When evaluating partial effects, it is important to distinguish between structural endogeneity and measurement errors. In contrast to linear models, these two sources of endogeneity affect partial effects differently in nonlinear models. We study this issue focusing on the Instrumental Variable (IV) Probit and Tobit models. We show that even when a valid IV is available, failing to differentiate between the two types of endogeneity can lead to either under- or over-estimation of the partial effects. We develop simple estimators of the bounds on the partial effects and provide easy to implement confidence intervals that correctly account for both types of endogeneity. We illustrate the methods in a Monte Carlo simulation and an empirical application.

翻译：在评估偏效应时，区分结构性内生性与测量误差至关重要。与线性模型不同，这两种内生性来源在非线性模型中对偏效应的影响存在差异。我们通过聚焦工具变量(IV)Probit和Tobit模型研究该问题。研究表明，即便存在有效工具变量，未能区分两种内生性类型仍可能导致偏效应被低估或高估。我们开发了偏效应边界的简易估计量，并提供易于实施的置信区间，能正确涵盖两种内生性类型。我们通过蒙特卡洛模拟与经验应用示例演示了这些方法。