Making Sense of Ignoring Cents: Price Points and Price Rigidity under Rational Inattention

We explore the relationship between price points and price rigidity using two datasets. One is a large weekly transaction price data set, covering 29 product categories over an eight-year period from a large Midwestern United States supermarket chain. The other comes from the Internet and includes daily prices over a two-year period for a variety of consumer electronic products with a wide range of prices, such as music CDs, digital cameras, DVD players, notebook PCs, etc. Across the two datasets, we find that overall “9” is the most frequently used for the penny, dime, dollar and the ten-dollar digits, and that the most common price changes are those that keep the terminal digits at 9 (e.g., multiples of dimes, dollars, etc). More importantly, when we econometrically estimate the contribution of price points to price rigidity, we find that overall 9ending prices are at least 24% less likely to change in comparison to the prices ending with other digits. This level of price point rigidity is robust across the wide variety of price levels, product categories, retail formats and retailers examined in this study. To explain the phenomenon of 9ending prices and their link to price rigidity, we extend the implications of the theory of rational inattention to individual price dynamics. We argue that the practice of 9-ending pricing may be an equilibrium outcome of firms’ reaction to their customers’ rational inattention to the rightmost digits of a price. An additional implication of rational inattention is that the popularity of 9endings might vary across different channels depending on the degree of rational inattention by consumers in a particular channel. For example, it predicts that 9-ending should be more popular among bricks-and-clicks stores and less so among pure Internet retailers, as the Internet affords customers the opportunity to be rationally more attentive about prices because of lower search costs. We find that our Internet data are consistent with this prediction. We conclude by discussing the macroeconomic, business, and information systems (IS) implications of our findings.