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Revisiting Panel Data Discrete Choice Models with Lagged Dependent Variables

Christopher R. Dobronyi, Fu Ouyang, Thomas Tao Yang

arXiv 23 Jan 2023 · Econometrics · 2 citations (OpenAlex)

arXiv:2301.09379 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper revisits the identification and estimation of a class of semiparametric (distribution-free) panel data binary choice models with lagged dependent variables, exogenous covariates, and entity fixed effects. We provide a novel identification strategy, using an "identification at infinity" argument. In contrast with the celebrated Honore and Kyriazidou (2000), our method permits time trends of any form and does not suffer from the "curse of dimensionality". We propose an easily implementable conditional maximum score estimator. The asymptotic properties of the proposed estimator are fully characterized. A small-scale Monte Carlo study demonstrates that our approach performs satisfactorily in finite samples. We illustrate the usefulness of our method by presenting an empirical application to enrollment in private hospital insurance using the Household, Income and Labour Dynamics in Australia (HILDA) Survey data.

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55
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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
1Ouyang, F. and T. T. Yang (2024) Semiparametric Estimation of Dynamic Binary Choice Panel Data Models self0.96510590%
2Manski, C (1987) Semiparametric Analysis of Random Effects Linear Models from Binary Panel Data0.96510490%
3Honoré, B. and E. Kyriazidou (2000) Panel Data Discrete Choice Models with Lagged Dependent Variables0.956321088%
4Horowitz, J (1992) A Smoothed Maximum Score Estimator for the Binary Response Model0.92843100%
5Lee, S. M. S. and M. C. Pun (2006) On $m$ out of $n$ bootstrapping for nonstandard M-estimation with nuisance parameters0.87472100%
6Andrews, D. and M. Schafgans (1998) Semiparametric Estimation of the Intercept of a Sample Selection Model0.87462100%
7Seo, M. H. and T. Otsu (2018) Local M-estimation with discontinuous criterion for dependent and limited observations0.6939433%
8Fox, J. T (2007) Semiparametric estimation of multinomial discrete-choice models using a subset of choices0.64422100%
9Yan, J. and H. I. Yoo (2019) Semiparametric estimation of the random utility model with rank-ordered choice data0.64422100%
10Chamberlain, G (1986) Asymptotic efficiency in semi-parametric models with censoring0.64422100%

Showing the top 10 of 71 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
1Transition Probabilities and Moment Restrictions in Dynamic Fixed Effects Logit Models0.40511
2Robust Analysis of Short Panels0.40511