Forecasting data vintages

This article provides a discussion of Clements and Galvão’s paper “Forecasting with vector autoregressive models of data vintages: US output growth and inflation.” Clements and Galvão argue that a multiple-vintage VAR model can be useful for forecasting data that are subject to revisions. They draw a “distinction between forecasting future observations and revisions to past data,” which focuses forecasters’ attention on yet another real time data issue. This comment discusses the importance of taking data revisions into consideration, and compares the multiple-vintage VAR approach of Clements and Galvão to a state space approach.