Nonparametric instrumental variable (NPIV) estimation is a cutting‐edge methodological framework employed to uncover causal relationships in the presence of endogenous regressors, without imposing ...

This project implements a novel approach to causal inference using Graph Attention Networks (GAT) to synthesize instrumental variables for confounded treatment effect estimation. The system learns to ...

This paper establishes that instruments enable the identification of nonparametric regression models in the presence of measurement error by providing a closed form ...

A brief description of the methods used by the SYSLIN procedure follows. For more information on these methods, see the references at the end of this chapter. There are two fundamental methods of ...

This paper extends the usual Instrumental Variables estimator of the parameters of a linear regression involving stochastic regressors to the case where these parameters are subject to exact linear ...

Abstract: Treatment effect estimation from observational data is a fundamental problem in causal inference, and its critical challenge is to address the confounding bias arising from the confounders.

Several of the estimation methods supported by PROC MODEL are instrumental variables methods. There is no standard method for choosing instruments for nonlinear regression. Few econometric textbooks ...