Modeling Judgment in Macroeconomic Forecasts

Philip Hans Franses*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
19 Downloads (Pure)


Many macroeconomic forecasts are the outcome of a judgmental adjustment to a forecast from an econometric model. The size, direction, and motivation of the adjustment are often unknown as usually only the final forecast is available. This is problematic in case an analyst wishes to learn from forecast errors, which could lead to improving the model, the judgment or both. This paper therefore proposes a formal method to include judgment, which makes the combined forecast reproducible. As an illustration, a forecast from a benchmark simple time series model is only modified when the value of a factor, estimated from a multitude of variables, exceeds a user-specified threshold. Simulations and empirical results for forecasting annual real GDP growth in 52 African countries provide an illustration.

Original languageEnglish
Pages (from-to)401-417
Number of pages17
JournalJournal of Quantitative Economics
Early online date9 Nov 2021
Publication statusPublished - Dec 2021

Bibliographical note

Funding Information:
The author is grateful to Olivier Mulkin for research assistance and to two anonymous reviewers for their detailed and very helpful comments.

Publisher Copyright:
© 2021, The Author(s).

Research programs

  • ESL 98-01 capgrp ARW


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