Language as Data: A Survey of Natural Language Processing for Economics and Finance

This paper surveys the main methods, requisites, and applications of natural language processing (NLP) in economics and finance, guided by the following research questions: what is NLP currently capable, of and how can it contribute to economic research? What are the methods and techniques to achieve such contributions? What kind of data is needed and suitable for these methods' implementation? And what can we expect to achieve with NLP in economics and finance? These four questions outline the structure of the paper, respectively addressed by the topics of (i) useful NLP tasks for economics, (ii) NLP models, (iii) economic and financial textual data for NLP, and (iv) NLP applications in economics and finance. We further contribute by resorting to bibliometric tools to help us visualize the literature map of this field, also providing valuable insights to our survey. We finally indicate that there is much room to apply natural language processing to economic issues but alert that, more than ever, researchers must be careful not to stray away from questions motivated by hypotheses closely tied to economic theories.