Identification and Overidentification of Linear Structural Equation Models
In this paper, we address the problems of identifying linear structural equation models and discovering the constraints they imply. We first extend the half-trek criterion to cover a broader class of models and apply our extension to finding testable constraints implied by the model. We then show that any semi-Markovian linear model can be recursively decomposed into simpler sub-models, resulting in improved identification and constraint discovery power. Finally, we show that, unlike the existing methods developed for linear models, the resulting method subsumes the identification and constraint discovery algorithms for non-parametric models.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Arellano-Bond LASSO Estimator for Dynamic Linear Panel Models
The Arellano-Bond estimator is a fundamental method for dynamic panel data models, widely used in practice. However, the estimator is severely biased when the data's time series dimension $T$ is long due to the large deg…
Time SeriesOveridentification in Shift-Share Designs
This paper studies the testability of identifying restrictions commonly employed to assign a causal interpretation to two stage least squares (TSLS) estimators based on Bartik instruments. For homogeneous effects models …
validDecomposition and Identification of Linear Structural Equation Models
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 mod…
Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables
We developed a novel approach to identification and model testing in linear structural equation models (SEMs) based on auxiliary variables (AVs), which generalizes a widely-used family of methods known as instrument…
NeuralSI: Structural Parameter Identification in Nonlinear Dynamical Systems
Structural monitoring for complex built environments often suffers from mismatch between design, laboratory testing, and actual built parameters. Additionally, real-world structural identification problems encounter many…
parameter estimationStructural Health Monitoring