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This paper presents a frame-level hybrid framework for modeling MPEG-4 and H.264 multi-layer variable bit rate (VBR) video traffic. To accurately capture long-range-dependent and short-range-dependent properties of VBR sequences, we use wavelets to model the distribution of I-frame sizes and a simple time-domain model for P/B frame sizes. However, unlike previous studies, we analyze and successfully model both inter-GOP (group of pictures) and intra-GOP correlation in VBR video and build an enhancement-layer model using cross-layer correlation. Simulation results demonstrate that our model effectively preserves the temporal burstiness and captures important statistical features (e.g., the autocorrelation function and the frame-size distribution) of original traffic. We also show that our model possesses lower complexity and has better performance than the previous methods in both single- and multi-layer sequences.