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New possibilities in identification of binary choice models with fixed effects

Yinchu Zhu

arXiv 21 Jun 2022 · Econometrics · 1 citations (OpenAlex)

arXiv:2206.10475 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We study the identification of binary choice models with fixed effects. We propose a condition called sign saturation and show that this condition is sufficient for identifying the model. In particular, this condition can guarantee identification even when all the regressors are bounded, including multiple discrete regressors. We also establish that without this condition, the model is not identified unless the error distribution belongs to a special class. Moreover, we show that sign saturation is also essential for identifying the sign of treatment effects. Finally, we introduce a measure for sign saturation and develop tools for its estimation and inference.

Citation extraction

31
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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
1Chamberlain, G (2010) Binary response models for panel data: Identification and information0.874182100%
2Manski, C. F (1987) Semiparametric analysis of random effects linear models from binary panel data0.87482100%
3Pakes, A. and Porter, J (2024) Moment inequalities for multinomial choice with fixed effects0.84333100%
4Davezies, L., D'Haultfuille, X., and Laage, L (2022) Identification and estimation of average marginal effects in fixed effects logit models0.73732100%
5Chamberlain, G (1980) Analysis of covariance with qualitative data0.73732100%
6Chernozhukov, V., Fernandez-Val, I., Hoderlein, S., Holzmann, H., an… (2015) Nonparametric identification in panels using quantiles0.64422100%
7Hoderlein, S. and White, H (2012) Nonparametric identification in nonseparable panel data models with generalized fixed effects0.64422100%
8Kim, J. and Pollard, D (1990) Cube root asymptotics0.64422100%
9Seo, M. H. and Otsu, T (2018) Local m-estimation with discontinuous criterion for dependent and limited observations0.64422100%
10Chernozhukov, V., Fernández-Val, I., Hahn, J., and Newey, W (2013) Average and quantile effects in nonseparable panel models0.58531100%

Showing the top 10 of 35 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models0.40511