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On the Existence of Conditional Maximum Likelihood Estimates of the Binary Logit Model with Fixed Effects

Martin Mugnier

arXiv 21 Sep 2020 · Econometrics

arXiv:2009.09998 · PDF · DOI · OpenAlex · Extracted main text

Abstract

By exploiting McFadden (1974)'s results on conditional logit estimation, we show that there exists a one-to-one mapping between existence and uniqueness of conditional maximum likelihood estimates of the binary logit model with fixed effects and the configuration of data points. Our results extend those in Albert and Anderson (1984) for the cross-sectional case and can be used to build a simple algorithm that detects spurious estimates in finite samples. As an illustration, we exhibit an artificial dataset for which the STATA's command clogit returns spurious estimates.

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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
1Albert \ Anderson (1984) `On the existence of maximum likelihood estimates in logistic regression models', Biometrika 71(1), 1–100.69371100%
2McFadden (1974) Conditional logit analysis of qualitative choice behaviour, in P. Zarembka, ed., `Frontiers in Econometrics', Academic Press New…0.69361100%
3Andersen (1970) `Asymptotic properties of conditional maximum-likelihood estimators', Journal of the Royal Statistical Society0.40511100%
4McCullough \ Vinod (2003) `Verifying the solution from a nonlinear solver: A case study', American Economic Review 93(3), 873–8920.40511100%
5Rasch (1961) On general laws and the meaning of measurement in psychology, in `Proceedings of the Fourth Berkeley Symposium on Mathematical S…0.40511100%

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