It used to be that retail prices of generic products like coffee mugs, soap, etc., moved slowly. Not anymore. On major web retailers like Amazon, for a range of generic household products, the variation in prices over short periods of time is immense. For instance, on 12-Piece Porcelain, 12 Oz. Coffee Mug Set, the price ranged between $20.50 and $35.71 over the last year or so, with a hefty day-to-day variation.
On PCPartPicker, the variation in prices for Samsung SSD is equally impressive. Prices zig-zag on multiple sites (e.g., Dell, Adorama) by $100 over a matter of days multiple times over the last six months. (The cross-site variation—price dispersion—at a particular point in time is also impressive.)
Take another example. Softsoap Liquid Hand Soap, Fresh Breeze – 7.5 Fl Oz (Pack of 6) shows a very high-frequency change between $7.44 and $11. (See also Irish Spring Men’s Deodorant Bar Soap, Original Scent – 3.7 Ounce.)
What explains the within-site over-time variation? One reason could be supply and demand. There are three reasons I am skeptical of the explanation. First, on Amazon, the third-party new item price time series and Amazon price time series do not appear to be correlated (statistics by informal inspection or as one of my statistics professors used to call it—the ocular distortion test—so caveat emptor). On PCPartPicker, you see much the same thing: the cross-retailer price time series frequently crossover. Second, related to the first point, we should see a strong correlation in overtime price curves across substitutes. We do not. Third, the demand for generic household products should be readily forecastable, and the optimal dry good storage strategy is likely not storing just enough. Further, I am skeptical of strong non-linearities in the marginal cost of furnishing an item that is not in the inventory—much of it should be easily replenishable.
The other explanation is price exploration, with Amazon continuously exploring the profit-maximizing price. But this is also unpersuasive. The range over which the prices vary over short periods of time is too large, especially given substitutes and absent collusion. Presumably, companies have thought about the negative consequences of such wide price exploration bands. For instance, you cannot build a reputation as the ‘cheapest’ (unless there is coordination or structural reason for prices to move together.)
So I come empty when it comes to explanations. There is the crazy algorithm theory—as inventory dwindles, Amazon really hikes the price, and when it sees no sales, it brings the price right back down. It may explain the frequent sharp movements over a fixed band that you see in some places but plausibly doesn’t explain a lot of the other patterns we see.
Forget the explanations and let’s engage with the empirical fact. My hunch is that customers are unaware of the striking variation in the prices of many goods. Second, if customers become aware of this, their optimal strategy would be to use sites like CamelCamelCamel or PCPartPicker to pick the optimal time for purchasing a good. If retailers are somehow varying prices to explore profit-maximizing pricing (minus price discrimination based on location, etc.), and if all customers adopt the strategy of timing the purchase, then, in equilibrium, the retailer strategy would reduce to constant pricing.
p.s. I found it funny that there are ‘used product’ listings for soap.
p.p.s. I wrote about the puzzle of price dispersion on Amazon here.