Estimation of High‑Dimensional Seemingly Unrelated Regression Models

Aug 1, 2021·
Lidan Tan
,
Khai Chiong
,
Roger Moon
· 1 min read
Abstract
We develop estimation techniques for high‑dimensional seemingly unrelated regression (SUR) models. By leveraging regularization methods, the approach accommodates a large number of equations and potential cross‑equation dependencies.
Type
Publication
Econometric Reviews, Volume 40, Issue 9, pages 830–851, August 2021
publications

Tan, Chiong, and Moon extend the classical seemingly unrelated regression framework to high‑dimensional settings. Their regularization‑based estimator allows researchers to handle many equations simultaneously while capturing dependence across them. The results have implications for macroeconomics, finance, and marketing analytics.

High‑Dimensional Econometrics Seemingly Unrelated Regressions