The efficiency of multivariate macroeconomic forecasts

Bruno Deschamps, Christos Ioannidis

Research output: Journal PublicationArticlepeer-review


We examine the efficiency of multivariate macroeconomic forecasts by estimating a vector autoregressive model on the forecast revisions of four variables (GDP, inflation, unemployment and wages). Using a data set of professional forecasts for the G7 countries, we find evidence of cross-series revision dynamics. Specifically, forecasts revisions are conditionally correlated to the lagged forecast revisions of other macroeconomic variables, and the sign of the correlation is as predicted by conventional economic theory. This indicates that forecasters are slow to incorporate news across variables. We show that this finding can be explained by forecast underreaction.

Original languageEnglish
Pages (from-to)509-523
Number of pages15
JournalManchester School
Issue number5
Publication statusPublished - 1 Sept 2014

ASJC Scopus subject areas

  • Economics and Econometrics


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