The Impact of Gray-Listing on Capital Flows: An Analysis Using Machine Learning
Author/Editor: Mizuho Kida, Simon Paetzold
Release Date: © May, 2021
ISBN
: 978-1-51358-662-5
Stock #: WPIEE2021153
English
Languages and formats available
| English | French | Spanish | Arabic | Russian | Chinese | Portuguese | |
| Paperback | Yes | ||||||
| Yes | |||||||
| ePub | Yes |
Description
The Financial Action Task Force's gray list publicly identifies countries with strategic deficiencies in their AML/CFT regimes (i.e., in their policies to prevent money laundering and the financing of terrorism). How much gray-listing affects a country's capital flows is of interest to policy makers, investors, and the Fund. This paper estimates the magnitude of the effect using an inferential machine learning technique. It finds that gray-listing results in a large and statistically significant reduction in capital inflows.
More publications in this series: Working Papers
More publications by: Mizuho Kida ; Simon Paetzold
