Overcoming Data Sparsity: A Machine Learning Approach to Track the Real-Time Impact of COVID-19 in Sub-Saharan Africa
Download or Read eBook Overcoming Data Sparsity: A Machine Learning Approach to Track the Real-Time Impact of COVID-19 in Sub-Saharan Africa PDF written by Karim Barhoumi and published by International Monetary Fund. This book was released on 2022-05-06 with total page 23 pages. Available in PDF, EPUB and Kindle.
| Author | : Karim Barhoumi |
| Publisher | : International Monetary Fund |
| Total Pages | : 23 |
| Release | : 2022-05-06 |
| ISBN-10 | : 9798400210136 |
| ISBN-13 | : |
| Rating | : 4/5 (36 Downloads) |
Book Synopsis Overcoming Data Sparsity: A Machine Learning Approach to Track the Real-Time Impact of COVID-19 in Sub-Saharan Africa by : Karim Barhoumi
Book excerpt: 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.
