Working Paper: NBER ID: w1446
Authors: Edward P. Lazear
Abstract: Sellers of new products are faced with having to guess demand conditions to set price appropriately. But sellers are able to adjust price over time and to learn from past mistakes. Additionally, it is not necessary that all goods be sold with certainty. It is sometimes better to set a high price and to risk no sale. This process is modeled to explain retail pricing behavior and the time distribution of transactions. Prices start high and fall as afunction of time on the shelf. The initial price and rate of decline can be predicted and depends on thinness of the market, the proportion of customers who are "window shoppers," and other observable characteristics. In a simplecase, when prices are set optimally, the probability of selling the product is constant over time. Among the more interesting predictions is that women's clothes may sell for a higher average price than men's clothes, given similar cost, even in a competitive market. Another is that the initial price level and the rate of price decline are positively related to the probability of selling the good. Other observable relationships are discussed.
Keywords: Retail Pricing; Time Distribution; Clearance Sales
JEL Codes: D12; L81
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| initial price level (E30) | probability of selling a good (C25) |
| rate of price decline (E31) | probability of selling a good (C25) |
| initial price level and rate of price decline (E31) | probability of selling a good (C25) |
| gender-targeted pricing (J16) | consumer behavior (D19) |
| uniqueness of goods (L15) | pricing strategies (D49) |
| ability to adjust prices over time (D49) | pricing strategies (D49) |