Marginal effects for probit and tobit with endogeneity

Summary 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 non-linear models. We study this issue, focusing on the instrumental variable (IV) probit and tobit models. We show that even when a valid instrumental variable is available, failing to differentiate between the two types of endogeneity can lead to either under- or overestimation 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.

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Publication Details

Journal
Econometrics Journal
Published
2025-03-29
DOI
https://doi.org/10.1093/ectj/utaf010
Citations
1
Primary Topic
Aviation Industry Analysis and Trends
Type
article
Field-Weighted Citation Impact
3.09

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article

Marginal effects for probit and tobit with endogeneity

Ilze Kalnina, Andrei Zeleneev, Kirill S. Evdokimov
1 citations
Econometrics Journal
Aviation Industry Analysis and Trends
3.09
article

Marginal effects for probit and tobit with endogeneity

Ilze Kalnina, Andrei Zeleneev, Kirill S. Evdokimov
article en
1 citations

Abstract

Summary 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 non-linear models. We study this issue, focusing on the instrumental variable (IV) probit and tobit models. We show that even when a valid instrumental variable is available, failing to differentiate between the two types of endogeneity can lead to either under- or overestimation 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.

Econometrics JournalVol. 29(1)
North Carolina State University (US), Universitat Pompeu Fabra (ES), Barcelona School of Economics (ES), University College London (GB)
UK Research and Innovation, HORIZON EUROPE Framework Programme, Agencia Estatal de Investigación, European Social Fund
Openalex Percentile: Top 12%
Aviation Industry Analysis and Trends
3.09
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Marginal effects for probit and tobit with endogeneity — Ilze Kalnina, Andrei Zeleneev, et al. · Econometrics Journal (2025) | TGRS Research Map | TGRS