The Impact of Government Expenditure on Education in the ESG Models at World Level

Angelo Leogrande and Alberto Costantiello ()

No 4wctx, SocArXiv from Center for Open Science

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.

Date: 2023-05-04
New Economics Papers: this item is included in nep-env
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: The Impact of Government Expenditure on Education in the ESG Models at World Level (2023)
Working Paper: The Impact of Government Expenditure on Education in the ESG Models at World Level (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:4wctx

DOI: 10.31219/osf.io/4wctx

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