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New possibilities in identification of binary choice models with fixed effects

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  • Yinchu Zhu

Abstract

We study the identification of binary choice models with fixed effects. We provide a condition called sign saturation and show that this condition is sufficient for the identification of the model. In particular, we can guarantee identification even when all the regressors are bounded, including multiple discrete regressors. We also show that without this condition, the model is not identified unless the error distribution belongs to a special class. The same sign saturation condition is also essential for identifying the sign of treatment effects. A test is provided to check the sign saturation condition and can be implemented using existing algorithms for the maximum score estimator.

Suggested Citation

  • Yinchu Zhu, 2022. "New possibilities in identification of binary choice models with fixed effects," Papers 2206.10475, arXiv.org, revised Dec 2024.
    • Handle: RePEc:arx:papers:2206.10475
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    References listed on IDEAS

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    1. Manski, Charles F, 1987. "Semiparametric Analysis of Random Effects Linear Models from Binary Panel Data," Econometrica, Econometric Society, vol. 55(2), pages 357-362, March.
    2. Gary Chamberlain, 2010. "Binary Response Models for Panel Data: Identification and Information," Econometrica, Econometric Society, vol. 78(1), pages 159-168, January.
    3. Charalambos D. Aliprantis & Kim C. Border, 2006. "Infinite Dimensional Analysis," Springer Books, Springer, edition 0, number 978-3-540-29587-7, December.
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    Cited by:

    1. Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.

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