49 citations · 108 across the 19 of their papers we have counts for
20 papers
Identification and Estimation of Consumers' Preferences from Repeated Observations under Nonlinear Pricing
Samuele Centorrino, Frédérique Fève, Jean-Pierre Florens
We develop a nonparametric approach to identify and estimate consumer preferences and unobserved heterogeneity under nonlinear price schedules. Leveraging variation across multiple…
Panel data models with randomly generated groups
Jean-Pierre Florens, Anna Simoni
We develop a structural framework for modeling and inferring unobserved heterogeneity in dynamic panel-data models. Unlike methods treating clustering as a descriptive device, we m…
Tests of exogeneity in duration models with censored data
Gilles Crommen, Jean-Pierre Florens, Ingrid Van Keilegom
Consider the setting in which a researcher is interested in the causal effect of a treatment on a duration time , which is subject to right censoring. We assume that $T=φ(X,…
Debiasing Machine Learning Models by Using Weakly Supervised Learning
Renan D. B. Brotto, Jean-Michel Loubes, Laurent Risser +3
We tackle the problem of bias mitigation of algorithmic decisions in a setting where both the output of the algorithm and the sensitive variable are continuous. Most of prior work…
Partly Linear Instrumental Variables Regressions without Smoothing on the Instruments
Jean-Pierre Florens, Elia Lapenta
We consider a semiparametric partly linear model identified by instrumental variables. We propose an estimation method that does not smooth on the instruments and we extend the Lan…
Testing for homogeneous treatment effects in linear and nonparametric instrumental variable models
Jad Beyhum, Jean-Pierre Florens, Elia Lapenta +1
The hypothesis of homogeneous treatment effects is central to the instrumental variables literature. This assumption signifies that treatment effects are constant across all subjec…