The Importance of Loss Leaders in Pricing Decisions
Research by Anil Kashyap and Peter E. Rossi
Popular wisdom tells us that it's human nature to get
while the getting is good. Popular wisdom tells us this is
good financial practice as well. So when it comes to the world
of retail, it's no surprise that textbook economic theory
says that as demand for a product increases, so too should
its price. The surprise is that textbook economic theory is
wrong.
In fact, prices actually fall during periods of peak demand,
say University of Chicago Graduate School of Business professors
Anil Kashyap and Peter E. Rossi. In their recent study, "Why
Don't Prices Rise During Periods of Peak Demand? Evidence
From Scanner Data," Kashyap and Rossi, along with Judith
Chevalier of the Yale School of Management, argue that retailer
cuts to profit margins account for the drop in prices and
that advertising plays an important role in pricing.
Kashyap, Rossi, and Chevalier's findings show that consumers
get deals, for example, on tuna during Lent, beer over the
Fourth of July holiday, and snack crackers at Christmas-time
when those items are in high demand. Their findings also indicate
that because of imperfect competition, as opposed to a textbook
model, retailers follow a "loss leader" model of
pricing. This means that retailers spend a fixed amount to
advertise a select number of popular goods, lowering the prices
for those goods regardless of the overall shopping climate.
Cheap Tuna
To find out if pricing is truly counter-cyclical, Kashyap,
Rossi, and Chevalier drew on seven and a half years of weekly
store-level scanner data from Dominick's Finer Foods. Data
collection began in September 1989. Dominick's, the second-largest
supermarket chain in the Chicago metropolitan area, has approximately
100 stores and a market share of about 25 percent. The authors
chose to look at supermarket data because of the size of the
grocery/retailing sector (where sales totaled $435 billion
in 1999) and because the consumer-retailer interactions that
occur in grocery stores are similar to those in many other
types of purchases.
"The patterns we uncover are potentially relevant for
other parts of the economy," says Kashyap. "The
same model could apply to any industry that has high search
costs relative to what people are buying."
The authors then used climatological data from the National
Oceanic and Atmospheric Administration and the dates of holidays
to choose periods in which demand for particular goods is
likely to vary. The resulting shopping periods were "hot,"
"cold," Lent, Easter, Memorial Day, the Fourth of
July, Labor Day, Thanksgiving, the week after Thanksgiving,
and Christmas. Next, the authors grouped individual items
into aggregates and grouped aggregates into categories. Choosing
eleven categories, they decided to look at seasonal prices
for beer, "eating" soup, soup used in cooking, oatmeal,
tuna, snack crackers, regular crackers, cookies, cheese, analgesics,
and dish detergent.
Discovering a "pronounced tendency for retail prices
to be lower" at demand peaks for these categories of
items, the authors came up with two possible explanations:
marginal costs have seasonal patterns or markups move counter-cyclically
over the seasonal cycle. They ruled out the first hypothesis
by showing that while cooking soups and eating soups have
similar marginal costs, their pricing patterns are different.
They also found this to be true with regular crackers and
snack crackers. Moving forward with their second hypothesis,
the authors explored possible reasons for counter-cyclical
pricing.
Three Models of Competition
Kashyap, Rossi, and Chevalier considered three models of
imperfect competition that could generate counter-cyclical
pricing. The first looks at the cyclical elasticity of demand.
This theory claims that consumers decide which store to visit
based on the total purchase price of everything in their carts,
not the prices of individual items. Assuming that the cost
of searching for the lowest total price is fixed, consumers
are going to search more places when they are buying a large
number of goods, i.e. when overall demand is high. Prices
for consumer goods, then, should fall during high purchase
periods such as Christmas and weekends, when intensive shopping
takes place.
The second model suggests that firms tacitly collude when
assigning prices to goods. While this implicit agreement works
well under normal circumstances, temporary demand spikes tempt
individual retailers to break the agreement by lowering their
markups and dropping their prices. In doing so the retailers
would hope to capture a larger market share. As with the first
model, these price wars should occur when overall shopping
volume is high, because these times are when the most customers
are up for grabs.
Finally, the loss leader model gives advertising a role in
pricing, working on the assumptions that retailers must advertise
to inform customers about prices and that retailers pay a
fixed cost per ad. According to this model, it is efficient
for retailers to advertise (and commit to) a low price on
high-demand items, whether or not the aggregate volume of
shopping is high or low.
All three models predict that the prices of high-demand goods
will fall during high-demand periods. The main difference
is in their predictions for the behavior of retailer margins
for high-demand goods during low-demand periods. The loss
leader model is the only one to predict that retailer margins
will fall for a high-demand good even if the demand for all
other goods is low.
To decide among the theories, Kashyap, Rossi, and Chevalier
began by looking at holiday-sensitive goods. Defining retail
margins as price minus the wholesale cost, divided by price,
the authors found that the retail margins for such goods fall
during the holidays. Margins for cheese and snack crackers
drop significantly at Thanksgiving and Christmas, while beer
retail margins drop at Memorial Day, the Fourth of July, Labor
Day, and Christmas.
As aggregate demand tends to increase at these holidays,
however, the authors did not consider this evidence conclusive.
They turned to Lent, which is not associated with any shopping
surges. During Lent, retail margins on tuna declined 5 percent,
further weakening the case for the first two models. So did
results for the non-seasonal goods, such as cookies and analgesics.
Six out of these seven categories showed higher retail margins
at Christmas, despite the fact that Christmas is the peak
shopping period of the year.
Seeking more direct proof for the loss leader model, Kashyap,
Rossi, and Chevalier examined Dominick's advertising. The
typical supermarket circular advertises prices for about 200
of the 25,000 items the store carries. The data from Dominick's
showed a positive correlation between sales and reduced prices.
Even more significantly, the data also showed that popular
goods were the ones that were advertised the most, especially
seasonally peaking items.
A Word to Manufacturers
While clearly concluding that retailer behavior accounts
for most pricing changes, the authors acknowledge that manufacturer
behavior also plays a role. Although Kashyap, Rossi, and Chevalier
were able to study wholesale prices, they lacked data on manufacturing
costs and therefore could not explain why wholesale prices
showed a tendency to fall at seasonal demand peaks. "On
balance, we read the evidence as saying that manufacturer
behavior plays a more limited role in the counter-cyclicality
of prices than retailer behavior," they write.
"Manufacturers can only encourage retailers to use whatever
prices they think are optimal," explains Rossi. "Smart
retailers are going to cut their markups-the difference between
the retail and wholesale prices-at times of seasonal demand
and expand their sales."
During demand peaks, advertising and other promotions become
even more critical. Not only do goods receive greater exposure
to an increased number of consumers, but consumers pay attention
to the advertised prices and may switch brands. Knowing this,
retailers are less likely to advertise multiple products.
"If consumers regard different kinds of beer as being
roughly equivalent," explains Rossi, "why should
a retailer chew up two slots of advertising space for beer?"
To avoid losing out in the "promotions sweepstakes,"
Rossi advises manufacturers to consider offering retailers
more incentives to advertise or promote items directly rather
than cutting wholesale costs.
"Instead of investing $10 million in cutting wholesale
prices during the holidays," says Rossi, "maybe
it would be more efficient to spend that money on various
inducement incentives, such as lump-sum payments or funds
for developing new markets."
Anil Kashyap is Edward Eagle Brown Professor of Economics and Finance at the University of Chicago Graduate School of Business. Peter E. Rossi is Joseph T. Lewis Professor of Marketing and Statistics at the University of Chicago Graduate School of Business.
