This paper adopts a spatial econometric methodology to investigate the relationship between income and direct household emissions in Italy, as posited by the environmental Engel curve. The spatial approach is motivated by an expanding strand of studies that have detected significant spatial interactions in household‐polluting activities responsible for the generation of direct household emissions. Our results suggest the presence of significant spatial dependence for household emissions emerging among regions. At the same time, increases in the level of income do not seem to be coupled with a higher demand for environmental quality by Italian households.
This paper investigates the determinants of smart energy tracking app usage by citizens residing in French cities. Our framework is inspired by the extant strands of literature on smart cities and smart home technology adoption, but also contributing to them as smart energy applications reveal specificities that need to be incorporated; the latter include, for instance, the distinction between adoption and frequency of use, or the consideration of additional determinants such as privacy or environmental concerns. For our study, we build an original survey and rely upon citizen-level data, testing a Zero-Inflated Ordered Probit (ZIOP) model which allows to differentiate between adoption of the smart energy app and its frequency of utilisation. Our empirical findings reveal how the drivers related to smart city characteristics mainly affect the decision of adoption of energy tracking apps. Conversely, the more individual characteristics related to the perceived benefits of using energy tracking apps, dwelling type, and privacy concerns, primarily affect the frequency of utilisation. Our results bear policy implications on the issue of privacy, premising additional research on energy challenges in the utilization of energy apps in smart versus non-smart environments.
This paper aims to analyze the increasing issue of overcongestion affecting the immigration hosting facilities of many Italian municipalities, as well as the heterogeneity in immigration regulatory behavior emerging among the latter. Since 2014, the immigration rate in Italy has tripled and the redistribution process of immigrants among municipalities has increased in a sustained manner. Municipalities receive financial subsidies from the central government for hosting immigrants; at the same time, many of them have been experiencing a series of rigidities in the form of complaints by both firms and local residents when having to modify their desired rate of immigrant arrivals. I introduce an intertemporal dynamic framework where a municipal authority rationally maximizes its utility from allowing immigrants to relocate to its jurisdiction, while considering the disutility cost of rigidities and the negative repercussions of having a congestion level of its hosting facilities different from the optimal one. From the model, two major findings emerge. Firstly, the optimal congestion level for a municipality always corresponds to a situation of overcongestion. Secondly, even though the level of rigidities does not affect the steady-state level, it does affect the process of convergence towards it, resulting in either monotonic or oscillating paths of convergence.
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