Abstract.
This article introduces Data Science techniques into the study of central banking. It studies the evolution of the ECB’s communication through time, considering its three subsequent presidents (W. Duisenberg, J.C. Trichet and M. Draghi) and the pre- and post- 2008 financial crisis era. It helps understand the history of the ECB since its inception. From a methodological standpoint, we study the evolution of the ECB’s speeches. The speech analysis is based on data science and uses cutting-edge machine learning techniques and sentiment analyses. For that purpose, we have assembled a unique dataset of the ECB’s speeches. We have coded powerful algorithms to run the text analysis through time. They help us capture the evolution in the ECB’s understanding of the actual economic situation and also measure - for instance - the stress level at the ECB through a polarity analysis through time.
Keywords: European Central Bank, text analysis, data science, natural language processing, institutional communications
For attribution, please cite this work as
Sanger & Warin (2020, June 1). Thierry Warin, PhD: [Article] How Data Science can (also) help central bankers: An NLP study of the European Central Bank presidents’ speeches. Retrieved from https://warin.ca/posts/article-how-data-science/
BibTeX citation
@misc{sanger2020[article], author = {Sanger, William and Warin, Thierry}, title = {Thierry Warin, PhD: [Article] How Data Science can (also) help central bankers: An NLP study of the European Central Bank presidents’ speeches}, url = {https://warin.ca/posts/article-how-data-science/}, year = {2020} }