In this paper we propose a new approach to the problem of structural change from a Bayesian point of view. Our approach is based on a hierarchical model with a Dirichlet process prior. A notable feature of the Dirichlet process is its discreteness which is useful for detecting structural...

In this final article of our three-part series, we demonstrate why stochastic coefficients models are well suited to predict future variables We analyze the forecasting problem and consider various criteria of prediction If a forecaster must choose one from among several coherent predictors,...

A general stochastic coefficients model developed by Swamy and Tinsley serves as a reference point for discussion in this second of a series of three articles Other well-known specifications are related to the model. The authors weigh the advantages and disadvantages of stochastic coefficients...

We investigate the construction of more precise estimates of a collection of population means using information about a related variable in the context of repeated sample surveys. The method is illustrated using poll results concerning presidential approval rating (our related variable is...