Instrumental variables (IV) methods are central to applied microeconomics. While classical approaches assume linear models with constant effects, recent literature has shifted toward the local average treatment effect (LATE) framework to accommodate heterogeneous treatment effects. This paper provides a practical guide to aligning empirical practice with recent theory. We first examine how different specifications with covariates lead to distinct weighted averages of covariate-specific LATEs. We then discuss how parametric misspecification can undermine the causal interpretation of these estimands and suggest flexible specifications as essential robustness checks. Finally, we review formal tests for LATE assumptions and methods robust to monotonicity violations. We provide a guide to software implementations to help researchers apply the methods in practice.

翻译：工具变量（IV）方法是应用微观经济学的核心工具。虽然传统方法假设线性模型且效应恒定，但近期文献已转向局部平均处理效应（LATE）框架以容纳异质性处理效应。本文提供了将实证实践与最新理论相结合的实用指南。我们首先考察不同协变量设定如何导致协变量特定LATE的加权平均值差异，继而讨论参数误设可能损害这些估计量的因果解释力，并提出灵活设定作为必要的稳健性检验。最后，我们回顾了LATE假设的形式检验方法及应对单调性违背的稳健方法，并提供软件实现指南以帮助研究者实际应用这些方法。