Jump to navigation
Romain Bouis (IMF)
4 septembre 2025, 14h00–15h30, BDF, Paris, salle Salle 5 de l’espace conférence
This paper examines empirically how the effect of interest rates on the three components of bank profits – loan loss provisions, net interest margin, and non-interest income – varies depending on bank characteristics and the macroprudential policy environment. A new finding is that higher interest...
Aaron Kaye (Massachusetts Institute of Technology)
4 septembre 2025, 14h00–15h00, Zoom Meeting
In many online markets, platforms engage in platform design by choosing product recom- mendation systems and selectively emphasizing certain product characteristics. I analyze the welfare effects of personalized recommendations in the context of the online market for hotel rooms using clickstream...
Stefan Kiefer (Oxford University)
Toulouse : TSE, 4 septembre 2025, 11h00–12h15, salle Auditorium 3
Markov decision processes (MDPs) are a standard model for dynamic systems that exhibit both stochastic and nondeterministic behavior. For MDPs with finite state space it is known that for a wide range of objectives there exist optimal strategies that are memoryless and deterministic. In...
Angélique Acquatella (Toulouse School of Economics)
Toulouse : TSE, 1 septembre 2025, 17h00–18h00, salle Auditorium 3 JJ Laffont
Paris School of Economics, 7–8 juillet 2025
A3 - TSE Building, du 3 juillet, 08h00 au 4 juillet 2025, 18h00, salle Auditorium 3 - Jean-Jacques Laffont
Nuffield College, 3–4 juillet 2025
Zhijun Chen
1 juillet 2025, 14h00–15h00, Zoom Meeting
Digital rms o¤er digital products to consumers and collect consumer data as a by- product of their usage. This data acquisition generates both data-monetization revenue and data-driven consumer benets, while imposing privacy costs on consumers. The paper ex- plores compensation schemes for consumer...
TSE Building, du 30 juin au 1 juillet 2025
Theodor Misiakiewicz (Yale University)
Toulouse : TSE, 26 juin 2025, 11h00–12h15, salle Auditorium 3
In this talk, we consider random feature ridge regression (RFRR), a model that has recently gained renewed interest for investigating puzzling phenomena in deep learning—such as double descent, benign overfitting, and scaling laws. Our main contribution is a general deterministic equivalent for the...
