Can we measure inflation expectations using Twitter?

Cristina Angelico, Juri Marcucci, Marcello Miccoli () and Filippo Quarta ()
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Marcello Miccoli: International Monetary Fund
Filippo Quarta: Bank of Italy

No 1318, Temi di discussione (Economic working papers) from Bank of Italy, Economic Research and International Relations Area

Abstract: Using Italian data from Twitter, we employ textual data and machine learning techniques to build new real-time measures of consumers' inflation expectations. First, we select some relevant keywords to identify tweets related to prices and expectations thereof. Second, we build a set of daily measures of inflation expectations on the selected tweets combining the Latent Dirichlet Allocation (LDA) with a dictionary-based approach, using manually labelled bi-grams and tri-grams. Finally, we show that the Twitter-based indicators are highly correlated with both monthly survey-based and daily market-based inflation expectations. Our new indicators provide additional information beyond the market-based expectations, the professional forecasts, and the realized inflation, and anticipate consumers' expectations proving to be a good real-time proxy. Results suggest that Twitter can be a new timely source to elicit beliefs.

Keywords: inflation expectations; Twitter data; text mining; big data; survey-based measures; market-based measures; forecasting (search for similar items in EconPapers)
JEL-codes: C53 C55 D84 E31 E58 (search for similar items in EconPapers)
Date: 2021-02
New Economics Papers: this item is included in nep-big, nep-cwa and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Journal Article: Can we measure inflation expectations using Twitter? (2022)
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