Abstract
The temporal stability of estimated parameters in multiple regression marketing models is important if the model is to prove useful in making economic inferences and in developing marketing strategies. OLS estimates are potentially distorted in the presence of collinear data sets that typify marketing models; consequently, any underlying temporal stability present may go undetected. This paper investigates the temporal stability of parameter estimates by comparing the results obtained from OLS, ridge, and latent root regression techniques in the presence of ill-conditioned data. Ridge regression provided improved individual coefficient stability and slightly greater predictive accuracy beyond the original estimation period.
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Keywords
- Ordinary Little Square
- Latent Vector
- Ridge Regression
- Ordinary Little Square Estimate
- Ordinary Little Square Estimator
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© 2015 Academy of Marketing Science
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Moore, J.S., Shipchandler, Z.E. (2015). Alternative Approaches for Examining the Temporal Stability of Parameter Estimates in a Marketing Model. In: Malhotra, N. (eds) Proceedings of the 1986 Academy of Marketing Science (AMS) Annual Conference. Developments in Marketing Science: Proceedings of the Academy of Marketing Science. Springer, Cham. https://doi.org/10.1007/978-3-319-11101-8_88
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DOI: https://doi.org/10.1007/978-3-319-11101-8_88
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