Price dispersion and bargain hunting in the macroeconomy.

AuthorKaplan, Greg

In macroeconomic models, product markets are typically very simple. Consumers are treated as price-takers while firms trade against fixed demand curves. There is little that either households or firms can do to affect the terms of trade that they face in product markets.

But in reality there are many actions that buyers can take to influence the prices they pay. For example, in the retail market, households can pay more attention to price comparisons, travel to different stores, visit stores more frequently, switch brands, buy in bulk, or use coupons. In the wholesale market, firms can devote more resources to negotiating purchasing contracts or to exploring alternative suppliers. I refer to these actions collectively as bargain hunting. Similarly, sellers can take actions to alter the effective elasticity of demand that they face--for example, by expanding their presence in product markets through advertising, introducing new products, entering new geographic or demographic markets, or investing in long-term customer acquisition.

My research, carried out with a number of collaborators, has explored the implications of exerting effort in product markets for the behavior of the macroeconomy, both empirically and theoretically.

Different People, Different Prices

Bargain hunting presupposes that it is actually possible for a buyer to purchase the same product at more than one price. And if bargain hunting is indeed going on, then we should expect to see buyers differ in the prices they ultimately pay, in a way that is correlated with the effort they exert. A good area to start investigating bargain hunting is among final consumers in retail markets, because of the availability of detailed data on retail prices and house-hold shopping behavior. Guido Menzio and I built on a long literature documenting price dispersion among identical goods by conducting a comprehensive investigation into the nature of price dispersion in the retail sector, with a view to relating this dispersion to bargain hunting. (1)

[FIGURE 1 OMITTED]

Consistent with previous studies, we confirmed that price distributions for identical goods (as defined by their bar codes) in a given geographic market and time period, are highly dispersed; on average the standard deviation of log prices is around 20 percent. However, perhaps surprisingly, only a small fraction of this dispersion arises because some stores are more expensive than other stores. We can infer this because our scanner data allows us to observe the same store selling lots of different goods, the same good sold at lots of different stores, and the same good being sold at the same store in many different transactions. Most of the observed dispersion in prices actually takes place within stores. About half is due to a transaction component that captures both temporal variation in the price of a good at a given store due to temporary sales and other price changes and the fact that not all customers pay the same price for the same good on the same day because, for example, some use coupons or loyalty cards. The other half is due to persistent differences in the prices charged for a given product across stores that are equally expensive on average.

We refer to this latter component as relative price dispersion; in a follow-up paper with Nicholas Trachter and Leena Rudanko, we confirmed its existence using a much larger scanner dataset and more systematic methods. (2) We borrowed our empirical approach from labor economics, decomposing price distributions into components with different dynamic properties. This allowed us to measure how much of within-store price dispersion is due to temporal variation, like sales, and how much is due to persistent price differences. An important feature of relative price dispersion is that it implies asymmetries in the average price of different goods at different...

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