Testing bias in professional forecasts

Philip Hans Franses*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)


Professional forecasters can rely on econometric models, on their personal expertise or on both. To accommodate for adjustments to model forecasts, this paper proposes to use two stage least squares (TSLS) (and not ordinary least squares [OLS]) for the familiar Mincer–Zarnowitz regression when examining bias in professional forecasts, where the instrumental variable is the consensus forecast. An illustration for 15 professional forecasters with their quotes for real gross domestic product (GDP) growth, inflation and unemployment for the United States documents the usefulness of this new estimation method. It also shows that TSLS suggests less bias than OLS does.

Original languageEnglish
Pages (from-to)1086-1094
Number of pages9
JournalJournal of Forecasting
Issue number6
Publication statusPublished - Sept 2021

Bibliographical note

Publisher Copyright:
© 2021 The Author. Journal of Forecasting published by John Wiley & Sons Ltd.


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