Italian Provinces Research Articles

Machine Learning Models for Regional Photovoltaic Power Generation Forecasting with Limited Plant-Specific Data

Predicting electricity production from renewable energy sources, such as solar photovoltaic installations, is crucial for effective grid management and energy planning in the transition towards a sustainable future. This study proposes machine learning approaches for predicting electricity production from solar photovoltaic installations at a regional level in Italy, not using data on individual installations. Addressing the challenge of diverse data availability between pinpoint meteorological inputs and aggregated power data for entire regions, we propose leveraging meteorological data from the centroid of each Italian province within each region. Particular attention is given to the selection of the best input features, which leads to augmenting the input with 1-hour-lagged meteorological data and previous-hour power data. Several ML approaches were compared and examined, optimizing the hyperparameters through five-fold cross-validation. The hourly predictions encompass a time horizon ranging from 1 to 24 h. Among tested methods, Kernel Ridge Regression and Random Forest Regression emerge as the most effective models for our specific application. We also performed experiments to assess how frequently the models should be retrained and how frequently the hyperparameters should be optimized in order to comprise between accuracy and computational costs. Our results indicate that once trained, the model can provide accurate predictions for extended periods without frequent retraining, highlighting its long-term reliability.

The impact of public health efficiency on well-being in Italian provinces

PurposeThis work aims to analyse the relationship between public health efficiency and well-being considering a panel of 102 Italian provinces from 2000 to 2016 and evaluates if there are omitted variable biases and endogeneity biases and also evaluates if there are heterogeneous effects among provinces with different income levels.Design/methodology/approachWe use a multi-input and output bootstrap data envelopment analysis to assess public health efficiency. Then, we measure well-being indices using the min-max linear scaling transformation technique. A two-stage least squares model is used to identify the causal effect of improving public health efficiency on well-being to account for time-invariant heterogeneity, omitted variable bias and endogeneity bias.FindingsAfter controlling for important economic factors, the results show a significant effect of an accountable and efficient public health system on well-being. Those effects are concentrated in the North, the most economically, geographically and environmentally advantageous areas.Research limitations/implicationsThe use of the sample mean, probably the oldest and most used method for aggregating the indicators, could be affected by variable compensation, with consequent misleading results in the process of constructing the well-being index. Another limitation is the use of lagged values of the main predictor as an instrument in the instrumental variables setting because it could lead to information loss. Finally, the availability of data over a long period of time.Practical implicationsThe findings could help policymakers adopt measures to strengthen the public health system, encourage private providers and inspire countries worldwide.Social implicationsThese results draw the attention of local authorities, who play an important role in designing and implementing policies to stimulate local public health efficiency, which puts individuals in the conditions of achieving overall well-being in their communities.Originality/valueFor the first time in Italy, a panel of well-being indices was constructed by developing new methodologies based on microeconomic theory. Furthermore, for the first time, the assessment of the relationship between public health efficiency and well-being is carried out using a panel of 102 Italian provinces.

Air pollution and mortality for cancer of the respiratory system in Italy: an explainable artificial intelligence approach.

Respiratory system cancer, encompassing lung, trachea and bronchus cancer, constitute a substantial and evolving public health challenge. Since pollution plays a prominent cause in the development of this disease, identifying which substances are most harmful is fundamental for implementing policies aimed at reducing exposure to these substances. We propose an approach based on explainable artificial intelligence (XAI) based on remote sensing data to identify the factors that most influence the prediction of the standard mortality ratio (SMR) for respiratory system cancer in the Italian provinces using environment and socio-economic data. First of all, we identified 10 clusters of provinces through the study of the SMR variogram. Then, a Random Forest regressor is used for learning a compact representation of data. Finally, we used XAI to identify which features were most important in predicting SMR values. Our machine learning analysis shows that NO, income and O3 are the first three relevant features for the mortality of this type of cancer, and provides a guideline on intervention priorities in reducing risk factors.

