Temporal Consistency of Forecasts and Data Releases

Constantin Bürgi and Julio L. Ortiz

No 202207, Working Papers from School of Economics, University College Dublin

Abstract: We provide key insights on expectation formation based on the Bloomberg eco- nomic survey: around two thirds of professional forecasters provide GDP forecasts that are temporally consistent, meaning that quarterly forecasts add up to the annual. Temporally consistent forecasts are not more accurate than the inconsistent ones, but inconsistent ones might drive estimates of information frictions in some cases. For the overwhelming majority of consistent forecasts, annual GDP predictions almost imme- diately reflect the monthly GDP releases. These findings suggest that most forecasters make at least minor forecast updates after each data release. Indeed, the inattention rate is found to be between 3% and 6% at the quarterly frequency.

Keywords: Temporal forecast reconciliation; Temporal aggregation; Bloomberg survey; GDP; Forecast accuracy (search for similar items in EconPapers)
JEL-codes: E37 (search for similar items in EconPapers)
Pages: 14 pages
Date: 2022-02
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