Structural Modeling in Marketing: Review and Assessment

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Structural Workshop Paper - Discrete-Choice Models of Consumer Demand in Marketing (2011, result): “…in history will help identify causality, but this will almost surely result in a poorer t relative to a model that exploits all the variation in past history; thereby reducing forecasing ability. tive consumer preferences (see Chintagunta et al. 2006; Reiss and Wolak 2007 for recent discussions).”
Empirical Entry Games with Complementarities: An Application to the Shopping Center Industry (2012, methodology): “In order to identify non-parametrically the payoffs Πi in (12), we need to impose cross-equation restrictions (a.”
Marketing's Impact on Firm Value: Generalizations from a Meta-Analysis (2016, background): “A key assumption of many structural models is that firms behave optimally (i.e., they maximize cash profit or the net present value of cash flows, respectively; e.g., Chintagunta et al. 2006).”
Handling Endogenous Regressors by Joint Estimation Using Copulas (2012, unknown): “The key concern with this approach is that incorrect specification of the supply-side model can lead to biased estimates of demand-side parameters (Chintagunta et al. 2006).”