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Celebrity Endorsements, Firm Value and Reputation Risk: Evidence from the Tiger Woods Scandal

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We estimate the stock market effects of the Tiger Woods scandal on his sponsors and sponsors' competitors. In the 10-15 trading days after the onset of the scandal, the full portfolio of sponsors lost more than 2% of market value, with losses concentrated among the core three sponsors: Electronic Arts, Nike, and PepsiCo (Gatorade). Sponsors' day-by-day losses correlate strongly with Google search intensity regarding the endorsement-related impact of the scandal, as well as with qualitative indicators of "endorsement-related news." At least some sponsors' losses were competitors' gains, suggesting that endorsement deals are partially a business-stealing strategy. However, competitors who were themselves celebrity endorsement intensive fared relatively worse than those who were not endorsement intensive, and that difference also correlates day by day with news/search intensity regarding the scandal. It appears that the scandal sent a negative marketwide signal about the reputation risk associated with celebrity endorsements.
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Celebrity Endorsements, Firm Value and Reputation Risk:
Evidence from the Tiger Woods Scandal
Christopher R. Knittel and Victor Stango
October 28, 2010
Thanks to Anson Soderbery for fast and thorough research assistance. Knittel: Department of Economics, Uni-
versity of California, Davis, CA and NBER. Email: crknittel@ucdavis.edu. Stango: Graduate School of Management,
University of California, One Shields Avenue, Davis CA 95616.. Email: vstango@ucdavis.edu.
Celebrity Endorsements, Firm Value and Reputation Risk:
Evidence from the Tiger Woods Scandal
Abstract
We estimate the stock market effects of the Tiger Woods scandal, on both his sponsors and spon-
sors’ competitors. In the ten trading days after the beginning of the scandal, firms endorsed
by Woods suffered significant declines in stock market value, relative to both the entire stock
market and a set of competitor firms. The top five sponsors (Accenture, Nike, Gillette, Elec-
tronic Arts and Gatorade) lost 2-3 percent of their aggregate market value after the accident,
and his core three sponsors EA, Nike and PepsiCo (Gatorade) lost over four percent. At least
some sponsors’ losses were competitors’ gains, suggesting that endorsement deals are partially
a business-stealing strategy. However, competitors who are themselves endorsement-intensive
fared relatively worse than those who are not endorsement-intensive. It appears that the scandal
sent a negative market-wide signal about the reputation risk associated with celebrity endorse-
ments.
Keywords: celebrity endorsers, event studies, reputation risk
1 Introduction
As of mid-2009 professional golfer Eldrick ‘Tiger’ Woods earned roughly $100 million annually in
endorsement income, an amount far greater than that earned by any other athlete. On November
27, 2009, Woods was involved in a car accident outside his home. Following the accident, a series
of news reports about both the crash and Woods’ personal life damaged his public reputation, and
several sponsors either stopped featuring him or dropped him outright. In this paper we estimate
the stock market effects of the scandal, for both the sponsor firms and their competitors. Some of
those competitors are themselves “endorsement-intensive” (but have no deal with Tiger Woods),
while others have no celebrity endorsement deals.
Our empirics address several key questions about celebrity endorsements, firm value and busi-
ness strategy. Do firms capture value from investing in celebrity endorsements? If sponsors expe-
rience gains, do those gains represent net market value creation, or business-stealing from other
firms? And, does the stock market reflect changing expectations about the “reputation risk” that
firms take on by attaching their brands to celebrities? Previous work on celebrity sponsorship
almost exclusively focuses on the first question, rather than the latter two. And even the work on
gains from sponsorship faces some econometric difficulties that we circumvent, by dint of examining
the downside of a scandal rather than the upside of the initial endorsement deal.
Our first empirical finding is that between the car accident and Woods’ announcement ten
trading days later of an ‘indefinite leave’ from golf, his sponsors’ overall market value declined by
over two percentage points. The event study model we use measures losses relative to the stock
market overall, and also relative to competitor firms in the sponsors’ primary industries. Narrower
groups of firms with the biggest endorsement contracts, or that had made large complementary
investments in the “Tiger brand” lost more in percentage terms.
