Seeing the Forest for the Trees: using hLDA models to evaluate communication in Banco Central do Brasil

Angelo Fasolo, Flavia Graminho and Saulo Bastos

No 555, Working Papers Series from Central Bank of Brazil, Research Department

Abstract: Central bank communication is a key tool in managing ination expectations. This paper proposes a hierarchical Latent Dirichlet Allocation (hLDA) model combined with feature selection techniques to allow an endogenous selection of topic structures associated with documents published by Banco Central do Brasil's Monetary Policy Committee (Copom). These computational linguistic techniques allow building measures of the content and tone of Copom's minutes and statements. The effects of the tone are measured in different dimensions such as inflation, inflation expectations, economic activity, and economic uncertainty. Beyond the impact on the economy, the hLDA model is used to evaluate the coherence between the statements and the minutes of Copom's meetings.

Date: 2021-08
New Economics Papers: this item is included in nep-big, nep-cba, nep-cmp, nep-isf, nep-mac and nep-mon
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Related works:
Working Paper: Seeing the forest for the trees: Using hLDA models to evaluate communication in Banco Central do Brasil (2022)
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