Text mining (ID: 18718)

Analysis of central bank communication using advanced text modeling methods


Title: Analysis of central bank communication using advanced text modeling methods

Funder:  Austrian National Bank (OeNB), (link) 

Project Team: Paul Hofmarcher (University Salzburg, Principal Investigator), Bettina Grün (WU Vienna, Co-Investigator), Niko Hauzenberger (University Salzburg, Co-Investigator) 

Project Funded Staff: Niko Hauzenberger (July 2022-January 2023),  Jan Vavra (January 2023-)

Appropriate communication strategies from central banks are considered to be important tools for the effective implementation of monetary policy. Especially since the financial crisis, where many central banks were tied to the zero lower bound, good communication is essential to compensate for this limitation.

We analyze central bank speeches spanning more than five decades to examine different communication strategies and their effects on macroeconomic indicators, taking into account differences in time, region and actors. The project includes the three main contributions. First, building on recently developed text analysis models, we develop extensions and adaptations so that they are particularly suitable for central bank speeches. Second, we apply the existing and newly developed models to a new data set that contains more than 16,000 speeches by central bankers, which are available on the BIS website. Third, we use covariates derived from the text analysis to fit vector autoregressions to these covariates as well as macroeconomic indicators and thus carry out a structural analysis of a communication shock and to check whether this improves the predictive quality for macroeconomic indicators.

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