We also estimate stock price changes for sponsors’ competitors. We find that as sponsors
lost market value, competitors gained market value. More compelling is that these gains seem to
accrue only to competitors that are themselves not heavily invested in celebrity endorsements. On
the other hand, the subset of sponsors’ competitors with at least one celebrity endorsement deal
experienced no gains at all.
In the context of prior work linking stock market value to celebrity endorsements, our first result
provides clear evidence that in this case, endorsements generated substantial value for sponsor firms.
1
The losses that we measure are the converse of stock market value initially created through the
Tiger Woods endorsement deals, and are probably a lower bound on the initial gains experienced
by sponsor firms. Previous evidence of links between endorsements and stock market value has
been mixed, because nearly all of that work faces a harder identification problem: it uses initial
endorsement announcements, which are likely to be at least partially anticipated by traders, to
estimate gains in firm value.1The event we examine was by all accounts a complete surprise to the
market, making it a near-ideal natural experiment from an event study perspective.
A corollary of our result is that endorsement deals carry substantial risk. While we cannot
compare the losses sustained by sponsors to their initial gains, the losses we estimate are large.
That suggests taking a view of celebrity endorsement as a risky investment rather than a simple
short-run cost-benefit tradeoff - particularly if a firm plans to complement the endorsement deal
with co-investment in a new product or brand, as Nike did with its golf line, and as Electronic Arts
and Gatorade did with their “Tiger-specific” products.
Our finding that sponsors’ losses are competitors’ gains is novel in the context of previous
work. We are aware of one previous study (Mathur et al, 1997) examining competitors’ returns
after Michael Jordan’s announced return to professional basketball, but that study finds “only very
weak evidence” of a link between an endorser’s behavior and competitors’ stock market value. For
business strategy, the upshot of our finding is that one should view celebrity endorsements as yet
another tool for stealing business from competitors - and that one should incorporate information
about competitors’ endorsements when projecting one’s own future profitability.
Finally, the difference in competitors’ returns when we stratify by competitors’ “endorsement-
intensity” is provocative evidence about how markets price reputation risk associated with celebrity
endorsements, and about how events can change perceptions of that risk. The relatively more
negative returns for endorsement-intensive competitors suggests that the scandal changed market-
wide perceptions of risk associated with investments in celebrity endorsement. We are not aware
of any previous work examining this issue, and in the conclusion we discuss the implications of this
finding in more detail.
1Louie et al. (2001) is a notable exception. We discuss that work below.
2
2 Celebrity Endorsements and Firm Stock Market Value
Celebrity product endorsements, and endorsements by professional athletes in particular, are a
critical element of brand strategy.2The key question from a firm’s perspective, of course, is
whether a celebrity endorsement generates value sufficient to offset its possibly considerable cost.
Quantifying that benefit-cost tradeoff is hard, and consequently the question of whether celebrity
endorsements are value-enhancing remains open.
Stock market-based studies provide one window into measuring the returns associated with
celebrity endorsements. A firm’s stock price reflects expectations about the discounted value of a
firm’s expected future economic profits. If retaining a valuable endorser changes those expectations
- say, by increasing expected future sales - then an announcement of celebrity endorsement should
generate a “kick” in the stock price. Conversely, an adverse (reputation-damaging) event or the
departure of a valuable endorser might move those expectations about future profits downward,
which should result in a lower stock price.
Another dimension of using stock prices to evaluate celebrity endorsements is risk. As with
any investment, there is a chance that an endorsement deal will not pay off, either because a firm
initially underestimates the true gain associated with endorsement, or because the added value
of the celebrity endorser falls. Investors should treat that “reputation risk” as they would treat
any other component of risk in a firm’s stock: higher risk is less attractive. Holding the expected
level of future profits constant, investors should punish riskier firms with lower stock prices. In the
context of celebrity endorsements, that means that any firm with substantive exposure to celebrity
risk should be priced accordingly. More important, it means that changes in how markets perceive
the risk of celebrity endorsements might affect the value of all firms with celebrity reputation risk
exposure.
