3 papers
econ.EM2026
A Machine-Learning-Compatible Omnibus Test for Treatment Effect Heterogeneity
Elia Lapenta, Anthony Strittmatter, Pedro Vergara Merino
This study proposes a formal, computationally efficient nonparametric omnibus test for treatment-effect heterogeneity that is compatible with a broad class of estimators, including…
econ.EM2026
Average Marginal Effects in One-Step Partially Linear Instrumental Regressions
Lucas Girard, Elia Lapenta
We propose a novel procedure for estimating and conducting inference on average marginal effects in partially linear instrumental regressions using Reproducing Kernel Hilbert Space…
econ.EM2024
One-step smoothing splines instrumental regression
Jad Beyhum, Elia Lapenta, Pascal Lavergne
We extend nonparametric regression smoothing splines to a context where there is endogeneity and instrumental variables are available. Unlike popular existing estimators, the resul…