INFLATION EXPECTATIONS AND CONSUMPTION WITH MACHINE LEARNING

Diana Gabrielyan and Lenno Uusküla
Authors registered in the RePEc Author Service: Lenno Uusküla

No 142, University of Tartu - Faculty of Economics and Business Administration Working Paper Series from Faculty of Economics and Business Administration, University of Tartu (Estonia)

Abstract: We extract measures of inflation expectations from online news to build real interest rates that capture true consumer expectations. The new measure is infused to various Euler consumption models. While benchmark models based on traditional risk-free returns rates fail, models built with novel news-driven inflation expectations indices improve upon benchmark models and result in strong instruments. Our positive findings highlight the role played by the media for consumer expectation formation and allow for the use of such novel data sources for other key macroeconomic relationships.

Keywords: Euler equation; expectations; media; machine learning (search for similar items in EconPapers)
Pages: 42 pages
Date: 2022
New Economics Papers: this item is included in nep-big, nep-cmp, nep-mac and nep-mon
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Persistent link: https://EconPapers.repec.org/RePEc:mtk:febawb:142

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