Comparative analysis of alpine agritourism in Trentino, Tyrol, and South Tyrol: Regional variations and prospects

Abstract Agritourism is an increasingly popular form of tourism that entails visiting farms to engage in activities and gain insights into the farming way of life. This research explores the economic, social, and environmental dynamics of agritourism in the Tyrol–South Tyrol–Trentino Euroregion with a specific emphasis on the three distinct regional entities in Austria and Italy: the Austrian state of Tyrol (comprising North and East Tyrol) and the Italian autonomous provinces of South Tyrol and Trentino. It addresses two key research aims: uncovering regional distinctions among these Alpine provinces and understanding the motivations, challenges, and future plans of agritourism operators. A comprehensive review of existing literature frames the study, while data collection involves an online survey of agritourism farms in the region. Distinctive characteristics emerge, with Trentino emphasizing restaurant services, sustainability, and community engagement. South Tyrol prioritizes quality accommodations and work–life balance, while Tyrol aligns closer with South Tyrol’s focus. Notably, economic factors exert a substantial influence on their motivations to embrace agritourism, underscoring their pivotal role in this context. Despite facing challenges such as “time management and labour,” “meeting visitors’ expectations,” and “local permits and taxes,” most agritourism operators across the region display willingness to expand their activity in the future. Overall, agritourism in the study area is characterized by significant structural and operational differences resulting in different future public support and regulatory needs.

The interaction between corruption, bank cost efficiency and economic development in Italy

In this paper, we assess the interaction between corruption, bank cost efficiency, and economic development. Existing literature on the subject normally focuses separately on the link between corruption, financial development, and growth, and finds ambiguous results, not distinguishing between different types of credit institutions. We use Italian disaggregated data from 2004 to 2012, considering cooperative and non-cooperative banks, to determine whether controlling corruption affects banks’ cost efficiency in Italian provinces and promotes economic development. Utilizing a panel autoregressive model, we find that controlling corruption magnifies the positive impact of banks’ cost efficiency on economic development. Evidence of a positive effect of the interaction is observed, particularly in the case of non-cooperative banks and for higher values of the Control of Corruption Index.

Insights from Explainable Artificial Intelligence of Pollution and Socioeconomic Influences for Respiratory Cancer Mortality in Italy.

Respiratory malignancies, encompassing cancers affecting the lungs, the trachea, and the bronchi, pose a significant and dynamic public health challenge. Given that air pollution stands as a significant contributor to the onset of these ailments, discerning the most detrimental agents becomes imperative for crafting policies aimed at mitigating exposure. This study advocates for the utilization of explainable artificial intelligence (XAI) methodologies, leveraging remote sensing data, to ascertain the primary influencers on the prediction of standard mortality rates (SMRs) attributable to respiratory cancer across Italian provinces, utilizing both environmental and socioeconomic data. By scrutinizing thirteen distinct machine learning algorithms, we endeavor to pinpoint the most accurate model for categorizing Italian provinces as either above or below the national average SMR value for respiratory cancer. Furthermore, employing XAI techniques, we delineate the salient factors crucial in predicting the two classes of SMR. Through our machine learning scrutiny, we illuminate the environmental and socioeconomic factors pertinent to mortality in this disease category, thereby offering a roadmap for prioritizing interventions aimed at mitigating risk factors.

External relations, regional productivity, and exogenous shocks: lessons from the Italian experience

AbstractThis study provides novel insights into the debate concerning the external drivers of productivity at local (NUTS-3) level. In particular, it explores the role played by global production networks, measured through ownership ties among multinational firms and their subsidiaries abroad, in shaping patterns of productivity growth of local economies. Focusing on the Italian experience and using spatial econometrics techniques, the article demonstrates that external relations play a crucial role in sustaining the productivity of Italian provinces, even during periods of severe economic downturns, like the Great Recession. In detail, productivity growth is positively correlated with the Intensity of the networks established by multinational firms and their geographical dispersion.

