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A Narrative Fiscal Consolidation Dataset for Sub-Saharan Africa

Author

Listed:
  • Hany Abdel-Latif
  • Khalil Bechchani
  • Mr. Antonio David
  • Thibault Lemaire

Abstract

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.

Suggested Citation

  • Hany Abdel-Latif & Khalil Bechchani & Mr. Antonio David & Thibault Lemaire, 2026. "A Narrative Fiscal Consolidation Dataset for Sub-Saharan Africa," IMF Working Papers 2026/011, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2026/011
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