In observational studies, ignorability or conditional exchangeability is often an untenable assumption because of unmeasured confounders, pre-treamtent variables that affect both the treatment and the outcome. In this lecture, we discuss one of the most popular approaches to identify causal effects when ignorability fails: instrumental variables (IVs). Briefly, IVs require finding a variable , called an instrument, that satisfy certain assumptions. We cover two ways to formalize these assumptions, one based on monotonicity and another based on no additive interactions.