Beyond those straightforward intuitions, there is nuance to the stock market-based method
of measuring returns from endorsements. Stock prices reflect changes in expected profit rather
than sales or market share. Given that endorsement incurs expenses, it is possible that a celebrity
endorsement might reduce profit even as it sparks sales or growth. Put more formally, celebrity
endorsements generate economic rents, and the terms of the endorsement deal divide those rents. It
is possible that celebrities might bargain away all of the rents that they generate for their sponsors,
2See, e.g., the many references in Ding et al. (2009), and an earlier survey by Erdogan (1999).
3
making sponsorship at best a break-even proposition. On the other hand, higher stock market
prices for sponsors indicate that the firm has captured some of the economic rents generated by the
endorser/firm partnership. The key question for a firm, then, is whether it is possible (or perhaps
likely on average) that firms can capture rents generated by celebrity endorsements.
Another point worth mentioning is that because changes in expectations drive changes in stock
prices, it is much harder to measure changes in firm value following well-anticipated events. If, for
example, a celebrity endorsement deal is widely anticipated long before its formal announcement,
buyers and sellers of the sponsor’s stock will have fully priced all of the gains associated with
the deal well before the announcement itself, and the actual announcement will change neither
expectations nor stock prices. Examining stock price movements around the actual announcement
would therefore understate the gains associated with the endorsement deal. That means that the
empirically cleanest type of event to use for quantifying changes in firm value is a surprise, whether
it is good or bad, because surprises by definition avoid the anticipation problem.
In the context of the identification issue on the front end, it is not surprising that previous
studies attempting to link celebrity endorsements and corporate sponsorship to stock market value
have found mixed evidence.3We are aware of one study examining announcements of “bad news”
for celebrity endorsers (including athletes and entertainers); bad news is often, though not always,
more of a surprise than announcements of endorsement/sponsorship deals, and therefore provides
cleaner identification. In that paper, Louie et al. (2001) find that bad news with little “culpability”
for the endorser (such as a career-ending injury) generates gains for sponsors - this is an “any
publicity is good publicity” result - while bad news with more culpability (such as a DUI arrest)
generates losses.4The scandal that we examine falls squarely in the second (“more culpability”)
class.
3Farrell et al. (2000) find that Tiger Woods’ endorsement deal announcements generated stock market value for
Nike, but not for American Express or Fortune (Titleist). Agrawal and Kamakura (1995), Mishra et al. (1997),
Miyazaki and Morgan (2001), Pruitt et al. (2004) and Samitas et al. (2008) find that endorsements/sponsorships
generate positive stock market returns. Mathur et al. (1997) find that Michael Jordan’s return to professional
basketball generated positive returns for his sponsors. find that celebrity endorsements generate positive stock
market returns for a wide set of celebrities. On the other hand, Fizel et al. (2008), Farrell and Frame (1997), Clark
et al. (2009), Cornwell et al. (2001) and Ding et al. (2009) find weaker evidence, or even evidence (in the case of
Olympic sponsorships) negative returns following endorsement/sponsorship announcements.
4That paper also adds to an interesting set of studies asking how negative information about an endorser affects
brand perception and firm value. See, e.g., Till and Shimp (1998).
4
Previous studies also may contain mixed findings for two other reasons. First, it is probably
true that while some firms may capture rents when they sign celebrity endorsers, others may not.
Some celebrities may command payments that completely offset any incremental profit generated
for the sponsor firm. And second, some firms may simply overestimate the gains associated with
an endorsement deal; by a winner’s curse logic, those firms should in fact be the ones who sign
celebrities more often.
One advantage in our case is that the scandal represented a surprise. Before the accident, Tiger
Woods was widely acknowledged to have the most valuable “brand” of any athlete in the world
- a fact accruing both from his athletic success and from his clean public image. Until 2009 he
routinely placed in the top 5 of the Forbes “Celebrity 100” list of most influential celebrities world-
wide. So our setting is certainly one in which stock prices might plausibly reveal the economic
object of interest, because there is no evidence that the market anticipated any of the bad news
associated with the scandal. The flipside of that, and a limitation of our approach, is that while our
method can estimate by how much sponsors’ expected future profits fall after the scandal, it cannot
estimate the gain in expected future profits that firms initially experienced from the endorsement
deal - so, the losses that we estimate are a lower bound on the initial gains.
