Marketing applications offer many difficult and unique challenges in causal inference. In particular, targeted marketing activities, the arch-typical example of is search ads, can be difficult to evaluate using purely observational data. I review causal methods proposed in the recent...

We analyze the initial conditions bias in the estimation of brand choice models with structural state dependence. Using a combination of Monte Carlo simulations and empirical case studies of shopping panels, we show that popular, simple solutions that mis-specify the initial conditions are...

Ultimately, patents have value to the extent to which the product features enabled by the patents have economic value in the marketplace. That is, products which are enhanced by inclusion of patented features should generate incremental profits to the firm offering the enhanced product. Measures...

We discuss our experiences teaching Bayesian Statistics to students in doctoral programs in business. These students often have weak backgrounds in mathematical statistics and a predisposition against likelihood-based methods stemming from prior exposure to econometrics. This can be overcome by...

This monograph provides a review of choice models in marketing from the perspective of a utility maximizing consumer subject to budgetary restrictions. Marketing models of choice have undergone many transformations over the last 20 years, and the advent to hierarchical Bayes models indicate that...

We review applications of Bayesian methods to marketing problems. Key aspects of marketing applications include the discreteness of response or outcome data and relatively large numbers of cross-sectional units, each with possibly low information content. The use of informative priors including...

The quantity of any good demanded by consumers is dependent on the attributes and benefits of an offering, the rate at which marginal utility of the offering decreases, and the availability of substitutes. Traditional conjoint models focus on attributes and benefits, but have not incorporated...

Sales response models are widely used as the basis for optimizing the marketing mix or for allocation of the sales force. Response models condition on the observed marketing mix variables and focus on the specification of the distribution of observed sales given marketing mix activities. These...