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Identification and Estimation of Average Causal Effects in Fixed Effects Logit Models

Laurent Davezies, Xavier D'Haultfœuille, Louise Laage

arXiv 3 May 2021 · Econometrics · 8 citations (OpenAlex)

arXiv:2105.00879 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper studies identification and estimation of average causal effects, such as average marginal or treatment effects, in fixed effects logit models with short panels. Relating the identified set of these effects to an extremal moment problem, we first show how to obtain sharp bounds on such effects simply, without any optimization. We also consider even simpler outer bounds, which, contrary to the sharp bounds, do not require any first-step nonparametric estimators. We build confidence intervals based on these two approaches and show their asymptotic validity. Monte Carlo simulations suggest that both approaches work well in practice, the second being typically competitive in terms of interval length. Finally, we show that our method is also useful to measure treatment effect heterogeneity.

Citation extraction

41
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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
1Dobronyi, C., J. Gu, and K. il Kim (2021) Identification of dynamic panel logit models with fixed effects0.5855160%
2D'Haultfuille, X. and R. Rathelot (2017) Measuring segregation on small units: A partial identification analysis0.58531100%
3Hoderlein, S. and H. White (2012) Nonparametric identification in nonseparable panel data models with generalized fixed effects0.58531100%
4Chernozhukov, V., I. Fernández-Val, J. Hahn, and W. Newey (2013) Average and quantile effects in nonseparable panel models0.58531100%
5Andersen, E. B (1970) Asymptotic properties of conditional maximum-likelihood estimators0.51121100%
6Chernozhukov, V., I. Fernández-Val, and W. K. Newey (2019) Nonseparable multinomial choice models in cross-section and panel data0.51121100%
7Dette, H. and W. J. Studden (1997) The theory of canonical moments with applications in statistics, probability, and analysis, Volume 3380.51121100%
8Aguirregabiria, V. and J. M. Carro (2024) Identification of average marginal effects in fixed effects dynamic discrete choice models0.4052150%
9Hahn, J (1997) A note on the efficient semiparametric estimation of some exponential panel models0.40511100%
10Altonji, J. G. and R. L. Matzkin (2005) Cross section and panel data estimators for nonseparable models with endogenous regressors0.40511100%

Showing the top 10 of 41 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
1Binary choice logit models with general fixed effects for panel and network data0.64422
2Sufficient Statistics for Markovian Feedback Process and Unobserved Heterogeneity in Dynamic Panel Logit Models0.51121
3Assignment at the Frontier: Identifying the Frontier Structural Function and Bounding Mean Deviations0.40511