Template-Type: ReDIF-Paper 1.0
Author-Name: Franses, Ph.H.B.F.
Author-Name-Last: Franses
Author-Name-First: Philip Hans
Author-Person: pfr226
Title: Professional Forecasters and January
Abstract: Each month various professional forecasters give forecasts for next year's real GDP growth and
 many other variables. In terms of forecast updates, January is a special month, as then the
 forecast horizon moves to the following calendar year, and as such the observation is not a
 revision. Instead of deleting the January data when analyzing forecast updates, this paper
 proposes a periodic version of an often considered test regression, to explicitly include and
 model the January data. An application of this periodic model for many forecasts across a range
 of countries learns that apparently there is a January optimism effect. In fact, in January, GDP
 forecast updates are suddenly positive, and at the same time the forecast updates for
 unemployment are likewise negative. This optimism about the new year of the professional
 forecasters is however found to be detrimental to forecast accuracy. The main conclusion is that
 forecasts created in January for the next year need to be treated with care.
Length: 19
Creation-Date: 2019-07-01
File-URL: https://repub.eur.nl/pub/118666/EI2019-25-Report.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI2019-25
Classification-JEL: C53, E27, E37
Keywords: Professional forecasters, macroeconomic forecasting, weak-form efficiency, periodic, regression model, forecast updates, January effect
Handle: RePEc:ems:eureir:118666