PROGRAMME

SCHEDULE

Wednesday

09:30–10:15 Georgy Egorov (Northwestern): "Strategic Communication with Minimal Verification".

10:15–11:00 Raphaël Lévy (HEC): "Horizontal reputation and strategic audience management".

11:00–11:15 Break

11:15–12:00 Paweł Dziewulski (Oxford): "Eliciting the just-noticeable difference".

12:00–13:30 Lunch

13:30–14:15 Pierre Boyer (Polytechnique): "Politically feasible reforms of non-linear tax systems".

14:15–15:00 Bruno Strulovici (Northwestern): "Sequential investigations, fabrication and institutional unraveling​".

15:00–15:30 Break

15:30–16:15 James Best (Oxford): "Persuasion for the Long Run".

16:15–17:00 Josh Mollner (Northwestern): "High-Frequency Trading and Market Performance".


Thursday

09:30–10:15 Stefania Minardi (HEC): "Cases and Scenarios in Decisions under Uncertainty".

10:15–11:00 Jeff Ely (Northwestern): "Moving the goalposts".

11:00–11:15 Break

11:15–12:00 Eric Mengus (HEC): "Credibility and Monetary Policy".

12:00–13:30 Lunch

13:30–14:15 Peter Eso (Oxford): "Incomplete language as an incentive device".

14:15–15:00 Rafael Veiel (Crest Polytechnique): "The network structure of hierarchies of beliefs".

15:00–15:30 Break

15:30–16:15 Margaret Meyer (Oxford): "Information Design: Insights from Orderings of Dependence and Heterogeneity".

16:15–17:00 Daniel Martin (Northwestern): "Price Uncertainty Model".


Dinner on Thursday evening


Friday

09:30–10:15 Peter Klibanoff (Northwestern): "Incomplete Information Games with Ambiguity Averse Players".

10:15–11:00 Eduardo Perez-Richet (Sc. Po): "Information Design Under Falsification".

11:00–11:15 Break

11:15–12:00 Nemanja Antic (Northwestern): "Communication among Shareholders".

12:00–13:30 Lunch

13:30–14:15 Dan Quigley (Oxford): "Inside and Outside Information".

14:15–15:00 Maël Le Treust (ETIS/CNRS): "Persuasion with limited communication resources".

15:00–15:30 Break

15:30–16:15 Yingni Guo (Northwestern): "The Interval Structure of Optimal Disclosure".

16:15–17:00 Miguel Ballester (Oxford): "Separating Predicted Randomness from Noise".