Search

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]

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]

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]