Measurement of Organized Crime in the Italian Provinces with Spatially-Clustered Heterogeneity

ABSTRACTThis paper investigates the convergence process and the distribution dynamics of income among Italian NUTS-3 provinces between 2003 and 2011. Findings show the existence of multiple steady-state equilibria which is consistent with the well-documented persistence in income disparities among Italian provinces. The role of grant-making activities by Bank Foundations is assessed on a conditioning scheme. Results suggest that Bank Foundations can affect the shape of the distribution of income and, in the long run, reduce polarization with a tendency for income to collapse towards a unimodal distribution.

Municipal Waste Production, Economic Drivers, and 'New' Waste Policies: EKC Evidence from Italian Regional and Provincial Panel Data

A Human Capital Index for the Italian Provinces

A Human Capital Index for the Italian Provinces

This study examines the role of the Herfindahl-Hirschman Index (HHI) and a new diversification index that integrates geographical and sectoral factors to analyze economic activities in Italian provinces. The research highlights how local territorial heterogeneity influences urban and regional economics, emphasizing diversification as a strategy for growth. The findings underscore diversification’s importance in enhancing economic stability and resilience, while comparing it with specialization. Although it can boost competitive advantage through efficiency and innovation, specialization also increases vulnerability to sector-specific risks. The study calculates the HHI by using three categories: geographical diversification of export destinations, sectoral exports, and geographical import diversification. These insights provide a groundbreaking understanding of the economic dynamics within Italian provinces and regions, showcasing the advantages and trade-offs between diversification and specialization in regional economic development.

BackgroundExposure to particulate matter has been associated with increased risk of cardiovascular and respiratory diseases. We evaluated the ecological correlation between standardized hospital discharges with diabetes in Italian provinces and fine particulate matter (PM2.5) adjusting for common risk factors, socioeconomic factors and differences in hospitalization appropriateness.MethodsWe used cross sectional data aggregated at the province level and available from official institutional databases for years 2008–2010. Covariates included prevalence of adult overweight, obese, smokers, physically inactive, education and income (as average gross domestic product per person, GDP). We reduced the number of covariates to a smaller number of factors for the subsequent statistical model by extracting meaningful components using principal component analysis (PCA). Log-linear multiple regression analysis was used to model diabetes hospital discharges with PCA components and PM2.5 levels and hospitalization appropriateness for men and women.ResultsThe first PCA components for both men and women were characterized by larger loadings of risk factors (obesity, overweight, physical inactivity, cigarette smoking) and lower socioeconomic factors (educational level and mean GDP). Diabetes hospitalization increases with the first PCA component and decreases with the index of hospitalization appropriateness. In fully adjusted models, diabetes hospitalizations increase with increasing annual PM2.5 concentrations, with a rise of 3.5 % (1.3 %–5.6 %) for men and of 4.0 % (1.5 %-6.4 %) for women per unit of PM2.5 increase.ConclusionsWe found a significant ecological relationship between sex and age standardised hospital discharge with diabetes as principle diagnosis and mean annual PM2.5 concentrations in Italian provinces, once that covariates have been accounted for. The relationship was robust to different means of estimating PM2.5 exposure. A large portion of the variance of diabetes hospitalizations was linked to differences of hospital care appropriateness between Italian regions and this variable should routinely be included in ecological analyses of hospitalizations.

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.

Does unconventional monetary policy boost local economic development? The case of TLTROs and Italy

Social capital, quality of institutions and lockdown. Evidence from Italian provinces

IntroductionParticulate matter exposure has been associated with the appearance and severity of several diseases, including viral infections. The aim of this study was to investigate whether coronavirus disease 2019 (COVID-19) cases and deaths across Italian regions and provinces in March 2020 were linked to past exposure to fine and coarse particulate matter (namely, PM2.5 and PM10, respectively).Material and methodsGeographical distributions of COVID-19 cases and deaths (105,792 and 12,428, respectively, up to 31st March 2020), PM2.5 and PM10 exposure, and demographic characteristics were extracted from publicly accessible databases. Adjusted regression models were performed to test the association between particulate matter exposure in different Italian regions and provinces and COVID-19 incidence proportions and death rates.ResultsA heterogeneous distribution of COVID-19 cases/deaths and particulate matter exposure was observed in Italy, with the highest numbers in Northern Italy regions and provinces. Independent associations between regional PM2.5/PM10 exposure and COVID-19 incidence proportion and death rate were observed (COVID-19 incidence proportion: β = 0.71, p = 0.003, β = 0.61, p = 0.031, respectively; COVID-19 death rate: β = 0.68, p = 0.004 and β = 0.61, p = 0.029, respectively). Similarly, PM2.5/PM10 exposures were independently associated with COVID-19 incidence proportion (β = 0.26, p = 0.024 and β = 0.27, p = 0.006, respectively) at the provincial level. The number of days exceeding the provincial limit value of exposure to PM10 (50 µg/m3) was also independently associated with the COVID-19 incidence proportion (β = 0.30, p = 0.008).ConclusionsExposure to PM2.5 and PM10 is associated with COVID-19 cases and deaths, suggesting that particulate matter pollution may play a role in the COVID-19 outbreak and explain the heterogeneous distribution of COVID-19 in Italian regions and provinces.

Migration and the Structure of Manufacturing Production. A View from Italian Provinces

We reconstruct agricultural production across Italian provinces from 1871 to 1911 and examine how protectionist tariffs differently impacted on economic growth. Using a difference-in-differences model, we find that tariffs' effects varied significantly following local agricultural institutions: in most of the North, tariffs fostered modernization and productivity growth; conversely, in the South tariffs, although benefitting landowners in the short run, reinforced extractive practices and hindered development. These divergent responses to the same policy intervention deepened Italy’s North–South divide and highlight how institutional regimes and local conditions mediated the effectiveness of trade protection.

Low‐skill jobs and routine tasks specialization: New insights from Italian provinces

Using information on new knowledge intensive firms (KIFs) and universities in Italy, this chapter explores whether and how new KIFs creation at the local level depends on university presence. We evaluate the impact on new KIFs creation of: i) the different knowledge inputs offered by universities to geographical areas in which they are embedded and ii) the field of science in which universities are specialized. Moreover, we study whether and how the impact of university presence on new KIFs creation in a geographical area depends on economic development. After having classified data into geographical units (NUTS 3 level, Italian provinces), according to the location of new KIFs and universities, we estimate negative binomial regression models, where the dependent variable is the number of new KIFs in each Italian province. Results suggest that new KIFs creation at the local level is influenced by university presence. Furthermore, university specialization in the field of engineering and medical sciences positively influences new KIFs creation at the local level. Finally, we find a strong and significant effect of university presence in southern less developed provinces. Conversely, our data document that university presence does not affect new KIFs creation in northern, well developed provinces. We interpret these findings in light of the Italian North-South divide.

I feel that the paper lacks a certain level of rigorousness because of poor grammatical construction, which necessitate major revision. The paper is full of awkward stylistic formulations, which make it difficult to follow the authors' ideas. My first impression is that the paper needs a thorough proofreading and copyediting. I recommend the authors to have their manuscript reviewed by a native English language speaker. Please avoid using acronyms and initials; write terms out fully. Use third-person perspective only (no "my" "I" or "our" referents). Use past tense when discussing the procedure and results as well as other researchers' procedures and results.