Data revisions in the estimation of DSGE models

Abstract

Revisions of US macroeconomic data are not white-noise. They are persistent, correlated with real-time data, and with high variability (around 80% of volatility observed in US real-time data). Their business cycle effects are examined in an estimated DSGE model that distinguishes real-time data from final data. Both the consumption habit formation and the price indexation to lagged inflation fall significantly in the estimation. The model also shows that revision shocks of both output and inflation are expansionary because they occur when real-time published data are too low and the Fed reacts by cutting interest rates. Consumption revisions, by contrast, are countercyclical as consumption habits mirror the observed reduction in real-time consumption. Finally, revisions of the three variables explain 9.3% of changes of output in its long-run variance decomposition.

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