Predicting the Economic Impact of Post Covid-19 in Sub-Saharan African Countries Using Gradient Boosting

The global economy has faced an unprecedented threat from the COVID-19 outbreak. The current illness is ravaging Africa at an exponential rate, and all of the continent's nations are experiencing the effects of the epidemic. In this study, we used the COVID-19 outbreak as a case study to examine the prediction of the economic impact of the pandemic in Sub-Saharan Africa (SSA). We adopted several models to work on the dataset to compare which one worked best for all 3 target variables and we discovered that Gradient Boosting worked best across all 3 models. We adopted the gradient boosting approach to explain the interaction between economic agents and how the COVID-19 outbreak has affected the relationships between them. The effects of COVID-19 on economic variables were examined using gradient boosting, we discovered that Brand Purchase, Food Amount, and Food Shopping were statistically significant at 5 and 10%, respectively.

We will gauge the financial effect of COVID-19, based on past examinations completed. We figured out that during the covid19, the monetary gamble of this pandemic was high in the more unfortunate pieces of the world (developing countries). We will quantify the post monetary effect of 19 in emerging nations with the guide of pre-pandemic information sources utilizing Gradient Boosting.