Author(s): Alberto Costantiello, Angelo Leogrande
In this article we analyze the impact of Labor Force Partecipation Rate-LFPR in the context of the Environmental, Social and Governance-ESG model at world level. We use data from the ESG dataset of the World Bank for the period 2011-2020. We use Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, Dynamic Panel. We find that the level of LFPR is positively associated among others to “Ratio of Female to Male Labor Force Participation Rate” and “Life Expectancy at Birth”, and negatively associated among others, to “Unemployment” and “Agricultural Land”. Furthermore, we have applied a clusterization with the k-Means algorithm optimized with the Silhouette coefficient, and we found the presence of three clusters. Finally, we confront eight different machine learning algorithms to predict the value of LFPR. We find that the best predictor is the Linear Regression. Linear Regression predicts an increase in LFPR equal to 0.42% on average for the analyzed countries.