Non-Performing Loans and Macroeconomics Factors: The Italian Case

The purpose of this work is to investigate the influence of macroeconomics determinants on non-performing loans (NPLs) in the Italian banking system over the period 2008Q3–2020Q4. We mainly contribute to the literature by being the first empirical article to study this relationship in the Italian context in the recent period, thus providing fresh evidence on the macroeconomic impact on NPLs, i.e., on the credit risk of Italian banks. By employing the Autoregressive Distributed Lag (ARDL) cointegration model, we are able to investigate the short and long-run effects of macroeconomic factors on NPLs. The empirical findings show that gross domestic product and public debt have a negative impact on NPLs. On the other hand, we find that the unemployment rate and domestic credit positively influence impaired loans. Finally, we find evidence of the “gamble for resurrection” approach, i.e., Italian banks tend to support “zombie firms”.

Smart Cities and Sustainability

The term smart city is often synonymous with a sustainable city. The word smart implies the use of digital technology that serves to make processes and services more efficient and to connect the different actors on the urban scene. However, this is no guarantee of sustainability. A city can become sustainable if it changes its metabolism and from linear to circular as in nature's ecosystems. For this to happen, it is necessary to overcome the paradigm of quantitative economic growth based on the infinite substitutability between natural and economic capital. If smart city governance stakeholders primarily pursue profit according to the logic of the free market, the city may be smarter and efficient in the use of energy and resources, but it is not sustainable, often not even inclusive. The challenge of sustainability implies a paradigm shift and the use of digital technologies at the service of the collective good. In this context, after a general analysis of the characteristics of smart cities, the chapter focuses on an Italian case study, Turin Smart City.

Long-term relationship estimation and coupling/decoupling analysis between motorway traffic and Gross Value Added. Specification of an ARDL cointegration approach and application to the Italian case study

As transportation is an activity derived from spatial complementarities between a certain supply at an origin and a certain demand at a destination, according to a general axiom it seems that economic activities entail transport de-mand. In this perspective, an essential analysis deals with the quantification of the relationships between transport demand and certain socioeconomic variables. Elasticity is a concept widely used in transport economics as a measure of the responsiveness of transport demand concerning different factors represented as independent variables in an econometric model and coupling/decoupling concepts have been proposed in literature. This paper deals with the estimation of elasticities of motorway traffic demand based on Gross Value Added (GVA), and the consequent investiga-tion of coupling/decoupling situation. The analysis is based on the application of an Autoregressive-Distributed Lag (ARDL) cointegration model with the F-bound test and of the related Error Correction model. Starting from the general ARDL model and the methodology for the verification of its robustness, the same model is applied to the Italian toll road network. The time series of GVA for goods and services and the overall length of the toll network from 1995 to 2019 are considered as explanatory variables of the total annual distance traveled by light and heavy vehicles. The various tests in the ARDL framework show a cointegration between the variables, under the fulfillment of all the diag-nostic requirements. In this way, the long-term elasticities and the short-term adjustment dynamics are estimated sepa-rately for the goods and services components of GVA, and light and heavy vehicles. Starting from stable estimates of elasticities, the long-term coupling and decoupling effects between motorway traffic of light and heavy vehicles and the national production of goods and services can be shown. The paper, as well as providing an updated picture of the Italian situation, identifies a methodological framework that can be transferred to other contexts for a sector of great interest to investors, such as the motorway sector. All this can be useful to meet the needs of numerous stakeholders, who want to deepen the links between the economic cycle and traffic demand on toll motorways.

The Social and Health Impact of Accidents at Work: The Analysis of the Italian Case

The months of a gradual exit from the pandemic show some significant data and phenomena regarding the phenomenon of accidents at work and occupational diseases. The Italian figure highlights a recovery in injuries and illnesses, but also in the impact of new risk factors deriving from the digitalization of work, which grew with smart working during the pandemic. At the same time, the new organizational models highlight the increased risk of work-related stress diseases. The Italian situation makes clear the need to intervene on the issue of organizational well-being and welfare, to limit the negative impact of risk factors associated with this economic system on society and the health system through a new work culture.

Assessment of the Impacts of Climate Change on Power Systems: The Italian Case Study

Climate change due to the greenhouse effect will affect meteorological variables, which in turn will affect the demand for electrical energy and its generation in coming years. These impacts will become increasingly important in accordance with the increasing penetration of renewable, non-programmable energy sources (e.g., wind and solar). Specifically, the speed and amplitude of power system transformation will be different from one country to another according to many endogenous and exogenous factors. Based on a literature review, this paper focuses on the impact of climate change on the current, and future, Italian power system. The paper shows a wide range of results, due not just to the adopted climate change models used, but also to the models used to assess the impact of meteorological variables on electricity generation and demand. Analyzing and interpreting the reasons for such differences in the model results is crucial to perform more detailed numerical analyses on the adequacy and reliability of power systems. Concerning Italian future scenarios, the double impact of uncertainties in national policies and changes in power plant productivity and demand, has been considered and addressed.

How political choices shaped Covid connectivity: The Italian case study

The importance of implementing new methodologies to study the ever-increasing amount of Covid-19 data is apparent. The aftermath analysis of these data could inform us on how specific political decisions influenced the dynamics of the pandemic outbreak. In this paper we use the Italian outbreak as a case study, to study six different Covid indicators collected in twenty Italian regions. We define a new object, the Covidome, to investigate the network of functional Covid interactions between regions. We analyzed the Italian Covidome over the course of 2020, and found that Covid connectivity between regions follows a sharp North-South community gradient. Furthermore, we explored the Covidome dynamics and individuated differences in regional Covid connectivity between the first and second waves of the pandemic. These differences can be associated to the two different lockdown strategies adopted for the first and the second wave from the Italian government. Finally, we explored to what extent Covid connectivity was associated with the Italian geographical network, and found that Central regions were more tied to the structural constraints than Northern or Southern regions in the spread of the virus. We hope that this approach will be useful in gaining new insights on how political choices shaped Covid dynamics across nations.