Jörg Breitung, Alexander Mayer, Dominik Wied
arXiv 19 Jul 2022 · Econometrics · publishedEconometrics Journal (2024) · 19 citations (OpenAlex)
arXiv:2207.09246 · PDF · DOI · OpenAlex · Extracted main text
This paper considers a linear regression model with an endogenous regressor which arises from a nonlinear transformation of a latent variable. It is shown that the corresponding coefficient can be consistently estimated without external instruments by adding a rank-based transformation of the regressor to the model and performing standard OLS estimation. In contrast to other approaches, our nonparametric control function approach does not rely on a conformably specified copula. Furthermore, the approach allows for the presence of additional exogenous regressors which may be (linearly) correlated with the endogenous regressor(s). Consistency and asymptotic normality of the estimator are proved and the estimator is compared with copula based approaches by means of Monte Carlo simulations. An empirical application on wage data of the US current population survey demonstrates the usefulness of our method.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Park, S. and S. Gupta (2012) Handling Endogenous Regressors by Joint Estimation Using Copulas | 1.000 | 12 | 4 | 100% |
| 2 | Yang, F., Y. Qian, and H. Xie (2022) Addressing Endogeneity Using a Two-stage Copula Generated Regressor Approach | 0.874 | 9 | 2 | 100% |
| 3 | Pagan, A (1984) Econometric Issues in the Analysis of Regressions with Generated Regressors | 0.737 | 3 | 2 | 100% |
| 4 | Zhao, Y., I. Gijbels, and I. van Keilegom (2020) Inference for Semiparametric Gaussian Copula Model Adjusted for Linear Regression Using Residual Ranks | 0.659 | 7 | 3 | 29% |
| 5 | Lewbel, A., S. M. Schennach, and L. Zhang (2023) Identification of a Triangular Two Equation System Without Instruments | 0.644 | 2 | 2 | 100% |
| 6 | Wooldridge, J (2015) Control Function Methods in Applied Econometrics | 0.644 | 2 | 2 | 100% |
| 7 | Koenker, R. and Z. Xiao (2002) Inference on the Quantile Regression Process | 0.511 | 2 | 2 | 50% |
| 8 | Lemke, R. and I. Rischall (2003) Skill, Parental Income, and IV Estimation of the Returns to Schooling | 0.511 | 2 | 1 | 100% |
| 9 | Aloui, R., R. Gupta, and S. M. Miller (2016) Uncertainty and crude oil returns | 0.405 | 1 | 1 | 100% |
| 10 | Angrist, J.-D. and J.-S. Pischke (2008) Mostly Harmless Econometrics: An Empiricist's Companion | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 48 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | 2cmEndogeneity Corrections in Binary Outcome Models with Nonlinear Transformations: Identification and Inference | 1.000 | 10 | 5 |