Machine Learning and Causality: The Impact of Financial Crises on Growth
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Summary:
Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal discovery is at the core of most questions concerning economic policy. Recently, however, the literature has focused more on issues of causality. This paper gently introduces some leading work in this area, using a concrete example—assessing the impact of a hypothetical banking crisis on a country’s growth. By enabling consideration of a rich set of potential nonlinearities, and by allowing individually-tailored policy assessments, machine learning can provide an invaluable complement to the skill set of economists within the Fund and beyond.
Series:
Working Paper No. 2019/228
Subject:
Exchange rate flexibility Financial crises Foreign exchange Machine learning Technology
English
Publication Date:
November 1, 2019
ISBN/ISSN:
9781513518305/1018-5941
Stock No:
WPIEA2019228
Pages:
30
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