EconBase
← All papers

Endogeneity Corrections in Binary Outcome Models with Nonlinear Transformations: Identification and Inference

Alexander Mayer, Dominik Wied

arXiv 13 Aug 2024 · Econometrics · publishedOxford Bulletin of Economics and Statistics (2025) · 2 citations (OpenAlex)

arXiv:2408.06977 · PDF · DOI · OpenAlex · Extracted main text

Abstract

For binary outcome models, an endogeneity correction based on nonlinear rank-based transformations is proposed. Identification without external instruments is achieved under one of two assumptions: either the endogenous regressor is a nonlinear function of one component of the error term, conditional on the exogenous regressors, or the dependence between the endogenous and exogenous regressors is nonlinear. Under these conditions, we prove consistency and asymptotic normality. Monte Carlo simulations and an application on German insolvency data illustrate the usefulness of the method.

Citation extraction

49
references
90
in-text mentions
49
distinct cited
1
self-citations
9,777
main-text words

appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Breitung, J., A. Mayer, and D. Wied (2024) Asymptotic Properties of Endogeneity Corrections Using Nonlinear Transformations1.000105100%
2Dong, Y (2010) Endogenous regressor binary choice models without instruments, with an application to migration1.00083100%
3Zhao, Y., I. Gijbels, and I. van Keilegom (2020) Inference for Semiparametric Gaussian Copula Model Adjusted for Linear Regression Using Residual Ranks0.92844100%
4Zhao, Y., I. Gijbels, and I. V. Keilegom (2022) Parametric Copula Adjusted for Non- and Semiparametric Regression0.84333100%
5Park, S. and S. Gupta (2012) Handling Endogenous Regressors by Joint Estimation Using Copulas0.81142100%
6Park, S. and S. Gupta (2024) A Review of Copula Correction Methods to Address Regressor–Error Correlation0.73732100%
7Rivers, D. and Q. H. Vuong (1988) Limited Information Estimators and Exogeneity Tests for Simultaneous Probit Models0.73732100%
8Escanciano, J. C., D. Jacho-Chávez, and A. Lewbel (2016) Identification and estimation of semiparametric two-step models0.64441100%
9Amemiya, T (1985) Advanced Econometrics0.64422100%
10Blundell, R. W. and J. L. Powell (2004) Endogeneity in Semiparametric Binary Response Models0.64422100%

Showing the top 10 of 49 scored citations.