Temporal Consistency of Forecasts and Data Releases

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Title: Temporal Consistency of Forecasts and Data Releases
Authors: Bürgi, ConstantinOrtiz, Julio L.
Permanent link: http://hdl.handle.net/10197/12780
Date: 11-Feb-2022
Online since: 2022-02-28T16:58:26Z
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.
Type of material: Working Paper
Publisher: University College Dublin. School of Economics
Start page: 1
End page: 14
Series/Report no.: UCD Centre for Economic Research Working Paper Series; WP2022/07
Copyright (published version): 2022 the Authors
Keywords: Temporal forecast reconciliationTemporal aggregationBloomberg surveyGDPForecast accuracy
JEL Codes: E37
Language: en
Status of Item: Not peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Economics Working Papers & Policy Papers

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