Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/229710
Authors: 
Naghi, Andrea A.
Váradi, Máté
Zhelonkin, Mikhail
Year of Publication: 
2021
Series/Report no.: 
Tinbergen Institute Discussion Paper No. TI 2021-004/III
Abstract: 
Probit models with endogenous regressors are commonly used models in economics and other social sciences. Yet, the robustness properties of parametric estimators in these models have not been formally studied. In this paper, we derive the influence functions of the endogenous probit model’s classical estimators (the maximum likelihood and the two-step estimator) and prove their non-robustness to small but harmful deviations from distributional assumptions. We propose a procedure to obtain a robust alternative estimator, prove its asymptotic normality and provide its asymptotic variance. A simple robust test for endogeneity is also constructed. We compare the performance of the robust and classical estimators in Monte Carlo simulations with different types of contamination scenarios. The use of our estimator is illustrated in several empirical applications.
Subjects: 
Binary outcomes
Probit model
Endogenous variable
Instrumental variable
Robust Estimation
JEL: 
C26
C13
C18
Document Type: 
Working Paper

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