brand purchases in the previous year. The confidence interval for the effect of DVR
acquisition on advertising effectiveness was tightly centered around zero, suggesting
no diminution in advertising effectiveness, a result they attributed to fairly low rates
of advertising avoidance among panelists.
Is this a puzzle? As advertising avoidance has gotten easier, commercial avoidance
seems to become more frequent. Yet there is no evidence of diminished advertising effec-
tiveness, and television advertising revenues have not fallen. There are three possible
explanations. One is that advertisements may be designed to retain their effectiveness,
even when played at high speed. For example, prominent displays of the brand logo
reduce advertising avoidance (
Teixeira et al., 2010), and can increase brand attitude,
intention to purchase, and choice behavior (
Brasel and Gips, 2008). A second possibility,
which to the best of my knowledge remains unexplored, is that perhaps households do
not avoid ads when they are in the market for the advertised product. In other words, an
advertisement exposure that a consumer actively chooses to avoid might have offered
little value to the advertiser in the event of an exposure. Further, many commercials
are repeated with such frequency that even frequent ad-avoiders may receive some min-
imum number of exposures to the most common commercials. The third possibility is
that (at least some) ads may be complements to product consumption, as originally pro-
posed by
Becker and Murphy (1993). Tuchman et al. (2015) investigated this possibility
using a single-source panel database of purchases and advertising exposures. They found
that greater recent brand consumption led to a lower probability of zapping the brand’s
television advertisement in the future.
A number of theoretical analyses have produced competing predictions about how
increased levels of advertising avoidance will affect media markets.
Anderson and
Gans (2011)
modeled a monopoly platform and examined how consumer adoption of
advertising avoidance technology would alter its strategy. In equilibrium, consumers
who value programming the most adopt advertising avoidance technology first, leading
to rising advertising time, falling welfare and content quality, and more mass-market con-
tent.
Athey et al. (2013) extended this framework to allow for competing outlets, imper-
fect measurement of advertising exposure, and endogenous multihoming by advertisers.
As consumer switching increases, advertising levels rise and the premium paid for large
audience increases, but total advertising expenditure falls.
4
In contrast, Ghosh and Stock
(2010)
did not model media platforms but they did consider the effect of informative
advertisements on price competition in the product market. In their model, advertising
avoidance leads to some consumer ignorance, which can sometimes increase advertisers’
product prices and profits in equilibrium, raising the demand for advertising.
4
See also Chapter 10.
214 Handbook of Media Economics