Version 1
: Received: 10 April 2023 / Approved: 11 April 2023 / Online: 11 April 2023 (08:53:07 CEST)
How to cite:
Costantiello, A.; Leogrande, A. The Impact of Research and Development Expenditures on ESG Model in the Global Economy. Preprints2023, 2023040216. https://doi.org/10.20944/preprints202304.0216.v1
Costantiello, A.; Leogrande, A. The Impact of Research and Development Expenditures on ESG Model in the Global Economy. Preprints 2023, 2023040216. https://doi.org/10.20944/preprints202304.0216.v1
Costantiello, A.; Leogrande, A. The Impact of Research and Development Expenditures on ESG Model in the Global Economy. Preprints2023, 2023040216. https://doi.org/10.20944/preprints202304.0216.v1
APA Style
Costantiello, A., & Leogrande, A. (2023). The Impact of Research and Development Expenditures on ESG Model in the Global Economy. Preprints. https://doi.org/10.20944/preprints202304.0216.v1
Chicago/Turabian Style
Costantiello, A. and Angelo Leogrande. 2023 "The Impact of Research and Development Expenditures on ESG Model in the Global Economy" Preprints. https://doi.org/10.20944/preprints202304.0216.v1
Abstract
We estimate the value of Research and Development Expenditures as a percentage of GDP-RDE in the context of Environmental, Social and Governance-ESG model. We use the ESG World Bank database. We analyze data from193 countries in the period 2011-2020. We apply a set of econometric techniques i.e. Pooled Ordinary Least Squares-OLS, Panel Data with Random Effects, Panel Data with Fixed Effects, Weighted Least Squares-WLS. We found that the level of RDE is positively associated, among others, to “Nitrous Oxide Emissions” and “Scientific and Technical Journal Articles”, and negatively associated, among others to “Heat Index 35”, “Maximum 5-day Rainfall”. Furthermore, we perform a cluster analysis with the application of the k-Means algorithm optimized with the Elbow Method. The results show the presence of four clusters. Finally, we confront eight different machine-learning algorithms to predict the future value of RDE. We find that Linear Regression is the best predictive algorithms. RDE is expected to growth on average of 0.07% for the analysed countries.
Keywords
Analysis of Collective Decision-Making; General; Political Processes: Rent-Seeking; Lobbying; Elections; Legislatures; and 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.
