Skip to main content
Open Access Publications from the University of California

Department of Statistics, UCLA

Department of Statistics Papers bannerUCLA

Generalized Instrumental Variables


This paper concerns the assessment of direct causal effects from a combination of: (i) non-experimental data, and (ii) qualitative domain knowledge. Domain knowledge is encoded in the form of a directed acyclic graph (DAG), in which all interactions are assumed linear, and some variables are presumed to be unobserved. We provide a generalization of the well-known method of Instrumental Variables, which makes allows its application to models with few conditional independencies.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View