Coronavirus pandemic, remote learning and emerging education inequalities

Recent studies predict that the school closures and distance learning of the 2020 pandemic will lead to lower average education levels, but they may also result into greater and new education inequalities. Using PISA 2018 data from France, Germany, Italy, Spain and the United Kingdom, we find that, even before the pandemic, students lacking the resources needed to learn remotely – ICT resources at home, at school or a quiet place to study – experience strong and significant cognitive gaps with respect to their peers that, in mathematics, range from 70 percent of a school year in the United Kingdom, Germany and France to 25 percent in Spain. Gaps in reading are similar. With school closures and remote learning, these cognitive losses are predicted to increase. We find similar results by considering days of absence from school. In the longer run, students in Spain, Germany and Italy who cannot learn remotely are more likely to repeat grades and end their education early. Overall, cognitive gaps and school dropouts driven by a lack of ICT resources vary with countries’ educational systems and digital divides. Policies should aim to enhance the use of digital resources in education, and must be designed according to countries’ characteristics

Explaining anti-immigrant sentiment through spatial analysis: a study of the 2019 European elections in Italy

Does the settling of foreigners cause a rise in anti-immigrant sentiment due to resource competition? Or does the interaction allow for more respectful relations? And what if one also considers settlement in neighbouring municipalities? Applying an instrumental variable approach to variables collected at the municipality level and also including neighbouring areas, this paper aims to shed light on these questions by considering the vote for the Lega party across Italian municipalities in the 2019 European parliamentary election as a proxy for anti-immigration sentiment. Our results point out a negative effect of direct interactions with foreigners on the Lega vote, while the proximity of immigrants in neighbouring municipalities could have the opposite effect

Adams and Eves: The Gender Gap in Economics Majors

We investigate the gender gap in Economics among bachelor's and master's graduates in Italy between 2010 and 2019. First we establish that being female exerts a negative impact on the choice to major in Economics: at the bachelor level, only 73 women graduate in Economics for every 100 men, with the mathematical content of high school curricula as the key driver of the eect and a persistence of the gap at the master level. Second, within a full menu of major choices, Economics displays the largest gap, followed by STEM and then Business Economics. Third, decomposition analyses expose a unique role for the math background in driving the Economics gender gap relative to other elds. Fourth, a triple difference analysis of a high school reform shows that an increase in the math content of traditionally low math curricula caused an increase in the Economics gender gap among treated students

Adams and Eves: The Gender Gap in Economics Majors

We investigate the gender gap in Economics among bachelor’s and master’s graduates in Italy between 2010 and 2019. First we establish that being female exerts a negative impact on the choice to major in Economics: at the bachelor level, only 73 women graduate in Economics for every 100 men, with the mathematical content of high school curricula as the key driver of the effect and a persistence of the gap at the master level. Second, within a full menu of major choices, Economics displays the largest gap, followed by STEM and then Business Economics. Third, decomposition analyses expose a unique role for the math background in driving the Economics gender gap relative to other fields. Fourth, a triple difference analysis of a high school reform shows that an increase in the math content of traditionally low math curricula caused an increase in the Economics gender gap among treated students

Choose the school, choose the performance. New evidence on the determinants of student performance in eight European countries

This study aims to identify the main determinants of student performance in reading and maths across eight European Union countries (Austria, Croatia, Germany, Hungary, Italy, Portugal, Slovakia, and Slovenia). Based on student-level data from the OECD’s PISA 2018 survey and by means of the application of efficient algorithms, we highlight that the number of books at home and a variable combining the type and location of their school represent the most important predictors of student performance in all of the analysed countries, while other school characteristics are rarely relevant. Econometric results show that students attending vocational schools perform significantly worse than those in general schools, except in Portugal. Considering only general school students, the differences between big and small cities are not statistically significant, while among students in vocational schools, those in a small city tend to perform better than those in a big city. Through the Gelbach decomposition method, which allows measuring the relative importance of observable characteristics in explaining a gap, we show that the differences in test scores between big and small cities depend on school characteristics, while the differences between general and vocational schools are mainly explained by family social statu

Inter-municipal cooperation as a solution for public services delivery? The case of Unioni di Comuni in Emilia-Romagna Region

Inter municipal cooperation (IMC) represents a solution adopted all around the world in order to jointly provide services considering the complexity of contemporary socio-economic contexts. However, empirical evidence on IMC solutions is still week. The purpose of this paper is to analyse associations of municipalities (Unioni di Comuni, UC), the prevalent kind of IMC established in Italy, as a possible solution for sustainable public services delivery. Our research questions refer to the main features of Unioni di Comuni as an IMC for public services delivery in EmiliaRomagna Region (Italy), to the explanation of those characteristics, and to the evaluation of UCs and their features in terms of autonomy, resilience and sustainability. In order to meet our objectives, we accomplished a cluster analysis, considering administrative and socio-economic data; in addition, we examined specific characteristics within each cluster to proceed with a comparison between clusters in terms of revenues from transfers from other governments layers, own revenues, current expenses and financial autonomy index in the last years. Our results suggest a general tendency: to provide services through UC in E-R; and to enhance their development in terms of public service specialization. But at the same time, UCs generally decreased their own financial autonomy, relying on transfers from other public institutions. In line with Resource-Dependence Theory (RDT), our empirical analysis finds different clusters of UCs which act as new centres for public service delivery in Emilia-Romagna Region in order to reduce uncertainty over resources through the creation of new inter-institutional balances. However, the statement that strong UCs compensate weak starting territorial features of municipalities is not self-evident

