The ready-to-eat cereal industry is characterized by high concentration, high price-cost margins, large advertising-to-sales ratios, and numerous introductions of new products. Previous researchers have concluded that the ready-to-eat cereal industry is a classic example of an industry with nearly collusive pricing behavior and intense nonprice competition. This paper empirically examines this conclusion. In particular, I estimate price-cost margins, but more importantly I am able empirically to separate these margins into three sources: (i) that which is due to product differentiation; (ii) that which is due to multi-product firm pricing; and (iii) that due to potential price collusion. The results suggest that given the demand for different brands of cereal, the first two effects explain most of the observed price-cost margins. I conclude that prices in the industry are consistent with noncollusive pricing behavior, despite the high price-cost margins. Leading firms are able to maintain a portfolio of differentiated products and influence the perceived product quality. It is these two factors that lead to high price-cost margins.

This paper examines the construction of a price index based on an estimated-demand system. In principle the method examined can produce a price index that takes account of the introduction of new products and quality changes in existing products. However, I isolate two key assumptions that have to be made in order to interpret the demand estimates into welfare measures. Using estimates of a brand-level demand system for ready-to-eat cereal, I demonstrate the empirical importance of the assumptions. For the data I use, depending on the interpretation of the demand estimates, a price index can range between a 35% increase over the five years examined to a 2.4% decrease.

Temporary price reductions (sales) are common for many goods and naturally result in large increases in the quantity sold. Demand estimation based on temporary price reductions may mismeasure the long run responsiveness to prices. In this paper we quantify the extent of the problem and assess its economic implications. We structurally estimate a dynamic model of consumer choice using two years of scanner data on the purchasing behavior of a panel of households. The results suggest that static demand estimates, which neglect dynamics: (i) overestimate own price elasticities by 30 percent; (ii) underestimate cross-price elasticities to other products by up to a factor of 5; and

We study intertemporal price discrimination when consumers can store for future consumption needs. We offer a simple model of demand dynamics, which we estimate using market-level data. Optimal pricing involves temporary price reductions that enable sellers to discriminate between price sensitive consumers, who stockpile for future consumption, and less price-sensitive consumers, who do not stockpile. We empirically quantify the impact of intertemporal price discrimination on profits and welfare. We find that sales (i) capture 25–30 percent of the gap between non-discriminatory profits and (unattainable) third-degree price discrimination profits, (ii) increase total welfare, and (iii) have a modest impact on consumer welfare.

Food purchases differ substantially across countries. We use detailed household-level data from the United States, France, and the United Kingdom to (i) document these differences; (ii) estimate a demand system for food and nutrients; and (iii) simulate counterfactual choices if households faced prices and nutritional characteristics from other countries. We find that differences in prices and characteristics are important and can explain some difference (e.g., United States–France difference in caloric intake) but generally cannot explain many of the compositional patterns by themselves. Instead, it seems an interaction between the economic environment and differences in preferences is needed to explain cross-country differences.