On estimation of two-dimensional dynamic panel model with confounders

Abstract

In this paper, motivated by a real data example about borderline overian tumors, we study a two-dimension dynamic panel models with confounding individual effect for modeling binary panel data. We propose using the maximum likelihood estimation method to estimate the model parameters. The properties of the maximum likelihood estimators are studied. The performance of the proposed estimation method is studied by using a Monte Carlo simulation study. The proposed model and estimation methods are illustrated by the real data example.

Keywords:

• Confounders
• Panel data
• Two-dimension dynamic models
• Maximum likelihood estimation

Acknowledgment

The authors thank the anonymous referee and the editor for their useful comments and suggestions on an earlier version of this manuscript which resulted in this improved version.

Additional information

Funding

The authors also thank the National Natural Science Foundation of China (11471068 and 11871141) and Jilin Education Department thirteen five-year plan project (JJKU20170338KJ) for their support.