Predicting Early Data Revisions to U.S. GDP and the Effects of Releases on Equity Markets

A-Tier
Journal: Journal of Business & Economic Statistics
Year: 2017
Volume: 35
Issue: 3
Pages: 389-406

Authors (2)

Michael P. Clements (not in RePEc) Ana Beatriz Galvão (University of Warwick)

Score contribution per author:

2.011 = (α=2.01 / 2 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

The effects of data uncertainty on real-time decision-making can be reduced by predicting data revisions to U.S. GDP growth. We show that survey forecasts efficiently predict the revision implicit in the second estimate of GDP growth, but that forecasting models incorporating monthly economic indicators and daily equity returns provide superior forecasts of the data revision implied by the release of the third estimate. We use forecasting models to measure the impact of surprises in GDP announcements on equity markets, and to analyze the effects of anticipated future revisions on announcement-day returns. We show that the publication of better than expected third-release GDP figures provides a boost to equity markets, and if future upward revisions are expected, the effects are enhanced during recessions.

Technical Details

RePEc Handle
repec:taf:jnlbes:v:35:y:2017:i:3:p:389-406
Journal Field
Econometrics
Author Count
2
Added to Database
2026-01-25