Effectiveness of the SARS-CoV-2 Vaccination in Preventing Severe Disease-Related Outcomes: A Population-Based Study in the Italian Province of Bolzano (South Tyrol).

Objective: To investigate the effectiveness of SARS-CoV2 vaccination in preventing ordinary or intensive care unit (ICU) admissions and deaths among cases registered during a variant transitional pandemic phase in the geographically and culturally unique territory of the Province of Bolzano (South Tyrol), an Italian region with low vaccination coverage. Methods: We collected data from 93,643 patients registered as positive for SARS-CoV-2 by health authorities during the winter of 2021-22. The data were analyzed retrospectively using descriptive statistics and multiple logistic regression. Results: 925 patients were hospitalized (0.99%), 89 (0.10%) were in intensive care, and 194 (0.21%) died. Vaccinated patients had a significantly lower risk of being hospitalized: adjusted Odds Ratio (aOR): 0.39; 95% CI: 0.33-0.46, ICU admission: aOR: 0.16; 95% CI: 0.09-0.29 and death: aOR: 0.41; 95% CI: 0.29-0.58. Similar risk reductions were also observed in booster-vaccinated patients, independent of sex, age, and predominant variant. Furthermore, the median length of stay (LoS) in the ICU was significantly longer for unvaccinated individuals compared to vaccinated subjects (9 vs. 6days; p < 0.003). Conclusion: Primary series vaccination and ongoing campaign booster doses were effective in preventing all severe disease-related outcomes and in reducing ICU Length of Stay, even during a transitional pandemic phase and in a unique territorial context.

Access to credit and economic complexity: Evidence from Italian provinces

AbstractThis paper focuses on the relationship between “urbanization economies” and access to bank credit by assessing the role of product variety and economic complexity in affecting local credit market conditions. Using quarterly data on Italian provinces for 2008–2018 and adopting a dynamic (spatial) econometric approach, the work provides robust evidence highlighting how local economic complexity reduces the barriers to accessing local credit markets. With a greater “qualified” diversification (higher economic complexity), banks access successful projects with greater probability and are more willing to grant credit. The estimation results also reveal the existence of long‐run spatial spillover effects. The empirical findings advocate for a nuanced and context‐specific policy framework. By embracing place‐based and mission‐oriented policies encouraging diversification and knowledge diffusion, regions can enhance their economic resilience and provide tailored support to businesses, ensuring their stability and growth even in the face of challenging credit conditions.

The musical past revives in the present: An investigation into the cultural heritage of a community

This article explores how two specific musical performances, drawing respectively on the rich repertoire of Italian sacred music and a specific sound environment of a region, can promote cultural participation and ingenuity in the Italian countryside amidst uncertainty and demographic change due to depopulation and the loosening of traditional communal ties. The first study focuses on a specific case in the town of Ortona dei Marsi in the Italian province of L’Aquila. A seemingly everyday experience – participation in community singing – is considered and appreciated from a musicological perspective, while its importance for the revitalisation of a community is recognised. The rediscovering of a forgotten musical heritage contributes to an evolving, prosaic sense of rural cultural resources. The particular case of the community of the small rural town of Ortona dei Marsi, overcoming isolation, distance and new circumstances through the revitalisation of a musicologically significant object, sheds light on how a community serendipitously uses the opportunity to make and maintain music together to demonstrate social and cultural resilience. The second study looks at the experiences of middle school students in the Italian city of Biella of a specific sound memory that guides and paves the way to a diverse learning environment.

