This paper considers regression models for cross-section data that exhibit cross-section dependence due to common shocks, such as macroeconomic shocks. The paper analyzes the properties of least squares (LS) and instrumental variables (IV) estimators in this context. The results of the paper...

Empirical researchers often combine multiple instrumental variables (IVs) for a single treatment using two-stage least squares (2SLS). When treatment effects are heterogeneous, a common justification for including multiple IVs is that the 2SLS estimand can be given a causal interpretation as a...

We revisit the finite-sample behavior of just-identified instrumental variables (IV) estimators, arguing that in most microeconometric applications, just-identified IV bias is negligible and the usual inference strategies likely reliable. Three widely-cited applications are used to explain why...