Francesco Bianchi, Johns Hopkins University and Duke University

"Diagnostic Business Cycles"


A large psychology literature argues that, due to selective memory recall, decisionmakers' forecasts of their future circumstances appear overly influenced by the new information embedded in their current circumstances. We adopt the diagnostic expectations (DE) paradigm (Bordalo et al. (2018)) to capture this feature of belief formation and develop the micro-foundations for applying DE to business cycle models, while demonstrating its empirical relevance for aggregate dynamics. First, we develop behavioral foundations to address the theoretical challenges associated with modeling the feedback between optimal actions and agents' DE beliefs in the presence of (i) endogenous variables and (ii) time-inconsistencies in those optimal actions due to memory recall based on distant past. Second, we build on our theory to propose a portable solution method to study DE in dynamic stochastic general equilibrium models, which we use to estimate a quantitative New Keynesian model augmented with DE. We uncover a critical role played by both endogenous states and distant memory recall under DE in successfully replicating the boom-bust economic cycle observed in the data in response to a monetary policy shock.

Joint with Cosmin Ilut and Hikaru Saijo

Contact person: Emiliano Santoro