The Limits of Causal Inference from Observational Data. presentation to the American Economic Association Meetings, Boston. see: hss.cmu.edu/philosophy/people/directory/Peter_Spi rtes.html Spirtes

The Limits of Causal Inference from Observational Data. presentation to the American Economic Association Meetings, Boston. see: hss.cmu.edu/philosophy/people/directory/Peter_Spi rtes.html Spirtes (1999)

by P Spirtes

Venue:

Proceedings of AI and Statistics 99

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Piecewise Linear Instrumental Variable Estimation of Causal Influence

by Richard Scheines, Greg Cooper, Changwon Yoo, Tianjiao Chu

"... Instrumental Variable (IV) estimation is a powerful strategy for estimating causal influence, even in the presence of confounding. Standard IV estimation requires that the relationships between variables is linear. Here we relax the linearity requirement by constructing a piecewise linear IV estimat ..."

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Instrumental Variable (IV) estimation is a powerful strategy for estimating causal influence, even in the presence of confounding. Standard IV estimation requires that the relationships between variables is linear. Here we relax the linearity requirement by constructing a piecewise linear IV estimator. Simulation studies show that when the causal influence of X on Y is non-linear, the piecewise linear is an improvement. 1

The Limits of Causal Inference from Observational Data. presentation to the American Economic Association Meetings, Boston. see: hss.cmu.edu/philosophy/people/directory/Peter_Spi rtes.html Spirtes (1999)

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Piecewise Linear Instrumental Variable Estimation of Causal Influence