A Comparison of Time-Varying Parameter and Multiprocess Mixture Models in the Case of Money-Supply Announcements

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.     

Rule-governed behavior and human behavioral pharmacology: A brief commentary on an important topic

Over 25 years ago, B. F. Skinner introduced the concept of rule-governed behavior, which is the topic of this commentary. To date, behavioral pharmacologists have given rule-governed behavior little consideration in their analyses of drug action. There are, however, published studies that demonstrate the importance of rule-governed behavior in modulating drug effects in humans. Rule-governed behavior may help to explain differences in drug self-administration in humans and nonhumans and, in humans, differences in drug effects across individuals and situations. This commentary suggests that rule-governed behavior merits further attention in the context of human behavioral pharmacology, and posits that scientists who are experts in verbal behavior can make a unique contribution to the theoretical and experimental analysis of drug-related human behaviors, including drug abuse and its treatment.