Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We explore empirically models of aggregate fluctuations in which consumers form anticipations about the future based on noisy sources of information and these anticipations affect output in the short run. Our objective is to separate fluctuations due to changes in fundamentals (news) from those due to temporary errors in agents' estimates (noise). We show that structural VARs cannot be used to identify news and noise shocks, but identification is possible via a method of moments or maximum likelihood. Next, we estimate our model on US data. Our results suggest that noise shocks explain a sizable fraction of short-run consumption fluctuations.