Summary: Measurement-based traffic characterization has come to acquire a great deal of importance in high-speed networks. In this paper, we segregate the traffic behaviour into the macrodynamics and microdynamics depending on the time scales at which the process is observed. Our study compares the queueing solutions obtained using traffic models with very different underlying structure viz. Markovian vs non-Markovian which are identical only in their second-order and steady-state statistics. Our study suggests that higher-order traffic statistics are generally unimportant to queueing solutions. We also investigate the effect fo the microdynamics of the traffic on the queueing performance. The microdynamics are associated with the cell interarrival times and bulk arrivals. We show that the second-order statistics of the microdynamics are well captured by white noise in the arrival process power spectrum, which can have a significant impact on the queueing performance. A new modeling technique is introduced in which the microdynamics are incorporated into the correlation behaviour of traffic macrodynamics.