A MULTIVARIATE TIME-SERIES ANALYSIS OF SOME FLOUR PRICE DATA

In this paper we develop and compare several multivariate models for some multiple time series data. The data are indices of the price of flour at three sites in the USA and have been used for illustration in a recent methodological paper. The models all come from the vector autoregressive moving average class so that comparisons between them can easily be made using criteria such as Akaike's information criterion. It is particularly interesting to compare the models produced by relatively complicated model specification procedures with those developed by using more straightforward techniques to see whether we gain any worthwhile improvements in fit.