arXiv Open Access 2021

Root-n-consistent Conditional ML estimation of dynamic panel logit models with fixed effects

Hugo Kruiniger
Lihat Sumber

Abstrak

In this paper we first propose a root-n-consistent Conditional Maximum Likelihood (CML) estimator for all the common parameters in the panel logit AR(p) model with strictly exogenous covariates and fixed effects. Our CML estimator (CMLE) converges in probability faster and is more easily computed than the kernel-weighted CMLE of Honoré and Kyriazidou (2000). Next, we propose a root-n-consistent CMLE for the coefficients of the exogenous covariates only. We also discuss new CMLEs for the panel logit AR(p) model without covariates. Finally, we propose CMLEs for multinomial dynamic panel logit models with and without covariates. All CMLEs are asymptotically normally distributed.

Topik & Kata Kunci

Penulis (1)

H

Hugo Kruiniger

Format Sitasi

Kruiniger, H. (2021). Root-n-consistent Conditional ML estimation of dynamic panel logit models with fixed effects. https://arxiv.org/abs/2103.04973

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