Spatial Comprehensive Well-Being Composite Indicators Based on Bayesian Latent Factor Model: Evidence from Italian Provinces

This paper proposes spatial comprehensive composite indicators to evaluate the well-being levels and ranking of Italian provinces with data from the Equitable and Sustainable Well-Being dashboard. We use a method based on Bayesian latent factor models, which allow us to include spatial dependence across Italian provinces, quantify uncertainty in the resulting estimates, and estimate data-driven weights for elementary indicators. The results reveal that our data-driven approach changes the resulting composite indicator rankings compared to those produced by traditional composite indicators’ approaches. Estimated social and economic well-being is unequally distributed among southern and northern Italian provinces. In contrast, the environmental dimension appears less spatially clustered, and its composite indicators also reach above-average levels in the southern provinces. The time series of well-being composite indicators of Italian macro-areas shows clustering and macro-areas discrimination on larger territorial units.

MSW Management in Two Italian Mountainous Areas

Abstract Two case studies are reported in the present work. They regard municipal solid waste (MSW) management trends in the last decades in two Italian provinces selected to analyse some issues of waste management in mountainous areas. The first case study refers to a selective collection (SC) rate expected to reach 80 % soon. This scenario assumes SC mainly in kerbside mode. The scenario is based on specific local conditions: the absence of a thermo-chemical plant in the territory (but with a part of the residual MSW burnt in a neighbour province), the presence of local plant of anaerobic, and a sanitary landfill for pre-treated residual MSW. The adopted tariff helped increasing the SC rate: indeed, since 2013, a tariff calculated at user level, depending on the behaviour of each user, has been adopted. This is called punctual tariff. The second case study concerns an area where SC reached about 75 %. The punctual tariff has been recently introduced. In this scenario, an incineration plant and a Solid Recovered Fuel (SRF) plant allow implementing an industrial symbiosis solution in conjunction with a cement factory. The work demonstrates that SC can be the core of a correct MSW management and that kerbside collection is fully compatible with mountainous area. However, other issues remain to be optimized yet: the low density of mountain areas makes difficult to implement enhanced solutions of SC (e.g. for diapers) and increases costs for light packaging collection; moreover, the presence of tourist fluxes can significantly affect SC efficiency.

COVID-19 could accelerate the decline in recreational hunting: A natural experiment from Northern Italy.

Although many studies highlighted the potential of COVID-19 to reshape existing models of wildlife management, empirical research on this topic has been scarce, particularly in Europe. We investigated the potential of COVID-19 pandemic to accelerate the ongoing decline in an aging population of recreational hunters in Italy. Namely, we modelled spatiotemporal trends between 2011 and 2021 in the number of recreational hunters in 50 Italian provinces with a varying incidence of COVID-19, and temporally delayed waves of infection. Compared to projections from 2011-2019 data, we detected a lower number of hunters who enrolled for the hunting season, both in 2020 (14 provinces) and in 2021 (15 provinces). The provinces with the highest incidence of COVID-19 in the Lombardy and Emilia-Romagna regions were also those experiencing the most marked decrease in hunting participation. Our findings revealed that a wildlife management system based on recreational hunting can be rapidly destabilized by epidemics and their associated public health measures, particularly when the average age of hunters is high, like in Italy. Considered the high incidence attained by COVID-19 in many European countries, where hunters are pivotal for the management of large ungulates and where they were already declining before the pandemic, our findings call for further large-scale research about the impact of COVID-19 on hunting participation.

Residential exposure to magnetic fields from transformer stations and risk of childhood leukemia

