Testing for panel unit roots in the presence of spatial dependency

Abstract

In this article, the size and power properties of the Common-factor Im, Pesaran and Shin (CIPS), Wald (W), Likelihood Ratio (LR) and Lagrange Multiplier (LM) tests are investigated when the error term follows a spatial error model. In this study, the results from the Monte Carlo simulations, first, show that the CIPS test over-estimates the nominal size. Second, the simulation results show that the empirical size of the W test approaches the nominal size quickly, while the LR and LM tests underestimate the null hypothesis in both small and moderate sample sizes. Finally, the results also show that even though the LM and LR tests under-reject the true-null hypothesis they have higher power than the W test.

Keywords:

• panel data
• unit root tests
• spatial dependency
• Monte Carlo simulations

JEL Classification::

• C12
• C22
• C33