- Indico style
- Indico style - inline minutes
- Indico style - numbered
- Indico style - numbered + minutes
- Indico Weeks View
We will learn a surrogate model for an agent-based macroeconomic model (ABM) and an objective function. The goal is to have a fast filtering algorithm that can replace this slower simulation in, for example, a stochastic optimization or approximate Bayesian computation.
All material will be uploaded here for the RAMP.
The RAMP is brought to you by Amir Sani and Antoine Mandel from the Centre d'Économie de la Sorbonne-CNRS, Paris School of Economics, Université Paris 1 Panthéon-Sorbonne, Francesco Lamperti from Institute of Economics and LEM, Scuola Superiore Sant'Anna (Pisa) and your regular coaches.
Funding support is provided by the European Union Horizons 2020 Future and Emerging Technologies Distributed Global Financial Systems for Society (DOLFINS) project.
Location
The event will take place at the Maison des Sciences Économiques, Salle de conférence, 6th floor.
General Guidelines
Your primary goal is to have a high score in the "contributivity" column. One way to achieve it is to submit a strong model, high in the "score" column, but we appreciate especially those models which do not have top scores but are sufficiently different from the rest of the models to achieve high score in the "contributivity" column.
A general rule is that you should not resubmit until your previous model has not yet been trained (it shows up in the "New models" table.)