Robots, Trade and Employment in Italian Local Labour Systems

Three main shocks have affected advanced economies over the last 25 years, with significant consequences for work, production and economic growth. The first is technological change associated with robotics and the so-called Fourth Industrial Revolution. The second, which is partly related to the first, is the diffusion of ICT and the development of intelligent software applied both to industry and tertiary activities. The third is the strong competitive pressure from low cost and emerging countries, which have changed the geography of world production and trade flows, often within global value chains. Following the seminal papers of Acemoglu and Restrepo (2017) and Dauth, Findeisen, Südekum and Woessner (2017), the aim of this paper is to assess the impact of these three shocks on employment in Italian local labour markets in the period 1991-2011. What is new in our approach is the explicit consideration of the role played by the different typologies of local labour systems and industrial districts. We find that robots do not have any negative effect on employment in local labour markets. On the contrary, robots seem to be associated with a growth in overall employment, mainly due to the tertiary sector. The second result is that there is some evidence of a positive effect of ICT investments on local employment, in particular non-manufacturing employment. The last and most robust result of the econometric analysis is the negative impact of trade with low cost countries on local employment. This result has one almost absolute protagonist: China. All these impacts are not homogeneous across the national territory and partly depend on the characteristics of the local productive systems and industrial districts

Fusing NIR and Process Sensors Data for Polymer Production Monitoring

Process analytical technology and multivariate process monitoring are nowadays the most effective approaches to achieve real-time quality monitoring/control in production. However, their use is not yet a common practice, and industries benefit much less than they could from the outcome of the hundreds of sensors that constantly monitor production in industrial plants. The huge amount of sensor data collected are still mostly used to produce univariate control charts, monitoring one compartment at a time, and the product quality variables are generally used to monitor production, despite their low frequency (offline measurements at analytical laboratory), which is not suitable for real-time monitoring. On the contrary, it would be extremely advantageous to benefit from predictive models that, based on online sensors, will be able to return quality parameters in real time. As a matter of fact, the plant setup influences the product quality, and process sensors (flow meters, thermocouples, etc.) implicitly register process variability, correlation trends, drift, etc. When the available spectroscopic sensors, reflecting chemical composition and structure, consent to monitor the intermediate products, coupling process, and spectroscopic sensor and extracting/fusing information by multivariate analysis from this data would enhance the evaluation of the produced material features allowing production quality to be estimated at a very early stage. The present work, at a pilot plant scale, applied multivariate statistical process control (MSPC) charts, obtained by data fusion of process sensor data and near-infrared (NIR) probes, on a continuous styrene-acrylonitrile (SAN) production process. Furthermore, PLS regression was used for real-time prediction of the Melt Flow Index and percentage of bounded acrylonitrile (%AN). The results show that the MSPC model was able to detect deviations from normal operative conditions, indicating the variables responsible for the deviation, be they spectral or process. Moreover, predictive regression models obtained using the fused data showed better results than models computed using single datasets in terms of both errors of prediction and R2. Thus, the fusion of spectra and process data improved the real-time monitoring, allowing an easier visualization of the process ongoing, a faster understanding of possible faults, and real-time assessment of the final product quality

Hepatotoxicity Associated with the Use of Anti-TNF-α Agents

Medications to inhibit the actions of tumour necrosis factor alpha have revolutionized the treatment of several pro-inflammatory autoimmune conditions. Despite their many benefits, several serious side effects exist and adverse reactions do occur from these medications. While many of the medications' potential adverse effects were anticipated and recognized in clinical trials prior to drug approval, several more rare adverse reactions were recorded in the literature as the popularity, availability and distribution of these medications grew. Of these potential adverse reactions, liver injury, although uncommon, has been observed in some patients. As case reports accrued over time and ultimately case series developed, the link became better established between this family of medicines and various patterns of liver injury. Interestingly, it appears that the majority of cases exhibit an autoimmune hepatitis profile both in serological markers of autoimmune liver disease and in classic autoimmune features seen on hepatic histopathology. Despite the growing evidence of this relationship, the pathogenesis of this reaction remains incompletely understood, but it appears to depend on characteristics of the medications and the genetic composition of the patients; it is likely more complicated than a simple medication class effect. Because of this still incomplete understanding and the infrequency of the occurrence, treatments have also been limited, although it is clear that most patients improve with cessation of the offending agent and, in certain cases, glucocorticoid use. However, more needs to be done in the future to unveil the underlying mechanisms of this adverse reaction