| Abstract: | When time series data are available for both advertising and sales, it may be worth while to model the two series jointly. Such an analysis may contribute to our understanding of the dynamic relationships among the series and may improve the accuracy of forecasts. Multiple time series techniques are applied to the well-known Lydia Pinkham data to illustrate their use in modelling the advertising-sales relationship. In analysing the Lydia Pinkham data the need for a joint model is established and a bivariate model is identified, estimated and checked. Its forecasting properties are discussed and compared to other time series approaches. |
