Estimation of Nonlinear Dynamic Panel Data Models with Individual Effects

Abstract EN

This paper suggests a generalized method of moments (GMM) based estimation for dynamic panel data models with individual specific fixed effects and threshold effects simultaneously.

We extend Hansen’s (Hansen, 1999) original setup to models including endogenous regressors, specifically, lagged dependent variables.

To address the problem of endogeneity of these nonlinear dynamic panel data models, we prove that the orthogonality conditions proposed by Arellano and Bond (1991) are valid.

The threshold and slope parameters are estimated by GMM, and asymptotic distribution of the slope parameters is derived.

Finite sample performance of the estimation is investigated through Monte Carlo simulations.

It shows that the threshold and slope parameter can be estimated accurately and also the finite sample distribution of slope parameters is well approximated by the asymptotic distribution.