico Bariloche; Argentin

The role of environmental sustainability in the relocation choices of MNEs: Back to the home country or welcome in a new host country?

This study investigates how firms' awareness of environmental sustainability affects the revision of their internationalization strategies. Combining Stakeholder and Signalling theories, we argue that firms concerned with environmental sustainability have a higher propensity to return to their home country when confronted with the need to relocate foreign manufacturing subsidiaries, in order to match Corporate Social Responsibility (CSR) stakeholder expectations and enhance the effectiveness of sustainable disclosure endeavours. We also argue that the home country's environmental policy stringency, reflecting a stronger pressure by stakeholders and a higher need for effective signals, positively moderates the relationship between the firm environmental sustainability concern and the likelihood to move back home. The empirical analysis conducted on a sample of 150 relocations performed across European nations in 2002–2016 reveals that MNEs signalling their CSR are more likely to backshore only in case of rigid environmental laws, which are perceived as an opportunity to align with CSR stakeholder expectations and to amplify the benefits of disclosing the shortening of their global value chain