Dynamic simulation models of gas pipeline networks can be used for on-line applications such as state estimation, leak detection, etc. A prime requirement for such models is computational efficiency. In this paper, a transfer function model of a gas pipeline is used as a basis for developing a dynamic simulator for gas pipeline networks. The simulator is incorporated in a data reconciliation framework, which is ideally suited for on-line state estimation based on all available measurements of pressures and flow rates. The American Gas Association (AGA) model is used for making realistic computations of the gas compressibility. Accuracy and computational efficiency of the proposed method are evaluated by comparing our results with those obtained using a fully nonlinear second-order accurate finite difference method. The ability of the proposed approach for obtaining accurate state estimation from noisy measurements is demonstrated through simulations on an example network. We also demonstrate the use of the proposed approach for estimating an unknown demand at any node by exploiting the redundancy in measurements.