6 citations · 11 across the 6 of their papers we have counts for
6 papers
Pivotal and identification-robust nonparametric inference in linear IV models
Bertille Antoine, Pascal Lavergne
We develop new inference procedures for a linear IV model that are robust to identification strength and heteroskedasticity of unknown form, and nonparametric with respect to the f…
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…
Encompassing Tests for Nonparametric Regressions
Elia Lapenta, Pascal Lavergne
We set up a formal framework to characterize encompassing of nonparametric models through the L2 distance. We contrast it to previous literature on the comparison of nonparametric…
Powerful nonparametric checks for quantile regression
Samuel Maistre, Pascal Lavergne, Valentin Patilea
We address the issue of lack-of-fit testing for a parametric quantile regression. We propose a simple test that involves one-dimensional kernel smoothing, so that the rate at which…
A Significance Test for Covariates in Nonparametric Regression
Pascal Lavergne, Samuel Maistre, Valentin Patilea
We consider testing the significance of a subset of covariates in a nonparametric regression. These covariates can be continuous and/or discrete. We propose a new kernel-based test…
Data-driven rate-optimal specification testing in regression models
Emmanuel Guerre, Pascal Lavergne
We propose new data-driven smooth tests for a parametric regression function. The smoothing parameter is selected through a new criterion that favors a large smoothing parameter un…