Estimation and identification of change points in panel models with nonstationary or stationary regressors and error term

ABSTRACT

This article studies the estimation of change point in panel models. We extend Bai (2010) and Feng et al. (2009) to the case of stationary or nonstationary regressors and error term, and whether the change point is present or not. We prove consistency and derive the asymptotic distributions of the Ordinary Least Squares (OLS) and First Difference (FD) estimators. We find that the FD estimator is robust for all cases considered.

KEYWORDS:

• Change point
• consistency
• nonstationarity
• panel data

JEL CLASSIFICATION:

• C12
• C13
• C22

Acknowledgements

We would like to thank the Associate Editor and three referees for their helpful comments and suggestions.

Notes

¹In general, for any x_it with nonzero mean θ, the model in Eq. (1) can be rewritten as

where the new regressor is zero mean again. From the equation above, we can see that a change in the slope implies a change in the intercept, as long as the initial regressor x_it has nonzero mean.

²We thank a referee pointing this out.