Econometrics Seminar Series. Identification of Dynamic Panel Logit Models with Fixed Effects

Published: 6 November 2023

24 November. Dr Jiaying Gu, University of Toronto

Dr Jiaying Gu, University of Toronto

"Identification of Dynamic Panel Logit Models with Fixed Effects"
Friday, 24 November 2023. 11:30 am
Online

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Abstract

We show that the identification problem for a class of dynamic panel logit models with fixed effects has a connection to the truncated moment problem in mathematics. We use this connection to show that the sharp identified set of the structural parameters is characterized by a set of moment equality and inequality conditions. This result provides sharp bounds in models where moment equality conditions do not exist or do not point identify the parameters. We
also show that the sharp identified set of the non-parametric latent distribution of the fixed
effects is characterized by a vector of its generalized moments, and that the number of moments grows linearly in T. This final result lets us point identify, or sharply bound, specific classes of functionals, without solving an optimization problem with respect to the latent distribution. We illustrate our identification result with several examples, and an empirical application on modeling children’s respiratory conditions.

Bio

Jiaying Gu is the Associate Professor of Economics at University of Toronto. Her research interest includes empirical Bayes method, panel data unobserved heterogeneity, counterfactual analysis and partial identification.


For further information, please contact business-school-research@glasgow.ac.uk

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First published: 6 November 2023

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