8th conference on 'Nontraditional Data, Machine Learning, and Natural Language Processing in Macroeconomics'

18 May 2026

the ECONDAT 2026 Fall Meeting

Banca d'Italia, the Federal Reserve Board, the Bank of Canada, Sveriges Riksbank, the Bank of Japan and CEBRA (Central Bank Research Association) are co-organizing the 8th conference on 'Nontraditional Data, Machine Learning, and Natural Language Processing in Macroeconomics' - the ECONDAT 2026 Fall Meeting, which will take place in Tokyo on October 5-6, 2026.

The conference aims to promote the discussion and dissemination of empirical and theoretical research in macroeconomics and financial economics, with a focus on data science, nontraditional data, and artificial intelligence techniques, including machine learning and natural language processing. The event will provide an opportunity for exchanges on current topics with representatives from academia, central banks and other institutions.

Keynote speakers include Melissa Dell (Harvard University) and Matthew Shapiro (University of Michigan).

Research papers, either in a complete PDF format or as extended abstracts, must be submitted via the https://econdat2026f.raku-con.com/ submission portal by June 7, 2026. A detailed conference programme will be published once the various papers have been evaluated and selected.

For further information, please email conference@boj.or.jp.

Organizing Committee:

Yoshiyuki Kurachi, Tomohiro Sugo, Hiroki Takemura and Lisa Uemae (Bank of Japan).

Scientific Committee: Giuseppe Bruno, Sabina Marchetti and Juri Marcucci (Banca d'Italia), Tomaz Cajner, Ricardo Correa, Leland Crane, Christopher Kurz and Clara Vega (Federal Reserve Board), Joshua Brault, Ajit Desai, Maryam Haghighi and Daniel Indacochea (Bank of Canada), Yoshiyuki Kurachi and Tomohiro Sugo (Bank of Japan), Tunrayo Adeleke-Lorado, Marcus Buckmann, Dragos Gorduza and Andreas Joseph (Bank of England), Jean-Charles Bricongne (Banque de France), and Davide Bucci and Xin Zhang (Sveriges Riksbank).

Annexes

  1. 18 May 2026
    Call for papers
    pdf 73 KB