News, noise, and fluctuations : an empirical exploration

We explore empirically models of aggregate fluctuations with two basic ingredients: agents form anticipations about the future based on noisy sources of information and these anticipations affect spending and output in the short run. Our objective is to separate fluctuations due to actual changes in fundamentals (news) from those due to temporary errors in agents' estimates of these fundamentals (noise). We use a simple forward-looking model of consumption to address some methodological issues: structural VARs cannot be used to identify news and noise shocks in the data, but identification is possible via a method of moments or maximum likelihood. Next, we use U.S. data to estimate both our simple model and a richer DSGE model with the same information structure. Our estimates suggest that noise shocks play an important role in short-run consumption fluctuations. -- Aggregate shocks ; business cycles ; vector autoregression ; invertibility