|Tipo di tesi||Tesi di laurea magistrale|
|Autore||D'ECCLESIIS, ENRICO ANGELO RAFFAELE|
|Titolo||L’Angelo Sterminatore? Uno studio di model selection delle attitudini sul Cambiamento Climatico e le relative politiche in Europa|
|Titolo in inglese||The Exterminating Angel? A model selection study on Climate Change’s and related policies’s attitudes in Europe|
|Struttura||Dipartimento di Economia "Marco Biagi"|
|Corso di studi||Economia e politiche pubbliche (D.M.270/04)|
|Data inizio appello||2021-07-29|
|Disponibilità||Accessibile via web (tutti i file della tesi sono accessibili)|
La tesi si inserisce nella letteratura di Political Economy legata alle questioni ambientali e dei cambiamenti climatici con un approccio empirico.
The thesis is inserted in the Political Economy literature linked to environmental issues and climate change with an empirical approach. With reference to the European case, through the data provided by the European Social Survey "ESS" Round 8 of 2016, awareness of climate change and opinions on policies aimed at combating them are analyzed. To study the role of different socio-economic characteristics (income, education, age, etc.) and various personal attributes (values, preferences, trust, religion, etc.), some synthetic indices are defined that represent preferences and opinions on climate change: people's awareness to climate change, people's attention to take actions to protect the environment, the willingness of individuals to pass from a less dependence on oil through the use of renewable energy, insecurity towards the national energy situation, trust in possible activities private and public to protect the climate and support for public policies concerning climate change. To select the best explaining models, both computational selection procedures based on information criteria and theoretical criteria driven from a careful analysis of the climate literature are used. Following the same procedure, in the last part of the paper, political preferences towards environmental parties are also analyzed. The large number of starting variables available in the database, with respect to independent variables, controls and individual characteristics, allows us to review the results of the literature and to open up new directions for research.