A Narrative Fiscal Consolidation Dataset for Sub-Saharan Africa

Author: Hany Abdel-Latif, Khalil Bechchani, Mr. Antonio David, and Thibault Lemaire

Volume/Issue: Volume 2026 Issue 011

Publication date: January 2026

ISBN: 9798229034661

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Topics covered in this book

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Exports and Imports , Economics- Macroeconomics , Public Finance , Fiscal consolidation , Fiscal policy , Narrative identification , Sub-Saharan Africa , Artificial intelligence methods , Imf working papers , narrative fiscal consolidation dataset , fiscal consolidation action , views of the International Monetary Fund , Hany Abdel-Latif , Fiscal stance , Africa , Middle East , Southeast Asia , North Africa

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WORKING PAPERS PUBLISHED IN JULY 2007

WORKING PAPERS PUBLISHED IN MAY 2004

WORKING PAPERS PUBLISHED IN JUNE 2003

WORKING PAPERS PUBLISHED IN JUNE 2004

Summary

This paper introduces the first narrative-based dataset on fiscal consolidations for sub-Saharan Africa (SSA). Drawing on staff reports from the International Monetary Fund (IMF) during the period 1990-2024 and using an approach assisted by artificial intelligence (AI), the dataset systematically identifies fiscal consolidation actions motivated by long-term considerations (rather than cyclical conditions), such as reducing an inherited budget deficit, ensuring long-term public debt sustainability and improving economic efficiency. By focusing exclusively on measures exogenous to the business cycle, the dataset provides a more precise identification of fiscal consolidation actions for the empirical analysis of the macroeconomic effects of fiscal policy in SSA.