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Lumpy Forecasts

Author

Listed:
  • Javier Turen
  • Isaac Baley

Abstract

Professional forecasters adjust their inflation forecasts in a distinctly lumpy pattern, making infrequent but substantial revisions. Strategic concerns play a significant role—forecasters are more likely to adjust, and by larger amounts, when their forecasts deviate from the consensus. Using a fixed-event forecasting framework, we document the impact of lumpiness and consensus pressure on forecast adjustments. Our quantitative model, which integrates Bayesian belief updating with forecast revision costs and strategic concerns, not only replicates the observed lumpiness in survey data but also sheds light on forecasters' apparent overreactions to new information. This structured framework enables us to "cleanse" forecasts, isolating the underlying inflation beliefs that drive these forecasts.

Suggested Citation

  • Javier Turen & Isaac Baley, 2025. "Lumpy Forecasts," Working Papers 1476, Barcelona School of Economics.
    • Handle: RePEc:bge:wpaper:1476
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    More about this item

    Keywords

    consensus.; forecasting; overreaction; ï¬ xed-event forecasts; Bayesian learning; strategic concerns; forecast stability; forecast revision costs;
    All these keywords.

    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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