The Impact of Voice and Accountability in the Esg Framework in a Global Perspective

Abstract

We estimate the value of Voice and Accountability-VA in the context of the Environmental, Social and Governance-ESG data of the World Bank using data from 193 countries in the period 2011-2021. We use Panel Data with Fixed Effects, Panel Data with Random Effects and Pooled Ordinary Least Squares-OLS. We found that the level of VA is positively associated, among others, to “Maximum 5-Day Rainfall”, and “Mortality Rate Under 5” and negatively associated, among others, to “Adjusted Savings: Natural Resources Depletion”, and “Annualized Average Growth Rate in Per Capita Real Survey Mean Consumption or Income”. Furthermore, we apply the k-Means algorithm optimized with the Elbow Method. We found the k-Means useless due to the low variance of the variable among countries with the result of a hyper-concentration of elements in a unique cluster. Finally, we confront eight machine-learning algorithms for the prediction of VA. Polynomial Regression is the best predictive algorithm according to R-Squared, MAE, MSE and RMSE. The level of VA is expected to growth on average of 2.92% for the treated countries.