News-driven inflation expectations and information rigidities

被引:35
|
作者
Larsen, Vegard H. [1 ,2 ]
Thorsrud, Leif Anders [3 ]
Zhulanova, Julia [3 ]
机构
[1] BI Norwegian Business Sch, Norges Bank, Trondheim, Norway
[2] BI Norwegian Business Sch, Ctr Appl Macroecon & Commod Prices CAMP, Trondheim, Norway
[3] BI Norwegian Business Sch, Ctr Appl Macroecon & Commod Prices, Trondheim, Norway
关键词
Expectations; Media; Machine learning; Inflation;
D O I
10.1016/j.jmoneco.2020.03.004
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
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.
引用
收藏
页码:507 / 520
页数:14
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