The efficiency of multivariate macroeconomic forecasts

Bruno Deschamps, Christos Ioannidis

Research output: Contribution to journalArticlepeer-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 pages13
JournalManchester School
Issue number5
Early online date6 Jan 2014
Publication statusPublished - 30 Sept 2014


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