The Mental Health Index across the Italian Regions in the ESG Context
Emanuela Resta,
Giancarlo Logroscino (),
Silvio Tafuri (),
Peter Preethymol (),
Chiara Noviello (),
Alberto Costantiello () and
Angelo Leogrande
Additional contact information
Emanuela Resta: Unifg - Università degli Studi di Foggia = University of Foggia
Giancarlo Logroscino: UNIBA - Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro
Chiara Noviello: IC UM3 (UMR 8104 / U1016) - Institut Cochin - INSERM - Institut National de la Santé et de la Recherche Médicale - CNRS - Centre National de la Recherche Scientifique - UPCité - Université Paris Cité
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Abstract:
The following article analyses the relationship between the mental health index and the variables of the Environment, Social and Governance-ESG model in the Italian regions between 2004 and 2023. First of all, a static analysis is proposed aimed at identifying trends relating to mental health in the Italian regions with indication of the regional gaps. Subsequently, a clustering with k-Means algorithm is proposed. Below is a comparison of 11 machine learning algorithms for predicting the performance of the mental health index. Finally, the article offers some economic policy suggestions. The results are critically discussed in light of the scientific literature.
Keywords: ESG Mental Health Index Panel Data Data Analysis. JEL CODE: I11 I12 I13 I14 I15 I18; ESG; Mental Health Index; Panel Data; Data Analysis. JEL CODE: I11; I12; I13; I14; I15; I18 (search for similar items in EconPapers)
Date: 2024-06-14
Note: View the original document on HAL open archive server: https://hal.science/hal-04612739v1
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Working Paper: The Mental Health Index across the Italian Regions in the ESG Context (2024) 
Working Paper: The Mental Health Index across the Italian Regions in the ESG Context (2024) 
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