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Forecasting Economic Recession in Selected African Countries using Machine Learning Algorithms.

Makinde, Adeniyi Peter (2019) Forecasting Economic Recession in Selected African Countries using Machine Learning Algorithms. Masters thesis, Dublin, National College of Ireland.

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Abstract

The Author uses Machine learning approaches to classify through careful variable analysis the likelihood of a recession. Four algorithms are modelled on a data set of Financial and macro-economic variables of African economies. Results show that price level of capital stock (Stock index), real consumption plus investment, employment level, capital stocks are core variables with high predictive power of recession in African economies. Out of the four variables, Random forest outperforms with minimal misclassification error rate.
Keywords- Recession; forecasting model; Naïve Bayes; logistic regression; random forest; probit; financial indicators.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software

H Social Sciences > HC Economic History and Conditions > Economic Recession
Divisions: School of Computing > Master of Science in FinTech
Depositing User: Dan English
Date Deposited: 03 Jun 2020 10:37
Last Modified: 03 Jun 2020 10:37
URI: http://trap.ncirl.ie/id/eprint/4229

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