Text-Mining IMF Country Reports – An Original Dataset
29 Pages Posted: 10 Nov 2018 Last revised: 14 Aug 2019
Date Written: August 13, 2019
This article introduces an original panel dataset based on the text of country reports by the International Monetary Fund. It consists of a total of 5561 Article IV consultation and program review documents, published between 2004 and 2018 on 201 countries. The text of these reports provide indications of the perceived policy weaknesses, economic risks, ongoing reforms and implemented or neglected policy advice. Thus the content of IMF reports are widely used in the economics, political science and IR literature. To our knowledge this is the first comprehensive dataset that aggregates these country reports.
The paper gives a detailed account on the data acquisition and management process. To demonstrate and validate the dataset's application for research we present three validation exercises. We find that Article IV reports can indicate incoming institutional reforms, show changes in IMF policy advice over time and identify potential gains from recently discovered natural resources in certain cases. Taken together, this paper contributes an original dataset of IMF country reports and demonstrates how it can be a useful foundation for further research into the role of international financial institutions.
Keywords: economic policy, IMF, text analytics, original dataset
JEL Classification: E60, F53
Suggested Citation: Suggested Citation