Abstract:
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We propose an econometric two-stage model for category-level purchase and brand-level purchase which allows simultaneous brand purchase at the same time for analysis of scanner panel data in marketing. The proposed model formulation is consistent with the traditional theory of consumer behavior, and the utility functions remain to be normally distributed. Such modeling approaches have not been found in existing econometric models. We conduct Bayesian estimation with Markov Chain Monte Carlo algorithm for our proposed model. The simulation studies show the previously proposed related models can cause severe bias in predicting the future brand choices, while the proposed method can e?ectively predict them. Additionally in real data analysis, while the existing methods provided the parameter estimation results that were implausible, the proposed method provided the results that were plausible. The proposed model gives the result that the regression coe?cient for price is negative while the existing methods give the result that the regression coe?cient for price is positive, which means that the result of the proposed method is easier to interpret.
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