The recent blossoming of panel econometrics in general and panel time-series methods in particular has enabled many more research questions to be investigated than before. However, this development has not assuaged serious concerns over the lack of diagnostic testing procedures in panel econometrics, in particular vis-a-vis the prominence of such practices in the time-series domain: the recent introduction of residual cross-section independence tests aside, within mainstream panel empirics the combination of 'model', 'specification' and 'testing' typically refers to the distinction between fixed and random effects, as opposed to a rigorous investigation of residual properties. In this paper we investigate these issues in the context of non-stationary panels with multifactor error structure, employing Monte Carlo simulations to investigate the distributions and rejection frequencies for standard time-series diagnostic procedures, including tests for residual autocorrelation, ARCH, normality, heteroskedasticity and functional form.
