  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 allows its application to models with few
conditional independeces.
