Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/284135 
Year of Publication: 
2023
Series/Report no.: 
cemmap working paper No. CWP11/23
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
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.
Subjects: 
(Average) Partial Effects
Instrumental Variable
Control Variable
Errors-in-Variables
Counterfactuals
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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