In this paper we propose novel techniques for the empirical analysis of adaptive learning and sticky information in inflation expectations. These methodologies are applied to the distribution of households' inflation expectations collected by the University of Michigan Survey Research Center. To account for the evolution of the cross-section of inflation forecasts over time and measure the degree of heterogeneity in private agents' forecasts, we explore time series of percentiles from the empirical distribution. Our results show that heterogeneity is pervasive in the process of inflation expectation formation. We identify three regions of the distribution that correspond to different underlying mechanisms of expectation formation: a static or highly autoregressive region on the left hand side of the median, a nearly rational 6 We would like to thank the Editor, two anonymous referees, Sean Holly, Seppo Honkapohja, Hashem Pesaran, Cars Hommes, Tiago Cavalcanti, Domenico Delli Gatti, Chryssi Giannitsarou, Steffan Ball, Jagjit Chada, Daniele Massacci, Linda Rousova and seminar participants at Keele University, Cambridge Univer- JEL: E31; C53; D80;

This paper examines the nexus between news coverage on inflation and households’ inflation expectations. In doing so, we test the epidemiological foundations of the sticky information model (Carroll ). We use both aggregate and household‐level data from the Survey Research Center at the University of Michigan. We highlight a fundamental disconnection among news on inflation, consumers’ frequency of expectation updating, and the accuracy of their expectations. Our evidence provides at best weak support to the epidemiological framework, as most of the consumers who update their expectations do not revise them toward professional forecasters’ mean forecast.

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