Working Papers of Eesti Pank 8/2021
In this paper we analyse the communication reaction function1 of the European Central Bank (ECB) through topic-based indices derived from the speeches of the central bank. These indices are used as dependent variables in policy and communication reaction function models, as suggested by recent literature. The topics are extracted using Latent Dirichlet Allocation (LDA), a popular text mining algorithm for topic extraction. The ECB is at present reviewing its monetary policy strategy, and scholars are incorporating the new methods offered by text analysis to study the policy reaction function of the bank. We show how indices
built through topic modelling can be used to study the communication reaction function of a central bank, and we analyse which variables are significant for every topic communicated by the ECB.
1 The communication reaction function measures the response of the central bank’s communications to the indicators normally used in the policy reaction function of the same central bank. This can be done because the monetary policy of the central bank has to be consistent with its communications.
Keywords: Monetary policy, Central banking, Text mining, Communication reaction function.
JEL Classification: C55, C22, E52, E58.
The views expressed are those of the authors and do not necessarily represent the official views of Eesti Pank or the Eurosystem.
Authors’ affiliation and email: Luca Alfieri (corresponding author): University of Tartu, email: [email protected]. Diana
Gabrielyan: University of Tartu, email: [email protected].