Nothing
xtdml: Double Machine Learning for Static Panel Models with Fixed Effects
The 'xtdml' package implements partially linear panel regression (PLPR) models with high-dimensional confounding variables and an exogenous treatment variable within the double machine learning framework. The package is used to estimate the structural parameter (treatment effect) in static panel data models with fixed effects using the approaches established in Clarke and Polselli (2025) <doi:10.1093/ectj/utaf011>. 'xtdml' follows the object-oriented architecture of 'DoubleML' (Bach et al., 2024) <doi:10.18637/jss.v108.i03> and uses the 'mlr3' ecosystem.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Annalivia Polselli [aut, cre] (ORCID: <https://orcid.org/0009-0002-7579-7926>) |
| Maintainer | Annalivia Polselli <apolselli.econ@gmail.com> |
| License | GPL-2 | GPL-3 |
| Version | 0.1.13 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the xtdml package in your browser
Any scripts or data that you put into this service are public.
