Between hawks and doves: Measuring central bank communication

We propose a Hawkish-Dovish (HD) indicator that measures the degree of 'hawkishness' or 'dovishness' of the media's perception of the ECB's tone at each press conference. We compare two methods to calculate the indicator: semantic orientation and Support Vector Machines text classification. We show that the latter method tends to provide more stable and accurate measurements of perception on a labelled test set. Furthermore, we demonstrate the potential use of this indicator with several applications: we perform a correlation analysis with a set of interest rates, use Latent Dirichlet Allocation to detect the dominant topics in the news articles, and estimate a set of Taylor rules. The findings provide decisive evidence in favour of using an advanced text mining classification model to measure the medias perception and the Taylor rule application confirms that communication plays a significant role in enhancing the accuracy when trying to estimate the bank's reaction function.