Version 1
: Received: 30 December 2023 / Approved: 2 January 2024 / Online: 3 January 2024 (02:02:36 CET)
How to cite:
Resta, E.; Resta, O.; Costantiello, A.; Leogrande, A. Investigating the Determinants of Beds for High-Care Specialties in the Italian Regions in the Environmental, Social and Governance Model. Preprints2024, 2024010031. https://doi.org/10.20944/preprints202401.0031.v1
Resta, E.; Resta, O.; Costantiello, A.; Leogrande, A. Investigating the Determinants of Beds for High-Care Specialties in the Italian Regions in the Environmental, Social and Governance Model. Preprints 2024, 2024010031. https://doi.org/10.20944/preprints202401.0031.v1
Resta, E.; Resta, O.; Costantiello, A.; Leogrande, A. Investigating the Determinants of Beds for High-Care Specialties in the Italian Regions in the Environmental, Social and Governance Model. Preprints2024, 2024010031. https://doi.org/10.20944/preprints202401.0031.v1
APA Style
Resta, E., Resta, O., Costantiello, A., & Leogrande, A. (2024). Investigating the Determinants of Beds for High-Care Specialties in the Italian Regions in the Environmental, Social and Governance Model. Preprints. https://doi.org/10.20944/preprints202401.0031.v1
Chicago/Turabian Style
Resta, E., Alberto Costantiello and Angelo Leogrande. 2024 "Investigating the Determinants of Beds for High-Care Specialties in the Italian Regions in the Environmental, Social and Governance Model" Preprints. https://doi.org/10.20944/preprints202401.0031.v1
Abstract
In the following article, it is presented an investigation of the determinants of Beds for High-Care Specialties-BHCS in the Italian regions in the context of Environmental, Social and Governance-ESG approach. Data from ISTAT-BES for 20 countries in the period 2004-2021 are been used. Different econometric techniques have been applied i.e.: Pooled Ordinary Least Squares, Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel at 1 stage. Furthermore, a cluster analysis performed with a k-Means algorithm optimized with the Silhouette Coefficient indicated the presence of three clusters. Finally, eight different machine-learning algorithms are analysed to predict the future value of BHCS. The results show that the Artificial Neural Network-ANN algorithm is the best algorithm. The future value of BHSC is expected to growth on average of 4.88% for the analysed regions.
Keywords
Analysis of Health Care Markets; Health Behaviors; Health Insurance; Public and Private; Health and Inequality; Health and Economic Development; Government Policy; Regulation; Public Health
Subject
Business, Economics and Management, Econometrics and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
