The Impact of Gray-Listing on Capital Flows : An Analysis Using Machine Learning - Kida, Mizuho; Paetzold, Simon (Washington, D.C. : International Monetary Fund, 2021)
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.
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Keywords: Capital Flows and Emerging Market Economies; Foreign Exchange; Inferential Machine Learning Technique; Informal Economy; Underground Econom