The ESG Determinants of Mental Health Index Across Italian Regions: A Machine Learning Approach

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

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Year of publication:	2024-06-14
Authors:	Resta, Emanuela ; Logroscino, Giancarlo ; Tafuri, Silvio ; Peter, Preethymol ; Noviello, Chiara ; Costantiello, Alberto ; Leogrande, Angelo

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Type of publication:	Book / Working Paper
Language:	English
Notes:	Resta, Emanuela and Logroscino, Giancarlo and Tafuri, Silvio and Peter, Preethymol and Noviello, Chiara and Costantiello, Alberto and Leogrande, Angelo (2024): The ESG Determinants of Mental Health Index Across Italian Regions: A Machine Learning Approach.
Classification:	I11 - Analysis of Health Care Markets ; I12 - Health Production: Nutrition, Mortality, Morbidity, Substance Abuse and Addiction, Disability, and Economic Behavior ; i13 ; i14 ; i15 ; I18 - Government Policy; Regulation; Public Health
Source:	BASE

Persistent link: https://www.econbiz.de/10015213593