Leveraging Natural Language Processing (NLP) To Answer Economic Questions

Natural language processing (NLP) is undergoing a revolution as big data and large-language models transform the capacity to represent and analyse textual information and extra signals and meaning.

This conference aims to bring together recent research using these approaches in economics.

14h - Opening remarks 

14h05 - Opening speech -“Future Challenges for Text-as-Data in Economics”
               
               Professor Stephen Hansen, University College London

Session 1 – Using NLP to improve forecasting and understand narratives

14h40 - Making text count: Economic forecasting using newspaper text (Kalamara, Turrell, Redl, George, Kapadia, 2022)

15h00 -  Risky news and credit market sentiment (Labonne and Thorsrud, BI Norwegian Business School)

15h20 - The impact of monetary surprises on exchange rates: insights from a textual analysis approach on a panel of countries (Bricongne and Marolleau, Banque de France)

15h40 – Mining the Gap: Extracting Firms’ Inflation Expectations From Earnings Calls, (Albrizio, Dizioli and Vitale Simon, 2023, IMF)

16h00 - Short break

Session 2 – Using NLP to explore different concepts

16h10- Assessing Economic Risks Around Macroeconomic Forecasts:  A mixture of fined-tuned BERT and economic experts (Betin, Chalaux, Dex and Turner, OECD, forthcoming)

16h30 - New dimensions of regulatory complexity and their economic cost. An analysis using text mining (De Lucio and Mora-Sanguinetti, Banco de Espana, 2021)

16h50 - Using Computational Linguistics to Identify Competitors and Competitive Interactions (Phillips, Darmouth)

17h10 - Using NLP to detect data/AI hiring intensive jobs and firms (Schmidt, Pilgrim and Mourougane, forthcoming)

17h30 - Closing remarks 
 

Programme