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.

Diagnostic expectations constitute a realistic behavioural model of inference. This paper shows that this approach to expectation formation can be productively integrated into the New Keynesian framework. Diagnostic expectations generate endogenous extrapolation in general equilibrium. We show that diagnostic expectations generate extra amplification in the presence of nominal frictions; a fall in aggregate supply generates a Keynesian recession; fiscal policy is more effective at stimulating the economy. We perform Bayesian estimation of a rich medium-scale model that incorporates consensus forecast data. Our estimate of the diagnosticity parameter is in line with previous studies. Moreover, we find empirical evidence in favour of the diagnostic model. Diagnostic expectations offer new propagation mechanisms to explain fluctuations.