A Comparison of Time-Varying Parameter and Multiprocess Mixture Models in the Case of Money-Supply Announcements
比较了多过程混合模型和随机游走时变参数模型在利率与周货币供给关系中的表现，发现混合模型能更好处理体制转换和异常值，而时变参数模型表现不佳。
This study compares the performance of a recently proposed multiprocess mixture model and a random-walk time-varying parameter (TVP) model, using the interest rate–weekly money relationship for illustrative purposes. For the case of this relationship, which is subject to regime shifts and outliers, the mixture model performs well and the latter model performs poorly. This finding is of general interest, since investigators often adopt random-walk TVP models to accommodate potential regime shifts in regression relationships. The TVP estimation procedure is unlikely to find abrupt shifts, since the estimate of parameter variance is based on the entire data sample. In the face of rapid discontinuous shifts in the parameters, this variance estimate is unrepresentative of the variability during periods of abrupt shift or transient observations.