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This research proposes an analysis of the spread of COVID-19 during the three waves at the provincial level in Italy. Specifically, this study examines the distribution of COVID-19 cases across Italian provinces to determine the potential existence of territorial clusters, which are measured by spatial autocorrelation among the provinces. Furthermore, this study examines whether a convergence process occurred in the contagion of the virus among the provinces, thereby estimating its relative speed. To this end, the β-convergence model—commonly applied in economic growth models—is employed in this study to consider the demographic and environmental variables present in each province. The initial level and growth of infections observed in a certain province are then related to the level of infections and their growth rate in all other Italian provinces. This econometric estimation is conducted for the first, second, and third waves of the pandemic between March 2020 and June 2021, using covariates such as population density, aging index, average temperature, pollution levels, and the duration of the waves. The hypothesis of COVID-19 convergence, verified in all three waves, recorded a rather different average speed, with an influence exerted by demographic and environmental variables. Additionally, the econometric analysis is integrated, considering spatial effects using the Spatial Autoregressive (SAR) and Spatial Error (SEM) models, after verifying the existence of autocorrelation of the residuals for the first and third waves. The results obtained in this second estimation only partially confirm the influence of demographic and environmental variables for the first and third waves. In the first wave—in addition to identifying any spillover effects among provinces—the effects are decomposed into direct, indirect, and total effects. [ABSTRACT FROM AUTHOR]

The controversies on the relationship (called 'gradient') between the time trend of GDP and of subjective well-being oppose those who claim that the gradient is positive, to those who argue that it is nil. The possible existence of significant changes of the two trends and of the gradient within the same country is a challenge to both views. By focusing on the case of Italy, we show that the long-run trends of GDP and of well-being turned from increasing to decreasing, and that the gradient exhibits a rise through two structural breaks. This evidence is consistent with the 'loss aversion' hypothesis. From this macro-analysis we further go into micro-analysis to explain why subjective well-being declined so steeply. We find that the erosion of trust in others, the increase of financial dissatisfaction, worsened health, and greater importance of income contribute to the decline of subjective well-being. As far as we know, this is the first attempt to test the role of loss aversion in the long run using both macro- and micro-economic approaches. [ABSTRACT FROM AUTHOR]

Although the literature on the relationship between economic growth and CO2 emissions is extensive, the use of machine learning (ML) tools remains seminal. In this paper, we assess this nexus for Italy using innovative algorithms, with yearly data for the 1960–2017 period. We develop three distinct models: the batch gradient descent (BGD), the stochastic gradient descent (SGD), and the multilayer perceptron (MLP). Despite the phase of low Italian economic growth, results reveal that CO2 emissions increased in the predicting model. Compared to the observed statistical data, the algorithm shows a correlation between low growth and higher CO2 increase, which contradicts the main strand of literature. Based on this outcome, adequate policy recommendations are provided. [ABSTRACT FROM AUTHOR]

Academic research is generally seen as one of the most important goals of a university, but universities are being called upon simultaneously to assist in building a local entrepreneurial ecosystem and contributing to economic growth. Universities can be the source of startups based on academic research results and thereby influence a given industrial context. This paper investigates the impact of academic entrepreneurship on the economic performance of university spin-offs (USOs) and, in particular, how the composition of the founding team, the diversity of academic ownership, CEO duality, and the presence of women on the board of directors affect USO success. We study these relationships with a cross-sectional sample of 136 firms in southern Italy. Our findings highlight that governance and ownership can influence various indicators that are often used for measuring enterprise success in different ways and that, based on the specific success metrics, managers or policymakers should consider different aspects to better understand a USO's potential for success. [ABSTRACT FROM AUTHOR]

Forecasting mortality is still a big challenge for Governments that are interested in reliable projections for defining their economic policy at local and national level. The accuracy of mortality forecasting is considered an important issue for longevity risk management. In the literature, many authors have analyzed the long-run relationship between mortality evolution and socioeconomic variables, such as economic growth, unemployment rate or educational level. This paper investigates the existence of a link between mortality and real gross domestic product per capita (GDPPC) over time in the Italian regions. Empirical evidence shows the presence of a relationship between mortality and the level of real GDPPC (and not its trend). Therefore, we propose a multi-population model including the level of real GDPPC and we compare it with the Boonen–Li model (Boonen and Li in Demography 54:1921–1946, 2017). The validity of the model is tested in the out-of-sample forecasting experiment. [ABSTRACT FROM AUTHOR]

