Overcoming Data Sparsity: A Machine Learning Approach to Track the Real-Time Impact of COVID-19 in Sub-Saharan Africa
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Summary:
The COVID-19 crisis has had a tremendous economic impact for all countries. Yet, assessing the full impact of the crisis has been frequently hampered by the delayed publication of official GDP statistics in several emerging market and developing economies. This paper outlines a machine-learning framework that helps track economic activity in real time for these economies. As illustrative examples, the framework is applied to selected sub-Saharan African economies. The framework is able to provide timely information on economic activity more swiftly than official statistics.
Series:
Working Paper No. 2022/088
Subject:
COVID-19 Economic forecasting Foreign exchange Health Machine learning Oil prices Prices Real effective exchange rates Technology
Frequency:
regular
English
Publication Date:
May 6, 2022
ISBN/ISSN:
9798400210136/1018-5941
Stock No:
WPIEA2022088
Pages:
23
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