An Exponential Class of Dynamic Binary Choice Panel Data Models with Fixed Effects

Al-Sadoon, Majid M.; Li, Tong; Pesaran, M. Hashem

doi:10.2139/ssrn.2720447

Cited by 3 publications

(2 citation statements)

References 41 publications

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“…For the FE case, as previously noted, there are several proposed approaches (see Hsiao 2014) for estimating this FE model, including Honoré and Kyriazidou (2000), Bartolucci and Nigro (2010;2012), Al-Sadoon et al (2017. In a large-N-large-τ setting, controlling for the fixed effects using a comprehensive set of dummy variables is theoretically an option but not much used in practice.…”

Section: Autoregressive Dependencementioning

confidence: 99%

Econometric Models of Fertility

Miranda¹,

Trivedi²

2020

SSRN Journal

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Section: Autoregressive Dependencementioning

confidence: 99%

Econometric Models of Fertility

Miranda¹,

Trivedi²

2020

SSRN Journal

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“…Or, alternatively, change the model as inBartolucci and Nigro (2010) andAl-Sadoon, Li, and Pesaran (2017).…”

mentioning

confidence: 99%

Moment Conditions for Dynamic Panel Logit Models with Fixed Effects

Honoré

Weidner

2020

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This paper builds on Bonhomme (2012) to develop a method to systematically construct moment conditions for dynamic panel data logit models with fixed effects. After introducing the moment conditions obtained in this way, we explore their implications for identification and estimation of the model parameters that are common to all individuals, and we find that those common model parameters are estimable at root-n rate for many more dynamic panel logit models than has been appreciated by the existing literature. In the case where the model contains one lagged variable, the moment conditions in Kitazawa (2013Kitazawa ( , 2016 are transformations of a subset of ours. A GMM estimator that is based on the moment conditions is shown to perform well in Monte Carlo simulations and in an empirical illustration to labor force participation.

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Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models

Arellano

Bonhomme

2017

Annu. Rev. Econ.

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Recent developments in nonlinear panel data analysis allow identifying and estimating general dynamic systems. In this review we describe some results and techniques for nonparametric identification and flexible estimation in the presence of time-invariant and time-varying latent variables. This opens the possibility to estimate nonlinear reduced forms in a large class of structural dynamic models with heterogeneous agents. We show how such reduced forms may be used to document policy-relevant derivative effects, and to improve the understanding and facilitate the implementation of structural models. JEL code: C23.

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An Exponential Class of Dynamic Binary Choice Panel Data Models with Fixed Effects

Cited by 3 publications

References 41 publications

Econometric Models of Fertility

Econometric Models of Fertility

Moment Conditions for Dynamic Panel Logit Models with Fixed Effects

Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models

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