Total Factor Productivity
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Differing Roles of Leisure and Productivity in GDP - A Machine Learning based comparative analysis of Germany and USA
Announce Type: cross Abstract: The GDP of a country is modelled as the relative interaction between two agents - working hours, reflecting the social choice of a population, and Total Factor Productivity, reflecting the collective investment in productivity enhancers. It is shown that a Random Forest model can accu- rately predict the GDP from these two factors. The differences in the choices made by Germany and USA are analysed though Gini importance, SHAP plots and partial dependency.
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