arXiv 27 Jan 2024 · Statistics — Methodology · 1 citations (OpenAlex)
arXiv:2401.15253 · PDF · DOI · OpenAlex · Extracted main text
We provide a Copula-based approach to test the exogeneity of instrumental variables in linear regression models. We show that the exogeneity of instrumental variables is equivalent to the exogeneity of their standard normal transformations with the same CDF value. Then, we establish a Wald test for the exogeneity of the instrumental variables. We demonstrate the performance of our test using simulation studies. Our simulations show that if the instruments are actually endogenous, our test rejects the exogeneity hypothesis approximately 93% of the time at the 5% significance level. Conversely, when instruments are truly exogenous, it dismisses the exogeneity assumption less than 30% of the time on average for data with 200 observations and less than 2% of the time for data with 1,000 observations. Our results demonstrate our test's effectiveness, offering significant value to applied econometricians.
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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 | Angrist, J. D. and Krueger, A. B (1991) Does compulsory school attendance affect schooling and earnings? | 0.874 | 6 | 3 | 67% |
| 2 | Park, S. and Gupta, S (2012) Handling endogenous regressors by joint estimation using copulas | 0.811 | 4 | 2 | 100% |
| 3 | Wooldridge, J. M (2010) Econometric analysis of cross section and panel data | 0.737 | 3 | 2 | 100% |
| 4 | Yang, F., Qian, Y., and Xie, H (2022) Addressing endogeneity using a two-stage copula generated regressor approach | 0.737 | 3 | 2 | 100% |
| 5 | Kiviet, J. F (2020) Testing the impossible: Identifying exclusion restrictions | 0.644 | 4 | 1 | 100% |
| 6 | Durbin, J (1954) Errors in variables. review of the international statistical institute 22: 23–32 | 0.644 | 2 | 2 | 100% |
| 7 | Ebbes, P., Wedel, M., Böckenholt, U., and Steerneman, T (2005) Solving and testing for regressor-error (in) dependence when no instrumental variables are available: With new evidence for the… | 0.644 | 2 | 2 | 100% |
| 8 | Hausman, J. A (1978) Specification tests in econometrics | 0.644 | 2 | 2 | 100% |
| 9 | Kleibergen, F. and Zivot, E (2003) Bayesian and classical approaches to instrumental variable regression | 0.644 | 2 | 2 | 100% |
| 10 | Rossi, P. E. and Allenby, G. M (2003) Bayesian statistics and marketing | 0.644 | 2 | 2 | 100% |
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