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Fixed Effects Binary Choice Models with Three or More Periods

Laurent Davezies, Xavier D'Haultfoeuille, Martin Mugnier

arXiv 17 Sep 2020 · Econometrics · publishedQuantitative Economics (2023) · 8 citations (OpenAlex)

arXiv:2009.08108 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We consider fixed effects binary choice models with a fixed number of periods $T$ and regressors without a large support. If the time-varying unobserved terms are i.i.d. with known distribution $F$, \cite{chamberlain2010} shows that the common slope parameter is point identified if and only if $F$ is logistic. However, he only considers in his proof $T=2$. We show that the result does not generalize to $T\geq 3$: the common slope parameter can be identified when $F$ belongs to a family including the logit distribution. Identification is based on a conditional moment restriction. Under restrictions on the covariates, these moment conditions lead to point identification of relative effects. If $T=3$ and mild conditions hold, GMM estimators based on these conditional moment restrictions reach the semiparametric efficiency bound. Finally, we illustrate our method by revisiting Brender and Drazen (2008).

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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 information0.69381100%
2Brender, A. and A. Drazen (2008) How do budget deficits and economic growth affect reelection prospects? evidence from a large panel of countries0.69371100%
3Bonhomme, S (2012) Functional differencing0.51121100%
4Magnac, T (2004) Binary variables and sufficiency: Generalizing conditional logit0.51121100%
5Krein, M. and A. A. Nudelman (1977) The Markov Moment Problem and Extremal Problems0.4052150%
6Hsu, S.-H. and C.-M. Kuan (2011) Estimation of conditional moment restrictions without assuming parameter identifiability in the implied unconditional moments0.40511100%
7Hahn, J (1997) A note on the efficient semiparametric estimation of some exponential panel models0.40511100%
8Honore, B. E. and A. Lewbel (2002) Semiparametric binary choice panel data models without strictly exogeneous regressors0.40511100%
9Kitazawa, Y (2022) Transformations and moment conditions for dynamic fixed effects logit models0.40511100%
10Balakrishnan, N. and M. Leung (1988) Order statistics from the type i generalized logistic distribution0.40511100%

Showing the top 10 of 22 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
1Moment Conditions for Dynamic Panel Logit Models with Fixed Effects0.92843
2Identification of Dynamic Panel Logit Models with Fixed Effects We thank Victor Aguirregabiria, Roger Koenker, Ismael Mourifié and Stanislav Volgushev for useful discussion. We are grateful to numerous seminar participants for their feedback, and are especially grateful to Francesca Molinari and three anonymous referees for their helpful comments. All errors are our own0.64422
3Approximate Functional Differencing0.64422
4An Adversarial Approach to Identification0.51121
5Dynamic Ordered Panel Logit Models0.40511
6New possibilities in identification of binary choice models with fixed effects0.40511
7Simultaneity in Binary Outcome Models with an Application to Employment for Couples0.40511
8Identification in a Binary Choice Panel Data Model with a Predetermined Covariate0.40511
9Transition Probabilities and Moment Restrictions in Dynamic Fixed Effects Logit Models0.40511
10Common Correlated Effects Estimation of Nonlinear Panel Data Models0.40511