1 citations · 1 across the 3 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
A Bootstrap Specification Test for Semiparametric Models with Generated Regressors
Elia Lapenta
This paper provides a specification test for semiparametric models with nonparametrically generated regressors. Such variables are not observed by the researcher but are nonparamet…
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…