  Instrumental variables estimation has gained considerable traction in recent
decades as a tool for causal inference, particularly amongst empirical
researchers. This paper makes three contributions. First, we provide a detailed
theoretical discussion on the properties of the standard two-stage least
squares estimator in the presence of weak instruments and introduce and derive
two alternative estimators. Second, we conduct Monte-Carlo simulations to
compare the finite-sample behavior of the different estimators, particularly in
the weak-instruments case. Third, we apply the estimators to a real-world
context; we employ the different estimators to calculate returns to schooling.
