In this paper, we address the problem of identifying linear structural equation models. We first extend the edge set half-trek criterion to cover a broader class of models. We then show that any semi-Markovian linear model can be recursively decomposed into simpler sub-models, resulting in improved identification power. Finally, we show that, unlike the existing methods developed for linear models, the resulting method subsumes the identification algorithm of non-parametric models.
@article{arxiv.1508.01834,
title = {Decomposition and Identification of Linear Structural Equation Models},
author = {Bryant Chen},
journal= {arXiv preprint arXiv:1508.01834},
year = {2015}
}