Another benefit associated with our example is that Tiger Woods endorses several products
rather than just one. This allows us to estimate stock market effects across a wide set of otherwise
unrelated firms, and gives us more statistical power than one would have if the estimates were
confined to a single sponsor firm.5Comparing returns for many sponsors associated with a single
endorser can shed light on the circumstances in which endorsement deals are profitable for firms,
as long as one properly controls for the contemporaneous correlation in errors across sponsor firms.
The large number of sponsors also allows us to augment the analysis by collecting data for a wide
set of competitors to Tiger Woods’ sponsors. These data are useful in several ways. They allow us
to control for industry-specific factors affecting sponsors’ stock prices, because to the extent that
competitors and sponsors share industries those factors should also change stock prices for com-
petitors. More important, our competitor stock price data allow us to estimate whether sponsors’
losses after the scandal are competitors’ gains. Whether that is true depends on substitutability
between sponsors’ products and competitors’ products, and the extent to which celebrity endorse-
ment creates new demand, or merely steals business from competitors. Understanding whether
5In this respect, our work follows that of Farrell et al. (2000) and Mathur et al. (1997).
5
celebrity endorsement is business-stealing or pure value creation is important both conceptually
and for business strategy, but there has been very little empirical work examining the question.6
Finally, the dramatic nature of this particular scandal - an extremely damaging set of events for
the world’s leading endorser - allows us to examine the general role of reputation risk in determining
firm value for endorsement-intensive firms in general. As we discussed above, reputation risk
should be priced by the stock market. Following the Tiger Woods scandal, the media devoted
substantial attention to that risk; for example, a Google search for “celebrity reputation risk”
yields stories largely written about Tiger Woods after the scandal. One can argue that the scandal
either directly altered perceptions of the level of risk, or that it simply alerted the market to
precisely how important reputation risk can be for endorsement-intensive firms. In either event,
one might expect a stock market reaction. There is also evidence of a market response, by insurance
companies offering protection against celebrity reputation risk; a New York Times article written
January 31, 2010 was titled “Insuring Endorsements Against Athletes Scandals,” and stated this:7
In the wake of the Tiger Woods scandal, insurers are being inundated with inquiries
from corporations seeking to protect their investments, their brands and even their
sales when their celebrity endorsers suffer public embarrassment...In a new wrinkle,
more companies are trying to insure against the potential loss of sales when an athlete
product endorser is involved in a scandal.
Whether the scandal in fact changed market-level perceptions of reputation risk is of course an
empirical question. We explore that question by estimating post-scandal stock price changes for
two subsets of sponsors’ competitors: those who are themselves endorsement-intensive, and those
who are not endorsement-intensive. If the scandal sent a market-wide signal about reputation risk,
one might expect that risk to affect stock prices for all endorsement-intensive firms, even those
who do not have Tiger Woods as an endorser. We test that by comparing competitors’ returns
for the two subsets: if market-wide perceptions about reputation risk changed, one would expect
that competitors with endorsement deals would fare relatively worse than competitors without
endorsement deals.
6One notable exception is the work by Mathur et al. (1997), who find that competitors to Michael Jordan’s
sponsors experience “very weak” stock price changes after Jordan’s return to professional basketball.
7http://www.nytimes.com/2010/02/01/sports/01insurance.html.
6
3 The Endorsement Deals of Tiger Woods and the Scandal
Prior to November 2009, Tiger Woods’ annual endorsement income was estimated to be roughly
$100 million, a figure roughly twice as large as that for any other athlete.8We are able to identify
seven publicly owned, domestically traded companies with which Tiger Woods had an endorsement
or sponsorship deal as of November 27, 2009. We list those companies in Table 1.9While the
details of most contracts are private, the five most valuable contracts are seemingly with Accen-
ture, Gillette, Nike, PepsiCo (Gatorade) and Electronic Arts (EA).10 Those five deals generated
approximately $80-90 million in annual income prior to the scandal. In the empirical work below,
we estimate some stock price effects for this subset of “Big Five” firms.
