Estimating causal impacts is fraught with difficulty. Even randomized trials are imperfect, in part because we can seldom, if ever, conduct true experiments (though experimental design is still the gold standard of statistical research). IV is one of the more compelling quasi-experimental methods of estimating impacts, largely because the assumptions needed to justify the IV method are often more plausible than those needed to justify other methods, such as regression.

via The Urban Institute | Toolkit | Data Methods | Instrumental Variables Methods.