The Rule of Law in the Environmental, Social and Governance Framework in the World Economy

Abstract

Abstract In this article, we have estimated the Rule of Law for 193 countries using data from the Environmental, Social and Governance-ESG database of World Bank. We have used different econometric techniques to estimate the value of “Rule of Law” i.e.: Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS. We found that Rule of Law is positively associated, among others to “Regulatory Quality” and “Control of Corruption” and negatively associated among others to, “Access to Electricity” and “Prevalence of Overweight”. We have performed a cluster analysis with the k-Mean algorithm optimized with the Elbow Method and we find the presence of four clusters. Finally, we present a confrontation among eight different machine-learning algorithms to predict the level of Rule of Law. We find that Linear Regression is the best predictor according to MAE, MSE, RMSE and R-squared. JEL CODE: D7, D70, D72, D73, D78.