Dr Hugo Kruiniger hugo.kruiniger@durham.ac.uk
Associate Professor
Further results on the estimation of dynamic panel logit models with fixed effects
Kruiniger, Hugo
Authors
Abstract
Kitazawa (2013, 2016) showed that the common parameters in the panel logit AR(1) model with strictly exogenous covariates and fixed effects are estimable at the root-n rate using the Generalized Method of Moments. Honoré and Weidner (2020) extended his results in various directions: they found additional moment conditions for the logit AR(1) model and also considered estimation of logit AR(p) models with p>1. In this note we prove a conjecture in their paper and show that for given values of the initial condition, the covariates and the common parameters 2^{T}-2T of their moment functions for the logit AR(1) model are linearly independent and span the set of valid moment functions, which is a 2^{T}-2T-dimensional linear subspace of the 2^{T}-dimensional vector space of real valued functions over the outcomes y element of {0,1}^{T}. We also prove that when p=2 and T element of {3,4,5}, there are, respectively, 2^{T}-4(T-1) and 2^{T}-(3T-2) linearly independent moment functions for the panel logit AR(2) models with and without covariates.
Citation
Kruiniger, H. (2020). Further results on the estimation of dynamic panel logit models with fixed effects
Online Publication Date | Feb 3, 2023 |
---|---|
Publication Date | 2020 |
Deposit Date | Feb 28, 2023 |
Publicly Available Date | Feb 28, 2023 |
Public URL | https://durham-repository.worktribe.com/output/1167543 |
Publisher URL | https://doi.org/10.48550/arXiv.2010.03382 |
Files
Accepted Working Paper
(143 Kb)
PDF
You might also like
Large sample properties of GMM estimators under second-order identification
(2023)
Working Paper
Estimation of dynamic panel data models with a lot of heterogeneity
(2021)
Journal Article
Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions
(2013)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search