It is also worth making one other distinction between sponsor firms. Some sponsors augment
the endorsement relationship by making complementary co-investments in new products, the value
of which might also be tied to the endorser’s reputation. There are three such firms in our sample.
Nike has a considerable complementary investment in the Nike golf product line, which did not
exist prior to the Tiger Woods endorsement contract. Electronic Arts sells the “EA Tiger Woods”
line of video games, and recently launched a new “Tiger Woods Online” video game. Gatorade
invested considerable resources in developing a “Tiger Focus” drink.11
We draw this distinction because for firms with such co-investments in products linked to the
“Tiger brand,” there might be a tighter link between reputation risk and firm value. Developing
and marketing a new product line requires a considerable up-front investment, as well as substantial
production and marketing costs. The Nike golf line, for example, is a brand with considerable asset
value, accumulated via Nike’s substantial up-front and ongoing investment in R&D, physical capital
and brand equity. So, for firms with such complementary investments, changes in stock prices will
reflect changes in the value of those assets, as well as changes in direct sales associated with the
endorsement deal. So, in the empirical work below we estimate stock price effects for the “Big
8http://sportsillustrated.cnn.com/more/specials/fortunate50/2009/.
9See http://web.tigerwoods.com/sponsors/sponsors for a complete list. Some of the companies on that list are
either privately held, or traded on foreign exchanges; we do not track those companies.
10See http://industry.bnet.com/advertising/10005016/the-tiger-woods-sponsor-deathwatch-at-nike-digs-in-heels/
for details.
11Gatorade announced the discontinuation of the Tiger Focus drink two days before the scandal began. It is
difficult to know whether the decision was affected by the scandal, but to be conservative we treat Gatorade as
having a complementary investment associated with the Tiger Woods endorsement deal.
7
Three” of Nike, Electronic Arts and Gatorade: the set of firms with substantial complementary
investments associated with Tiger Woods.
3.1 The Timeline of the Scandal
The scandal began with a car accident on the evening of November 27, 2009 - a Friday, meaning
that the first trading day after the release of “bad news” is Monday November 30, 2009. Following
the night of the accident, several reputation-damaging pieces of information emerged, culminating
ten trading days later (December 11, 2009) with Tiger Woods’ announcement of an ‘indefinite
leave’ from golf.12 Any of the information released between those two dates may have reduced
Mr. Woods’ current value to endorsers, reduced the value of complementary assets linked to the
“Tiger brand,” increased uncertainty about the future value of those assets and Tiger Woods as
an endorser, and sent a signal about the magnitude of “reputation risk” for endorsement-intensive
firms.
In the wake of these events several sponsors either dropped Tiger Woods outright or distanced
themselves from him. On December 13, 2009 Accenture cancelled its endorsement deal. On De-
cember 31, 2009 AT&T cancelled its sponsorship deal with Woods. On February 26, 2010 Gatorade
ended its deal with Woods. Even the sponsors that retained Woods - Nike, for example - oriented
television and print advertising away from Tiger Woods-specific images after the scandal.
4 Estimated Stock Market Effects of the Scandal
To estimate shareholder losses for the set of sponsor firms following November 27 2009, we estimate
an event study. Our method is standard in marketing, economics and finance, and as we discuss
above has been employed extensively in studies linking stock market value to celebrity endorsements.
Our primary specification is:
Rit =αi+βm
iRm
t+βc
iRc
it +X
s
δsDst +it,(1)
where,
12For a timeline and some details about the allegations, see http://www.montrealgazette.com/sports/timeline+Tiger+Woods+decline/3374668/story.html.
8
Rit = the return on shares of sponsor i at time t,
Rm
t= the return on the Dow Jones value-weighted total market index at time t,
Rc
it = the return on shares of sponsor i’s competitors at time t,
δs= the abnormal return on day s after the accident,
Dst = a dummy variable equal to one during day s after the accident,
it = an error term.
