In this chapter we extend the concept of serial correlation common features
to panel data models. This analysis is motivated both by the need to devel
op a methodology to systematically study and test for common structures and
comovements in panel data with autocorrelation present and by an increase
in efficiency coming from pooling procedures. We propose sequential resting
procedures and study their properties in a small scale Monte Carlo analysi
s. Finally: we apply the framework to the well known permanent income hypot
hesis for 22 OECD countries, 1950-1992.