Forecasting sales response for multiple time horizons and temporally aggregated data: A comparison of constant and stochastic coefficient models

Past research on time-varying sales-response models emphasized the application of different estimation techniques in examining variation in advertising effectiveness over time. This study focuses on comparing sales forecasts using constant and stochastic coefficients sales-response models. Selected...

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Bibliographic Details
Published in:International journal of forecasting 1987, Vol.3 (3), p.479-488
Main Authors: Yokum, J.Thomas, Wildt, Albert R.
Format: Article
Language:English
Subjects:
Accuracy
Effectiveness
Forecasting
Forecasting evaluation
Forecasting models
Forecasting techniques
Sales forecasting
Studies
Time-varying coefficients
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Summary:Past research on time-varying sales-response models emphasized the application of different estimation techniques in examining variation in advertising effectiveness over time. This study focuses on comparing sales forecasts using constant and stochastic coefficients sales-response models. Selected constant and stochastic coefficient models are applied to six sets of bimonthly and one set of annual advertising and sales data to assess forecasting accuracy for time horizons of various lengths. Results show improved forecasting accuracy for a first-order autoregressive stochastic coefficient model, particularly in short-run forecasting applications.
ISSN:0169-2070
1872-8200
DOI:10.1016/0169-2070(87)90044-6