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Venue

Webex
14:00-16:00 CET

Format

online

Date

Wednesday, June 26, 2024

In cooperation with

Machine learning, neural networks and large-language models are swiftly being adopted in economic research. Currently, the use of generative AI is actively explored and embraced by economist in academia, central banks, think tanks and the financial sector. This workshop brings together cutting-edge research in two specific areas: first, the solving and estimation of economic models and, second, business cycle and inflation forecasting.

Organizing committee: Ernest Gnan – SUERF, Matthieu Darracq-Paries, Hanno Kase – ECB, Juha Kilponen, Esa Jokivuolle, Fabio Verona – Bank of Finland, Alessandro Notarpietro – Banca d’ Italia

Program

Time
Wednesday, 26 June 2024
14:00
Session 1: Solving and estimating macroeconomic models using deep learning

Estimating nonlinear heterogeneous agents models with neural networks

Hanno Kase, ECB

Co-authors: Leonardo Melosi, University of Warwick, FRB Chicago, DNB, CEPR, and Matthias Rottner, Deutsche Bundesbank

Solving life-cycle models with rich asset structure using deep learning

Marlon Azinovic, University of Pennsylvania

Multi-agent deep reinforcement learning in macroeconomic modelling

Tohid Atashbar, IMF
Chair: tba
15:15
Session 2: Business cycle and inflation forecasting using ML and AI

Maximally Forward-Looking Core Inflation

Philippe Goulet Coulombe, Université du Québec à Montréal

Exchange rate narratives

Kim Ristolainen, University of Turku

Co-author: Vito Cormun, Santa Clara University

Chair: tba
16:00
End