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Understanding Over-Optimism in Tax Revenue-to-GDP Forecasts under IMF-supported Programs

Author

Listed:
  • Jean-Marc Atsebi
  • Qiaoe Chen
  • Nikolay Gueorguiev
  • Magali Pinat

Abstract

Revenue mobilization is a key objective in many IMF-supported programs, yet tax revenue-to-GDP forecasts often fall short of outcomes. This paper analyzes the underlying drivers of these forecast misses by leveraging two novel global datasets on tax policy yields and tax administration capacity. It finds that tax revenue-to-GDP forecast errors are primarily driven by over-optimism in forecasted yields of tax policy measures and tax buoyancy assumptions, as well as macroeconomic forecast errors, particularly for growth and trade openness. Stronger tax administration capacity and well-implemented and high-quality revenue related structural reforms are associated with lower forecast errors. Additional empirical analysis shows that over-optimism in forecasted tax policy yields declines significantly when revenue measures are well-designed, part of large-measure revenue packages, and accompanied by high-quality revenue-related structural reforms. Improving forecast realism requires better-grounded yield estimations and tax buoyancy assumptions, explicit consideration of implementation capacity, and a focus on well-designed revenue-related structural reforms.

Suggested Citation

  • Jean-Marc Atsebi & Qiaoe Chen & Nikolay Gueorguiev & Magali Pinat, 2026. "Understanding Over-Optimism in Tax Revenue-to-GDP Forecasts under IMF-supported Programs," IMF Working Papers 2026/224, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:2026/224
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