Efficiency of QMLE for dynamic panel data models with interactive effects

Fuente: arXiv
Saved in:
Bibliographic Details
Main Author: Bai, Jushan
Format: Preprint
Published: 2023
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866915338462953472
author Bai, Jushan
author_facet Bai, Jushan
contents This paper studies the problem of efficient estimation of panel data models in the presence of an increasing number of incidental parameters. We formulate the dynamic panel as a simultaneous equations system, and derive the efficiency bound under the normality assumption. We then show that the Gaussian quasi-maximum likelihood estimator (QMLE) applied to the system achieves the normality efficiency bound without the normality assumption. Comparison of QMLE with the fixed effects approach is made.
format Preprint
id arxiv_https___arxiv_org_abs_2312_07881
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Efficiency of QMLE for dynamic panel data models with interactive effects
Bai, Jushan
Econometrics
This paper studies the problem of efficient estimation of panel data models in the presence of an increasing number of incidental parameters. We formulate the dynamic panel as a simultaneous equations system, and derive the efficiency bound under the normality assumption. We then show that the Gaussian quasi-maximum likelihood estimator (QMLE) applied to the system achieves the normality efficiency bound without the normality assumption. Comparison of QMLE with the fixed effects approach is made.
title Efficiency of QMLE for dynamic panel data models with interactive effects
topic Econometrics
url https://arxiv.org/abs/2312.07881