News-driven inflation expectations and information rigidities

Using a large news corpus and machine learning algorithms we investigate the role played by the media in the expectations formation process of households, and conclude that the news topics media report on are good predictors of both inflation and inflation expectations. In turn, in a noisy information model, augmented with a simple media channel, we document that the time series features of relevant topics help explain time-varying information rigidity among households. As such, we provide a novel estimate of state-dependent information rigidities and present new evidence highlighting the role of the media in understanding inflation expectations and information rigidities. (C) 2020 The Authors. Published by Elsevier B.V.

Automated summary

By analyzing the role of media in the expectations formation process of households, it was found that news topics are good predictors of both inflation and inflation expectations. The study also shows that the time series features of relevant topics help explain time-varying information rigidity among households, providing a novel estimate of state-dependent information rigidities and highlighting the role of the media in understanding inflation expectations and information rigidities.