The Rule of Law in the ESG Framework in the World Economy

In this article, I have estimated the Rule of Law for 193 countries using data from the Environment Social and Governance-ESG database of World Bank. I 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. I 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”. I have performed a cluster analysis with the k-Mean algorithm optimized with the Elbow Method and I find the presence of four clusters. Finally, I present a confrontation among eight different machine-learning algorithms to predict the level of Rule of Law. I find that Linear Regression is the best predictor according to MAE, MSE, RMSE and R-squared.