BackgroundSeveral studies have documented an increased risk of leukemia among children exposed to magnetic fields from high-voltage power lines, with some evidence of dose-response relation. However, findings in some studies have been inconsistent, and data on the effects of different sources of exposure are lacking. In this study, we evaluated the relation of childhood leukemia risk to exposure to magnetic fields from transformer stations. MethodsWe conducted a population-based case-control study in a pediatric population of two Northern Italian provinces of Modena and Reggio Emilia. We included 182 registry-identified childhood leukemia cases diagnosed during 1998–2019 and 726 population controls matched on sex, year of birth, and province of residence. We assessed exposure by calculating distance from childhood residence to the nearest transformer station within a geographical information system, computing disease odds ratios (ORs) and 95% confidence intervals (CIs) using conditional logistic regression, adjusting for potential confounders. We evaluated exposure using two buffers (15 m and 25 m radius) and assessed two case groups: leukemia (all subtypes) and acute lymphoblastic leukemia (ALL). ResultsResiding within 15 m of a transformer station (vs. ≥15 m) was not appreciably associated with risk of leukemia (all subtypes) or ALL. We found similar results using a less stringent exposure buffer (25 m). Among children aged ≥5 years, the adjusted ORs were 1.3 (95% CI 0.1–12.8) for leukemia and 1.3 (95% CI 0.1–12.4) for ALL using the 15 m buffer, while they were 1.7 (95% CI 0.4–7.0) for leukemia and 0.6 (95% CI 0.1–4.8) for ALL using the 25 m buffer. ConclusionsWhile we found no overall association between residential proximity to transformer stations and childhood leukemia, there was some evidence for elevated risk of childhood leukemia among children aged ≥5 years. Precision was limited by the low numbers of exposed children.

Migration and the location of MNE activities: Evidence from Italian provinces

AbstractWe investigate the migration‐inward foreign direct investment (FDI) nexus in narrow geographies. A novel two‐stage empirical strategy allows us to investigate the role of migration as a determinant of multinational enterprises (MNEs) location choices and unpick heterogeneity in foreign investors' preferences towards the presence of migrants in the host location. This allows us to shed light on the relative importance of the underlying mechanisms linking migration and inward FDI. Relying on 1113 greenfield investments by 895 MNEs in Italian NUTS3 regions over 2003–2015, we find that immigrants from the country of origin of the investor exert a positive but highly heterogeneous effect on MNE location choices. Investors are more sensitive to the presence of migrants from their country of origin when they lack experience in the destination country (first‐time investors) and when their investments concern market‐access or business‐services (downstream) activities. This is consistent with the view that migrants act as information brokers that bridge the fixed costs of international business activities.

What Else Is Needed to Improve Survival from Out-of-Hospital Cardiac Arrest to Hospital Admission? Data from a Prospective Registry for the Years 2020–2023 in the Italian Province of Varese

What Else Is Needed to Improve Survival from Out-of-Hospital Cardiac Arrest to Hospital Admission? Data from a Prospective Registry for the Years 2020–2023 in the Italian Province of Varese

Strengthening local economies through social capital: The role of cooperative firms in driving economic growth in Italy

AbstractThis paper aims to empirically explore the linkage between the cooperative sector and economic growth in Italian provinces (NUTS‐3), through a panel analysis covering the period between 2013 and 2019. We hypothesize that the cooperative sector can contribute to economic growth through its ability to generate social capital, thereby helping to mitigate market failures. The empirical analysis does not provide us with robust evidence of the positive connection between the cooperative sector as a whole and local economic growth. However, when we disaggregate the cooperative sector into ordinary and social cooperatives, we find intriguing results. Indeed, there is robust evidence of a negative relationship between the territorial distribution of ordinary cooperatives and economic growth, while for social cooperatives we find a positive relationship. We interpret these results as showing that the pursuit of general interest objectives, which allows the principle of mutuality to be extended to indirect forms of reciprocity, could make cooperative firms more effective in promoting the economic performance of territories. This is because they are more likely to generate bridging social capital that encourages the spread of generalized trust, a key factor in the advancement of modern market economies.

Incidence and Survival of Testicular Cancers in a Province in Northern Italy and Their Association with Second Tumors.

