This paper proposes and estimates a dynamic model of household inflation expectations. The information flow constraint of the household leads to costly information monitoring. Households use a Bayesian learning model to form and update inflation expectations. The model identifies and corrects for sizable reporting and sampling errors prevalent in household surveys. The estimates show that better-educated households track inflation more closely and report their expectations more accurately. Household inflation expectations are less responsive to changes in the inflation target after the Great Recession. Model-implied household inflation expectations improve the fit of the expectation-augmented Phillips curve. Inattention from households makes it more costly for the Fed to lower inflation than would be the case if everyone is perfectly informed.
|Original language||English (US)|
|Number of pages||45|
|State||Published - Nov 2019|