Version 1
: Received: 4 May 2023 / Approved: 5 May 2023 / Online: 5 May 2023 (03:31:39 CEST)
How to cite:
Leogrande, A.; Costantiello, A. The Impact of Government Expenditure on Education in the ESG Models at World Level. Preprints2023, 2023050286. https://doi.org/10.20944/preprints202305.0286.v1
Leogrande, A.; Costantiello, A. The Impact of Government Expenditure on Education in the ESG Models at World Level. Preprints 2023, 2023050286. https://doi.org/10.20944/preprints202305.0286.v1
Leogrande, A.; Costantiello, A. The Impact of Government Expenditure on Education in the ESG Models at World Level. Preprints2023, 2023050286. https://doi.org/10.20944/preprints202305.0286.v1
APA Style
Leogrande, A., & Costantiello, A. (2023). The Impact of Government Expenditure on Education in the ESG Models at World Level. Preprints. https://doi.org/10.20944/preprints202305.0286.v1
Chicago/Turabian Style
Leogrande, A. and Alberto Costantiello. 2023 "The Impact of Government Expenditure on Education in the ESG Models at World Level" Preprints. https://doi.org/10.20944/preprints202305.0286.v1
Abstract
In this article, we estimate the value of Government Expenditure on Education-GEE in the context of Environmental, Social and Governance-ESG dataset of the World Bank. We use data from 193 countries in the period 2011-2020. We use Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled Ordinary Least Squares-OLS, and Weighted Least Squares-WLS. Our results show that the value of GEE is positively associated among others to “Case of Death, by communicable disease and maternal, prenatal and nutrition conditions”, and “Unemployment”, and negatively associated among others to “Hospital Beds” and “Government Effectiveness”. Furthermore, we apply the k-Means algorithm optimized with the Elbow Method and we find the presence of four clusters. Finally, we confront eight machine learning algorithms for the prediction of the future value of GEE. We found that the Polynomial Regression is the best predictive algorithm. The Polynomial Regression predicts an increase in GEE of 7.09% on average for the analysed countries.
Keywords
Analysis of Collective Decision-Making; General; Political Processes: Rent-Seeking; Lobbying; Elections; Legislatures; Voting Behaviour; Bureaucracy; Administrative Processes in Public Organizations; Corruption; Positive Analysis of Policy Formulation; Implementation
Subject
Business, Economics and Management, Economics
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.
