The Regulatory Quality and ESG Model at World Level

Alberto Costantiello () and Angelo Leogrande

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Abstract: In this article, we analyse the determinants of Regulatory Quality-RQ for 193 countries in the period 2011-2020. We use a database from ESG-Environment Social Governance of the World Bank. We apply OLS, Panel Data with Fixed Effects and Panel Data with Random Effects. We found that the variables that have the most positive impact on RQ, among others, are "GHG Net Emission", "Mean Drought Index", and "Heat Index". We also found that the variables that have the most negative impact on RQ are among others "Renewable Energy Consumption", "Voice and Accountability" and "Rule of Law". Furthermore, we have applied the k-Means algorithm optimized with the Elbow Method and we find the presence of five clusters. In adjunct, we confront eight machine learning algorithms to predict the value of RQ and we found that the best predictor is Polynomial Regression. The predictive level of RQ for the analysed countries is expected to diminish of-1,29%. In the end, we present a network analysis with the Euclidean distance and we found the presence of a structure of seven networks using augmented data.

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 JEL Classification: D7 D70 D72 D73 D78; 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 JEL Classification: D7; D70; D72; D73; D78 (search for similar items in EconPapers)
Date: 2023-03-14
New Economics Papers: this item is included in nep-des
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Citations: View citations in EconPapers (6)

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Working Paper: The Regulatory Quality and ESG Model at World Level (2023)
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