Biases in demand analysis due to variation in retail distribution

Aggregate demand models typically assume that consumers choose between all available products. Since consumers may be unwilling to search across every store in a given market for a particular item, this assumption is problematic when product assortments vary across stores. Using supermarket scanner data for five product categories we demonstrate that approximately one third of products have limited retail distribution, which account for one fourth of dollar sales. Monte Carlo analysis demonstrates that the level of limited product availability observed in the data can significantly bias the results of aggregate demand models that incorrectly assume all consumers in a given market face the same choice set.     

A diagrammatical template for business market demand estimation

This article describes a template that can help guide managers through a minefield of complex product interactions and demand drivers on the way to producing a realistic demand estimation. It is based on many years of consulting and conducting postmortems to find out what went wrong when demand forecasts have gone awry.A menu of troublesome variables that make up a rogue's gallery of the worst offending causes of estimation error are presented. The premise being, if we are aware of the potential trouble spots in demand estimation, we are likely to avoid some of the more serious problems that plague market projections.A diagrammatical template is presented that shows these troublesome variables and where they enter into the demand evaluation process. Next, the template components are introduced to show how the various product interactions and drivers that affect demand estimation are used and how they impact market projections. Throughout, a list of dos and don'ts are provided along with a sufficient number of real-life disaster stories to reinforce the issues.     

The choice at the checkout: Quantifying demand across payment instruments

Dramatic changes have occurred in the U.S. payment system over the past two decades, most notably an explosion in electronic card-based payments. This shift has led to a series of policy debates driven in part by consumers' choice of payment instruments. Using a new nationally representative survey, we transform consumer responses to open-ended questions into product rankings and estimate a characteristics-based rank-order logit model in order to quantify consumer substitution among payment methods. Our estimates are then used to conduct supply-driven and demand-driven counterfactual experiments in order to estimate market share and cost effects. From a counterfactual experiment in which merchants stop accepting credit cards, we predict merchant costs to decline substantially. Because merchants accept credit cards nonetheless, we regard our finding as evidence either that the credit card networks hold market power, or that merchants experience unmeasured intangible benefits from credit card acceptance. We also predict that contactless debit will take market share from cash, checks, and credit, and that the age/cohort effect alone is unlikely to cause debit card use to increase substantially over a 10-year period.     

Service-based capacity strategy for manufacturing service duopoly of differentiated prices and lognormal random demand

Globalization of production has ushered in vibrant manufacturing service industries whose business is to serve the production needs of product engineering firms. In these engineering–manufacturing chains, risk of capacity supply is an important concern for product firms as manufacturers are normally conservative in capacity expansion, especially when demand uncertainty and investment risk are high. To provide quality manufacturing services, this risk must be taken into consideration in formulating a capacity strategy. This paper presents a competition analysis method based on supply risk for a manufacturing duopoly of differentiated prices and lognormal random demand. A novel service-based demand rationing rule is first proposed. Reaction curves and equilibrium of capacity strategy are next derived. Finally, competition behavior of the duopoly is analyzed.     

Recovering markups from production data

In this paper, I discuss, what I call, the Production-Approach to recovering markups. In contrast to the most popular approach in empirical IO, which relies on demand estimation, this approach requires standard production data while allowing for various price-setting models and puts no restrictions on underlying consumer demand. Using production data together with standard cost minimization allows a researcher to obtain markups in a flexible way. After presenting a brief and selective overview of the literature I contrast the production approach to that of the more popular demand estimation approach. This discussion makes it clear that both approaches face important trade-offs and at a minimum empirical economist should have both techniques as part of their toolbox. The hope is that the use of both methods will only depend on the data at hand and the relevant institutional knowledge, paired with the actual research question we are trying to answer.     

Resale and bundling in auctions

The possibility of resale increases bidders' incentives to jointly reduce demand in multi-object auctions, because resale increases low-value bidders' willingness to pay and reduces high-value bidders' willingness to pay. Therefore, resale may reduce the seller's revenue. In a simple model with complete information, however, allowing resale and bundling the objects on sale are “complement strategies” for the seller (under reasonable conditions)—by bundling and allowing resale the seller earns a higher revenue than by selling the objects separately and/or forbidding resale. We also show why allowing resale may reduce efficiency.     

Recent progress in the empirical analysis of multi-unit auctions

I discuss some recent progress in the empirical analysis of multi-unit auctions, through which a number of important commodities (Treasury bills and bonds, electricity, emission permits, monetary infusions by some central banks) are allocated.     

Distribution contracts to support optimal inventory holdings under demand uncertainty

When suppliers produce products for which demand is uncertain, they face a problem of inducing downstream distributors to stock inventory levels that the suppliers prefer. This paper considers a wide array of alternative supply contracts, each of which consists of a mixture of constant per-unit wholesale prices, buy-back arrangements, and post sale payments contingent on sales made, such as revenue sharing or buybacks. We show that linear supply contracts specifying any combination of two of these three instruments can implement the vertical integrated outcome for a monopoly, thereby generating the supplier's preferred inventory configuration and price distribution. We extend our results to differentiated product oligopoly, demonstrating that each supplier obtains its preferred inventory configuration and price distribution, given the choices of its rival. Distributors choose optimal inventories from the suppliers' standpoint, even if suppliers do not know the distribution of demand uncertainty, and, given the perfect competition among distributors, all profits in the supply chain are captured by suppliers. Thus, suppliers are able to deal with demand uncertainty with remarkably little information about demand, and without the need to control dealer actions in detail. In particular, suppliers need not specify either dealer inventories or resale prices, but instead encourage distributors to order based on information in their possession and to set prices that generate desirable resale price dispersion.     

Using merger simulation models: Testing the underlying assumptions

Merger simulation is now widely used by economists to evaluate the likely competitive effects of a proposed merger. However, the reliability of a given merger simulation depends crucially on the reliability of the data used and the assumptions made. We discuss tests that can be used to assess the reliability of a merger simulation and show how these tests were applied in the context of the Volvo–Scania merger.