Unit root inference in panel data models where the time‐series dimension is fixed: a comparison of different tests

Abstract

Summary The objective of the paper is to investigate and compare the performance of some of the unit root tests in micropanels, which have been suggested in the literature. The framework is a first-order autoregressive panel data model allowing for heterogeneity in the intercept but not in the autoregressive parameter. The tests are all based on usual t-statistics corresponding to least squares estimators of the autoregressive parameter resulting from different transformations of the observed variables. The performance of the tests is investigated and compared by deriving the local power of the tests when the autoregressive parameter is local-to-unity. The results show that the assumption concerning the initial values is extremely important in this matter. The outcome of a simulation experiment demonstrates that the local power of the tests provides a good approximation to their actual power in finite samples.