Agents forming adaptive expectations generally make systematic mistakes. This characterization has fostered the rejection of adaptive expectations in macroeconomics. Experimental evidence, however, shows that in complex environments human subjects frequently rely on adaptive heuristics –...

The adaptive learning approach has been fruitfully employed to model the formation of aggregate expectations at the macroeconomic level, as an alternative to rational expectations. This paper uses adaptive learning to understand, instead, the formation of expectations at the micro-level, by...

Research about narratives’ role in economics is scarce, while real word experience and research in other sciences suggest they matter a lot. This article proposes a view and methodology for quantifying the epidemiology of media narratives relevant to business cycles in the US, Japan, and...

What are the effects of beliefs, sentiment, and uncertainty, over the business cycle? To answer this question, we develop a behavioral New Keynesian macroeconomic model, in which we relax the assumption of rational expectations. Agents are, instead, boundedly rational: they have a...

This paper estimates a New Keynesian model extended to include heterogeneous expectations, to revisit the evidence that postwar US macroeconomic data can be explained as the outcome of passive monetary policy, indeterminacy, and sunspot-driven fluctuations in the pre-1979 sample, with a switch...

Motivated by the observation that survey expectations of stock returns are inconsistent with rational return expectations under real-world probabilities, we investigate whether alternative expectations hypotheses entertained in the asset pricing literature are consistent with the survey...

Unique longitudinal probabilistic expectations data from the Berea Panel Study, which cover both college and early post-college periods, are used to examine young adults’ beliefs about their future incomes. We introduce a new measure of the ex post accuracy of beliefs, and two new approaches...