This study investigated the incidence, mortality, and 5-year survival rates of testicular cancers diagnosed in a northern Italian province, which were eventually associated with previous or subsequent extratesticular neoplasms. Cases from 1996 to 2020 were examined by age and histotype (seminoma vs. non-seminoma). The standardized incidence rate was calculated using the European population, and the annual percent change (APC) was reported. The five-year relative survival was estimated using the Pohar Perme method. The association with the second neoplasm was also evaluated. In our study, 385 patients with testicular cancer were included, most of whom were aged between 30 and 40 years. The non-seminoma and seminoma groups accounted for 44% and 18% of younger adults, respectively. The incidence rate increased during the study period (APC 1.6*); however, it increased in seminomas (APC 2.3*) but not in non-seminomas (APC -0.1). Conversely, the mortality rate remained constantly low either overall or in each of the two groups. The overall 5-year survival rate of testicular cancer patients was 95% (99% and 88% for seminomas and non-seminomas, respectively). Primary extratesticular tumors were documented in 37 cases, 18 after and 19 before the testicular cancer diagnosis. Our study confirms that the increased incidence and excellent survival rate are the prerogative of seminomas.

Investigating mortality trends in Italy during the COVID-19 pandemic: life expectancy changes within provinces and vaccination campaign impact up to December 2022

ObjectivesWe used publicly available population data from 1 January 2019 up to 31 December 2022, to investigate mortality trends in Italy during the COVID-19 pandemic, evaluating changes in life expectancy (LE) at birth within provinces and the impact of COVID-19 vaccinations. Study designAggregate data analysis. MethodsAnnual period life tables were used to estimate sex-specific LEs within provinces from 2019 to 2022. We used Arriaga decomposition to analyze the contribution of age groups (<60 years and ≥60 years) to annual LE changes. We implemented a Quasi-Poisson regression model to estimate the number of averted deaths by the achieved COVID-19 vaccination rates from January 2021 up to December 2022, simulating a counterfactual scenario where vaccine doses were not administered. ResultsThe results revealed geographical heterogeneity in annual LE changes across Italian provinces during the pandemic. By the end of 2022, LE was below the prepandemic levels in 88% of provinces for females and in 76% for males. In addition, we estimated that the achieved vaccination rates averted 460,831 deaths (95% confidence interval: 250,976–707,920), corresponding to a 25% reduction in expected all-cause mortality. ConclusionsOverall, the study highlighted the significant role of COVID-19 vaccinations in averting a considerable number of deaths and improving LE. However, by the end of 2022, LE had not fully recovered to prepandemic levels in many provinces. This could be attributed to concurrent factors, including enduring COVID-19 pandemic effects, intense summer heat waves and early onset of seasonal flu. Further research and continuous monitoring are essential to fully comprehend long-term mortality trends and optimize public health strategies.

Assessing geographical differences of the COVID-19 impact on fuel consumption: the case of Italy

We propose a spatio-temporal analysis aiming at estimating the variation of gasoline and diesel consumption occurred in the Italian provinces as a consequence of the COVID-19 pandemic during 2020 and 2021. We employ generalized linear models and generalized additive models to predict business-as-usual per capita fuel consumption by means of socio-economic variables, such as demography, tourist stays, temperature and territorial characteristics. The province-specific impact of the restrictions is then estimated as the difference between the observed and model-predicted values. The spatio-temporal dynamics is introduced by means of appropriate spline basis functions allowing both spatial and time trend to be smooth surfaces. Moreover, we include a smooth spatio-temporal interaction that properly capture the seasonal characteristic of different areas. Our findings highlight that the national mobility restrictions imposed to fight the spread of COVID-19 in the first wave (March to May 2020) reduced gasoline and diesel consumption homogeneously nationwide, with some slight differences between northern and southern provinces. However, the second wave lockdown (Winter 2020–2021) determined heterogeneous impacts across Italian provinces. In particular, we highlight the existence of a divergence between North and South Italy in terms of reaction to the pandemic. Indeed, while southern provinces experienced the weakest and less variable reductions, the northern provinces recorded strong and persistent contractions of fuel consumption. Also, southern and tourism-devoted provinces recovered quickly and compact to the post-pandemic reopenings.