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Binary choice logit models with general fixed effects for panel and network data

Kevin Dano, Bo E. Honoré, Martin Weidner

arXiv 15 Aug 2025 · Econometrics

arXiv:2508.11556 · PDF · Extracted main text

Abstract

This paper systematically analyzes and reviews identification strategies for binary choice logit models with fixed effects in panel and network data settings. We examine both static and dynamic models with general fixed-effect structures, including individual effects, time trends, and two-way or dyadic effects. A key challenge is the incidental parameter problem, which arises from the increasing number of fixed effects as the sample size grows. We explore two main strategies for eliminating nuisance parameters: conditional likelihood methods, which remove fixed effects by conditioning on sufficient statistics, and moment-based methods, which derive fixed-effect-free moment conditions. We demonstrate how these approaches apply to a variety of models, summarizing key findings from the literature while also presenting new examples and new results.

Citation extraction

56
references
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in-text mentions
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distinct cited
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self-citations
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main-text words

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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
1Honoré, B. E. and M. Weidner (2024) Moment conditions for dynamic panel logit models with fixed effects self1.00053100%
2Dano, K (2023) Transition probabilities and moment restrictions in dynamic fixed effects logit models self0.9285380%
3Graham, B. S (2016) Homophily and transitivity in dynamic network formation0.87472100%
4Bonhomme, S (2012) Functional differencing0.87452100%
5Graham, B. S (2017) An econometric model of network formation with degree heterogeneity0.81142100%
6Kitazawa, Y (2022) Transformations and moment conditions for dynamic fixed effects logit models0.73732100%
7Rasch, G (1960) Studies in mathematical psychology: I. Probabilistic models for some intelligence and attainment tests0.73732100%
Chamberlainunmatched citation key Chamberlain0.69361100%
9Chamberlain, G. (1980, January) (1980) Analysis of Covariance with Qualitative Data0.64422100%
10Charbonneau, K. B (2017) Multiple fixed effects in binary response panel data models0.64422100%

Showing the top 10 of 108 scored citations. 1 of these could not be matched to a bibliography entry, so only the citation key is shown.

Cited by, within the corpus

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

Citing paperIntensityMentionsSections
1Sufficient Statistics for Markovian Feedback Process and Unobserved Heterogeneity in Dynamic Panel Logit Models0.81142
2Compound Selection Decisions: An Almost SURE Approach0.64422
3Statistical inference in large multi-way networks0.64422
4Triadic Network Formation0.40511
5Tractable Identification of Strategic Network Formation Models with Unobserved Heterogeneity0.40511
6Semiparametric Dynamic Logit Model with Endogenous Networks0.40511
7Debiased Inference for Dynamic Nonlinear Panels with Multi-dimensional Heterogeneities0.00011