Visualization Tools for Time Series Model Selection

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Price indices that place quantity information on the same time scale as prices enable them to capture real-time phenomena such as substitutions, and evolving consumer preferences more generally. But, because BLS quantity information (obtained from households) comes with an approximately one-year lag, it is not possible to produce such an index until this year passes. To provide a timely statistic, BLS issues a preliminary version of the index, currently using a constant elasticity of substitution model. This approach applies a fixed level of substitution across all items, areas, and months. We propose instead to forecast the weights needed by the index via a seasonal multivariate time series model of item-area expenditure shares and incorporate the item-area prices, which are presumed to drive much of substitution behavior.

The choice of time series model and its parameters has a profound effect on the behavior of the index. Visualization plays an important role in this selection. To choose the model that best captures the dynamic consumer behavior underlying the changes in the index, graphs displaying how parameter choices affect the fit of the index are necessary.