Summary
In this chapter, we explored instrumental variables regression, focusing on addressing unobserved confounders in estimating causal relationships between a treatment 
and an outcome 
It highlighted instrumental variable regression as a technique for mitigating confounder bias by using an exogenous instrument 
that affects the outcome exclusively through the treatment. This method isolates the causal effect of the treatment by identifying variations in the outcome resulting from instrumental variable-driven changes in the treatment. The chapter addressed the fulfillment of instrumental variable assumptions, such as the exclusion restriction, and introduced two-stage least squares estimation for practical implementation. By combining theoretical discussions with economic history examples, the chapter elucidated instrumental variable regression’s utility and constraints, emphasizing its effectiveness in resolving endogeneity when conventional approaches are inadequate. In...
