Estimating three-dimensional nonlinear panel data models with interactive effects

ABSTRACT

This article considers two three-step estimation approaches to three-dimensional nonlinear panel data models with interactive effects correlated with the independent variables. We propose a Nonlinear Least Squares-Principal Component Analysis-Grid Search iterated approach to estimate the static model, and a GMM-PCA-GS iterated method to the dynamic model. Monte Carlo experiments examine the finite sample performance of the methods.

KEYWORDS:

• Three-dimensional panel data models
• smooth transition
• interactive effects
• NLS-PCA-GS
• GMM-PCA-GS

JEL CLASSIFICATION:

• C23
• C26
• C63

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This article was supported by fundamental research funds for South-Central University for Nationalities [grant number CZZ15005] and National Statistical Science Research Program [grant number 2015LY17].