Karsten T. Hansen

The Option Value of Returns: Theory and Empirical Evidence

When a firm allows the return of previously purchased merchandise, it provides customers with an option that has measurable value. Whereas the option to return merchandise leads to an increase in gross revenue, it also creates additional costs. Selecting an optimal return policy requires balancing both demand and cost implications. In this paper, we develop a structural model of a consumers decision to purchase and return an item that nests extant choice models as a special case. The model enables a firm to both measure the value to consumers of the return option and balance the costs and benefits of different return policies. We apply the model to a sample of data provided by a mail-order catalog company. We find considerable variation in the value of returns across customers and categories. When the option value is large, there are large increases in demand. For example, the option to return womens footwear is worth an average of more than

Channel Pass-Through of Trade Promotions

15 per purchase to customers and increases average purchase rates by more than 50%. We illustrate how the model can be used by a retailer to optimize his return policies across categories and customers.

Adjusting for Publication Bias in Meta-Analysis: An Evaluation of Selection Methods and Some Cautionary Notes

Packaged goods manufacturers spend in excess of

Market Structure Across Retail Formats

75 billion annually on trade promotions, even though their effectiveness has been hotly debated by academics and practitioners for decades. One reason for this ongoing debate is that empirical research has been limited mostly to case studies, managerial surveys, and data from one or two supermarket chains in a single market. In this paper, we assemble a unique data set containing information on prices, quantities, and promotions throughout the entire channel in a category. Our study extends the empirical literature on pass-through in three important ways. First, we investigate how pass-through varies across more than 1,000 retailers in over 30 states. Second, we study pass-through at multiple levels of the distribution channel. Third, we show how the use of accounting metrics, such as average acquisition cost, rather than transaction cost, yields biased estimates of pass-through and therefore overstates the effectiveness of trade promotions. We find that mean pass-through elasticities are 0.71, 0.59, and 0.41, for the wholesaler, retailer, and total channel, respectively. More importantly, at each level of the channel we observe large variances in pass-through estimates that we explain using various measures of cost and competition. Surprisingly, we find that market structure and competition have a relatively small impact on pass-through. We conclude by showing how the profitability of manufacturer and wholesaler deals can be improved by utilizing detailed effectiveness estimates. For example, a manufacturer using an inclusive trade promotion strategy might offer a 10% off invoice deal to all retailers on every product. This strategy would decrease manufacturer and wholesaler profits for 56% of product/store combinations, whereas retailers experience a profit boost in 96% of cases. Manufacturers and wholesalers can avoid unprofitable trade deals for specific products and retailers by utilizing estimates of pass-through, consumer price elasticity, and margins. Compared to the inclusive strategy, such a selective trade promotion strategy would improve deal profitability by 80% and reduce costs by 40%.

Outsourcing Retail Pricing to a Category Captain: The Role of Information Firewalls

We review and evaluate selection methods, a prominent class of techniques first proposed by Hedges (1984) that assess and adjust for publication bias in meta-analysis, via an extensive simulation study. Our simulation covers both restrictive settings as well as more realistic settings and proceeds across multiple metrics that assess different aspects of model performance. This evaluation is timely in light of two recently proposed approaches, the so-called p-curve and p-uniform approaches, that can be viewed as alternative implementations of the original Hedges selection method approach. We find that the p-curve and p-uniform approaches perform reasonably well but not as well as the original Hedges approach in the restrictive setting for which all three were designed. We also find they perform poorly in more realistic settings, whereas variants of the Hedges approach perform well. We conclude by urging caution in the application of selection methods: Given the idealistic model assumptions underlying selection methods and the sensitivity of population average effect size estimates to them, we advocate that selection methods should be used less for obtaining a single estimate that purports to adjust for publication bias ex post and more for sensitivity analysis—that is, exploring the range of estimates that result from assuming different forms of and severity of publication bias.

Estimating distributions of treatment effects with an application to the returns to schooling and measurement of the effects of uncertainty on college choice

We study how market structure within a product category varies across retail formats. Building on the literature on internal market structure, we estimate a joint store and brand choice model where the loading matrix of brand attributes are allowed to be retail format specific. The approach allows us to recover brand maps for different retail formats while controlling for the short-term marketing mix activities at these stores and the self-selection of households that frequent a particular format. The model is applied to consumer panel data from two product categories, where households are observed to make purchases across three store types: high-end grocery store, traditional supermarket, and large everyday low pricing (EDLP) formats. Our results show strong correlations between the marketing mix sensitivities, store format preference, and unobserved brand attributes. These correlations translate into significant differences in market structure across retail formats and in the direction and size of preference vectors for unobservable brand attributes. We find a tight clustering of brands at the EDLP format, whereas brands are found to compete in distinct subgroups at other stores. Results show that failure to account for retail format effects can substantially bias the understanding of underlying market structure and could lead to incorrect implications in applications such as new product entry.

2001 Lawrence R. Klein Lecture Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice

It has been argued that retailers lack both the resources and capabilities to maximize category performance. Retailers may seek category management CM advice from a manufacturer, referred to as a category captain CC. A CCs recommendations affect all brands in the category, not just her own. Despite an increase in the number of CC collaborations, retailers are still concerned about manufacturer opportunism and militant behavior by manufacturers not selected as CCs, whereas government agencies are worried about anticompetitive behavior that could harm consumers. The Federal Trade Commission recommends strictly enforced information firewalls within a CCs organization as a best-practice guideline. In this study we develop an empirical model and use policy simulations to quantify the impact of CC arrangements with information firewalls on retailers, manufacturers, and consumers. We show how these effects could be influenced by the deactivation of vertical and horizontal information firewalls within the CCs organization.