*! version 1.0.0 18jul2026

Title

xtoutliers -- Outlier detection and robust estimation for panel data

Description

xtoutliers is a suite of three complementary tools for handling outliers
in linear panel-data models. Each addresses a different response to outliers:
detect, accommodate, and robustify. Typing xtoutliers
prints this overview.

Commands

xtvsom Variance Shift Outlier Model (VSOM): detects and
accommodates outliers by shifting (down-weighting) their variance. Runs as a
postestimation companion to xtreg (fixed
effects), regress (pooled) and ivregress (2SLS / simultaneous),
or standalone.

xtrobust Robust estimation of fixed- and random-effects panels
with the S-estimator and the Weighted Likelihood Estimator (WLE), compared with
OLS.

xtlossf Distribution-free outlier detection via loss functions,
for nonnegative (Part I) and mixed-sign (Part II) data.

xtoutliers methods Equation-by-equation
methods and the code®paper compatibility map.

Examples

Detect and accommodate outliers after a fixed-effects fit:

. webuse nlswork

. xtreg ln_wage age tenure hours, fe

. xtvsom, graph

Robust fixed-effects estimation:

. xtrobust ln_wage age tenure hours, fe method(all) graph

Loss-function detection comparing two data versions:

. xtlossf pop2010 pop2020 , q(-0.5) graph

References

Ismadyaliana, S., Setiawan, and J.D.T. Purnomo. 2024. Panel data
modeling: Identifying and handling outliers with the VSOM approach.
MethodsX 13: 102900.

Jaseem, H.N., and L.A. Mohammad. 2024. Detecting Outliers and Using
Robust Methods in Linear Panel Data Model. Al-Nahrain Journal of Science
27(4): 40-46.

Coleman, C.D., and T. Bryan. 2025. Loss Functions for Detecting Outliers
in Panel Data. arXiv:2509.07014v2.

Author

Dr Merwan Roudane

merwanroudane920@gmail.com

github.com/merwanroudane