The specification is a standard market model where the dependent variable is a sponsor’s daily
percentage return exclusive of dividends, from Wharton Research Data Services and the Center for
Research in Stock Prices (CRSP). The controls are the value-weighted total market return and a
value-weighted competitor portfolio return; below we present results that both include and omit the
competitor portfolio. The competitor portfolio includes the first ten firms listed by Google Finance
as “competitors” of the sponsor - meaning the sponsor’s parent company.13 The purpose of including
competitors based on parent companies rather than sponsors is to control as completely as possible
for all possible confounding contemporaneous movements in stock prices, many of which will be
industry-specific; the ideal match for a particular parent company is another firm that competes in
a set of industries identical to those of the sponsor’s parent company. Table A1 lists competitors
for each sponsor; we include only competitors traded on U.S. stock exchanges. The model allows
for sponsor-specific daily mean returns (alphas) and correlations with market/competitor returns
(betas). The data begin on January 1, 2005 and extend to December 31, 2009. We omit observations
for the thirty trading days preceding November 27, 2009 (the day of the accident). Including them
does not change the results, and we find no evidence of pre-event abnormal returns. Event date
“one” is November 30, the first trading day after the accident (which occurred after the close of
trading on November 27).
Our model yields estimates of daily abnormal returns, δs, which are deviations of actual returns
on the days after the scandal from those predicted by the model. We weight observations by
market capitalization, effectively estimating the abnormal returns that one would earn by holding
a value-weighted portfolio of Tiger Woods’ sponsors. We also estimate cumulative abnormal returns
(CARs) - which are running sums of the daily abnormal returns - starting on November 30th. The
CARs estimate sponsors’ total loss over a multi-day window starting on event date one, relative to
13We have estimated the model using the first five or three competitors, and also using the Yahoo! Finance
competitor list. Varying the specification of competitors’ returns has no effect on the results. Nor does weighting
competitors’ returns equally.
9
the market and competitor returns. In the results below we report abnormal returns and CARs for
windows extending up to fifteen trading days after the event date.
When examining the effect of a single event on multiple firms, it is important to adjust the
estimated standard errors for the contemporaneous correlation of sponsor-specific errors on the
same day.We use Salinger’s (1992) procedure for calculating standard errors on the cumulative
abnormal returns. The procedure involves making a simple transformation to the data matrix that
yields correct standard errors.
In some cases we estimate a more flexible specification that allows abnormal returns to vary
across firms within the same day:
Rit =αi+βm
iRm
t+βc
iRc
it +X
is
δisDst +it ,(2)
This more flexible specification allows us to conduct non-parametric sign and rank tests re-
garding the post-event abnormal returns δis. In both tests the null hypothesis is that post-event
abnormal returns are centered on zero, which is what one would expect if the post-event period
contains no systematic news about firm value. Rejecting the null suggests that some (either pos-
itive or negative) information affected sponsor firms’ returns. In these models we also correct for
contemporaneous correlation of errors across sponsor firms.
During the event period there is one earnings announcement, by PepsiCo (the parent of Gatorade),
on December 9th. We discuss the results in the context of this possibly confounding factor below.
Another confounding factor is that the smallest sponsor, TLC Vision, filed for bankruptcy on De-
cember 21, 2009. That turns out not to matter much because TLC’s weight in the portfolio is
trivially small, but it is worth noting. If one weights the portfolio equally, the returns for portfolios
including TLC become more negative after the scandal - but that probably reflects the spurious
influence of TLC’s imminent bankruptcy (which seems well-anticipated by the market, based on its
stock price leading up to December 21). That makes using a value-weighted portfolio (or focusing
on the Big Five/Three) more attractive conceptually.
A final point concerns interpretation of the results. Ideally, one would want to interpret any
abnormal returns as measuring percentage changes in the expected value of future economic profits.