This paper empirically explores the dynamic relationships between financial development, globalization, energy consumption, economic growth, and ecological footprint in G7 countries over the period 1980–2015. Using a recently introduced threshold cointegration test with an endogenous structural break, the paper aims primarily to determine the effects of financial development and globalization on environmental degradation. The results confirm the presence of cointegration in Canada, Italy, and Japan. The long-run estimates indicate that globalization significantly reduces ecological footprint in Canada and Italy, while financial development reduces pollution in Japan. The findings also demonstrate that energy consumption stimulates environmental degradation in these three countries. Furthermore, the causality test that considers smooth structural breaks via a fractional frequency flexible Fourier function indicates that globalization causes ecological footprint in all the G7 countries except France, while financial development causes ecological footprint in France, Japan, and the United Kingdom. Finally, the overall results suggest that globalization is a more effective tool than financial development in regulating ecological footprint for G7 countries. Therefore, we recommend that policymakers should make use of the opportunities that globalization offers to solve environmental problems. [ABSTRACT FROM AUTHOR]

This paper re-investigates the time-varying impacts of economic growth on carbon emissions in the G-7 countries over a long history. In doing so, the historical data spanning the period from the 1800s to 2010 (as constructed) for each country is examined using the time-varying cointegration and bootstrap-rolling window estimation approach. Unlike the previous environmental Kuznets curve (EKC) studies, using this methodology gives us avenue to detect more than one, two, or more turning points for the economic growth-carbon emissions nexus. The empirical findings show that the nexus between economic growth and carbon emission seems over a long history to be M-shaped for Canada and the UK; N-shaped for France; inverted N-shaped for Germany; and inverted M-shaped (W-shaped) for Italy, Japan, and the USA. In addition, the possible validity of EKC hypothesis is examined for both the pre-1973 and post-1973 sub-periods. Based on this investigation, we found that an inverted U-shaped is confirmed only for the pre-1973 period in France, Italy, and the USA. These empirical evidences provide new insights to policy makers to improve environmental quality using economic growth as an economic tool for the long run by observing changes in the environmental impact of this growth from year to year. [ABSTRACT FROM AUTHOR]

By means of stochastic volatility in the mean model to allow for time-varying parameters in the conditional mean and quarterly data for the G7 countries, this article examines the dynamic nexus between the volatility of output and economic growth for the G7 countries. This approach allows us to model parameter time-variation so as to reflect changes in the effect of volatility appearing in both the conditional mean and the conditional variance. The evidence in this article indicates that the effect of output volatility on output growth is strongly time-varying and quite analogues for all the G7 countries, with a break around 1973. The effect of output volatility on growth becomes more negative after 1973, with negative and statistically significant estimates after 1973 or early 1990s. Our estimates show a reversal of the declining trend and a significant increase in output volatility in the late-2000s, indicating that the Subprime Crisis brought a temporary break in the Great Moderation. However, the Great Moderation seems to be generally restored by the mid-2010s. The effect of output growth on output volatility is insignificant for all countries except for Italy and the US, for which the estimates are positive and statistically significant. Our estimates also show that output volatility is counter-cyclical for all countries. [ABSTRACT FROM AUTHOR]

This paper aims to answer two research questions: (1) Is the smart sustainable city (SSC) environment a stimulus for the urban knowledge-based economy?; and (2) Which SSC domains are more conducive to stimulating the urban knowledge-based economy? To answer these questions, this study develops a framework and multidimensional indexes to better explain the different domains of the SSC and their impact on the knowledge-based economy. The analysis was performed on a sample of 116 Italian cities. Italy was chosen because smart city policies are diffused nationwide and Italian urban development is very differentiated (large and small cities; northern and southern cities). The results confirm that the knowledge-based economy at city level is positively correlated to the creation of a urban smart sustainable environment. Moreover, sustainable social services and sustainable local transport are considered the most relevant components of SSC. Our study contributes significantly to the literature by providing a new approach to understanding the factors influencing the creation of an SSC and identifying which SSC domains are important for the development of urban-level economic growth, suitable not only. Its findings, therefore, have implications for academics and urban policy makers, especially for the valorisation of smaller cities. [ABSTRACT FROM AUTHOR]

Fertility, a key process shaping long-term population dynamics, has reflected demographic transitions and responds—more or less rapidly—to economic downturns. Assuming a non-neutral role of space on birth rates, the present study investigates the spatio-temporal evolution (1952–2018) of total fertility rate (TFR) at regional scale in Italy, a country with intense decline of births and enlarged socioeconomic divides between the wealthiest Northern regions and the most disadvantaged Southern regions. A progressive reduction of the traditional North–South fertility divide was observed in Italy since the 1980s with a rapid decline of TFR. Results of descriptive statistics and time series analysis indicate that regional fertility in Italy was increasingly associated with economic downturns. Considering the spatial response of birth rates to economic expansions and recessions, heterogeneous regional fertility trends underlie more individualistic behaviors that reflect a different propensity to childbearing in recent times. With both expansion and recession, fertility rates in Northern Italy—thanks to the contribution of internal and international migrations—were responding more rapidly to economic downturns than in Southern Italy—a disadvantaged region with a more stagnant population, emigration and aging, reverting the typical framework of the 1950s. [ABSTRACT FROM AUTHOR]