In commonly used models, the parameter b may be interpreted as a measure of product
differentiation: it measures how many consumers a firm loses by raising its price slightly
above that of its competitor and is therefore large if there is little product differentiation.
For instance, in the Hotelling duopoly example of
Tirole (1988, pp. 192–294), b ¼1=2t,
where t is the unit transport cost. In a random utility model with i.i.d. valuations for the
two products, f, b ¼
Ð
+ 1
1
f EðÞ
2
dE, where f is the density of the additive random utility
term: it may then be interpreted as the “mass” of consumers who are just indifferent
between the two products at equal prices. For the uniform distribution on [α, β] used
by
Christou and Vettas (2008), b ¼1= β αðÞ. In this uniform case, a broader support
means more heterogeneity in products and tastes.
From the first-order condition,
(4.13) and (4.14), more differentiation, and hence a
lower b, all other things being equal, moves the equilibrium price and the advertising
intensity upward. Note, however, that price is decreasing in advertising intensity. This
is because more advertising by the competitor means less captive consumers who only get
an ad from firm i. For Φ
¼1, the pass-through rate p
c takes its full information value
1/2b. This opens up the possibility that more product differentiation leads to lower prices,
although for the present specification with quadratic costs of advertising, this is not the
case. There is, however, no ambiguity about the impact of an increase in product differ-
entiation on advertising, which is positive.
To discuss the impact of the number of competitors on pricing and advertising, I draw
on the analysis in
Christou and Vettas (2008), who study a variant of the model with a
random utility specification of demand. They find that more firms unambiguously lead to
a decrease in the advertising activity of each firm. Although this seems coherent with the
intuition from
Dorfman and Steiner (1954), it does not reflect a systematic relationship
between market power and advertising. Indeed,
Christou and Vettas (2008) find that an
increased number of competitors does not necessarily lead to lower prices. The intuition
for this is simple and follows from the same strategic interplay between price and adver-
tising that causes a potentially ambiguous impact of product differentiation on pricing.
For a fixed advertising intensity by competitors, an increase in the number of firms
decreases a firm’s price. However, more competition leads to a lower advertising inten-
sity, which increases market power, and hence the price.
Christou and Vettas (2008) find
that this price-augmenting effect may actually dominate in their setting.
The above price comparative statics results suggest that it might be extremely mislead-
ing to ignore the limited access of consumers to information when performing a struc-
tural estimation of market demand. This has been done in numerous studies in the wake
of the groundbreaking work of
Berry et al. (1995) on the automobile industry. Sovinsky-
Goeree (2008)
addresses this issue in her analysis of the US personal computer market in
the late 1990s. She uses data on ad expenditures in various media (magazines, newspapers,
TV, radio) as well as a survey of consumers that includes information about their exposure
139Advertising in Markets