Abstract
There are various reasons why professional forecasters may disagree in their quotes for macroeconomic variables. One reason is that they target at different vintages of the data. We propose a novel method to test forecast bias in case of such unobserved heterogeneity. The method is based on so-called symbolic regression, where the variables of interest become interval variables. We associate the interval containing the vintages of data with the intervals of the forecasts. An illustration to 18 years of forecasts for annual US real GDP growth, given by the Consensus Economics forecasters, shows the relevance of the method.
Original language | English |
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Pages (from-to) | 829-839 |
Number of pages | 11 |
Journal | Journal of Forecasting |
Volume | 41 |
Issue number | 4 |
Early online date | 2 Dec 2021 |
DOIs | |
Publication status | Published - Jul 2022 |
Bibliographical note
JEL Code: C53Funding Information:
We thank two anonymous reviewers for their detailed and helpful comments.
Publisher Copyright:
© 2021 The Authors. Journal of Forecasting published by John Wiley & Sons Ltd.