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Yannick GUYONVARCH (Télécom Paris) – "Nonasymptotic inference on functionals in regular M-estimation problems"

March 31 @ 2:00 pm - 3:00 pm | Organizers: , François-Pierre Paty, Nicolas Schreuder
Statistics-Econometrics-Machine Learning Seminar.
Time: 14:00 pm – 15:00 pm
Date: 31st of March 2021
Place: Online
Yannick GUYONVARCH (Télécom Paris) – “Nonasymptotic inference on functionals in regular M-estimation problems”
Abstract :
This talk will be divided in three parts. We will first present several motivating examples which are popular in the applied econometric literature (average marginal effects in binary regression, average treatment effects). In the second part of the talk, we will present a new confidence interval (CI) for a scalar mean. Under existence of moments of order four, this CI is valid nonasymptotically and is more accurate asymptotically than a CI derived from the Bernstein concentration inequality. We will explain at length the connection between our new CI and existing approaches based on alternative concentration inequalities. In the final part of the presentation, we will show how to use the result obtained for scalar means to derive new nonasymptotic CIs for smooth functionals in regular M-estimation models.