In our case that is hard, if not impossible, for a few reasons. Most of our sponsor firms are large
multi-product firms, for which Tiger Woods endorses only a single product; Nike produces many
10
products outside its golf line, for example. Nike’s stock price, of course, reflects expectations about
its profits from all business lines. So, the percentage change in profits will be weighted by the shares
of economic profits flowing from “Tiger-related” products and “non-Tiger-related” products. One
could proxy for those shares using dollar values of sales - Nike golf, for example, represents roughly
ten percent of annual sales for Nike - but there is no guarantee that shares of expected future
profit correspond to shares of dollar sales. Another complicating factor is that if the scandal sent a
market-wide signal about celebrity reputation risk, then even the non-Tiger-related business lines
might suffer. That would be particularly true for a company like Nike, which is one of the most
celebrity endorsement-intensive firms in the world. For these reasons, we try to be as structure-free
in the econometric model as possible; the caveat is that our results should be taken as indicating
the direction and overall dollar value (percentage change x market capitalization) of abnormal
returns, but should not be taken as indicating percentage changes in Tiger-related economic profit.
This is particularly important when comparing gains/losses across firms, for which “Tiger-related”
gains/losses and shares of economic profits may be very different.
4.1 Primary Results
Table 2 shows estimates of cumulative abnormal returns (CARs) for all sponsors, for the Big Five
only and for the Big Three only. The first three columns show full results for the model in equation
(2), which controls for both market and competitor returns. The second three columns show results
from the more parsimonious model omitting competitors’ returns. The fit in the first three columns
is better, and the competitors’ returns explain a share of variation in sponsors’ returns that is both
statistically and economically significant.14
In the first three columns, for the full group of sponsors, the point estimates are negative by the
10-day and 15-day horizons, but are not statistically significant. For the sub-groups, the percentage
declines are bigger, and statistically different from zero. In the Big Five subsample the 10-(15-)day
CAR shows a loss of 2.6%(3.4%), and in the Big Three subsample the 10-(15-)day CARs show a
losses of 4.0%(4.8%). The Big Five CARs are statistically significant at 10% or better, and the Big
Three CARs are statistically significant at 5% or better. The results in the second three columns,
from the model excluding competitors’ returns, are closer to zero and less significant. That suggests
that competitors’ returns were positive relative to the market - something we examine in more detail
14The p-value on an exclusion restriction for competitors’ returns is less than 0.0001.
11
below.
The pattern of percentage declines across the sub-groups makes sense. The full group number
is the lowest, because it includes firms with relatively small involvements with Mr. Woods. The
Big Five have greater involvements, and we see that they suffer more damage. And, the sponsors
with the greatest complementary investments in the “Tiger brand” suffer the most.
Figure 1 provides more detail on the pattern of losses over time. It shows the cumulative
abnormal returns for these groups over the entire period from November 30 to December 16.
One interesting feature of the losses is that they do not occur immediately. That suggests that
information about the downside of the scandal for sponsor firms leaked gradually - this generally fits
the cycle of media coverage after the accident, in the sense that there was considerable uncertainty
about both the circumstances of the accident and the other allegations about Tiger Woods’ personal
life. The the announcement on December 11 of Tiger Woods’ indefinite leave from golf does seem
to be a watershed of sorts - returns turn negative in the few days leading up to that announcement
and then largely stabilize.
Table 3 shows daily abnormal returns and presents the results of the sign and rank tests. The
main body of the table shows daily abnormal returns for each of our main sponsor groups in the
first three columns. These abnormal returns are the individual δscoefficients, which are averaged
across firm (weighted by firm value). Shaded cells show negative values for these coefficients: of
the forty-five daily abnormal returns in the first three columns, 31 (69%) are negative.
The bottom four rows use the firm-specific daily abnormal returns δis (not shown in the table)
to conduct both sign and rank tests over 10-day and 15-day windows. Again, the null hypothesis
in these tests is that returns are centered on zero. The alternative (one-tailed) hypothesis in
each test is that the returns are centered on a negative value, indicating the systematic release
of negative information affecting all firms. The sign test uses only information about the sign
(positive or negative) of each coefficient, while the rank test uses information about both signs and
magnitudes.
For the full sponsor group, the p-values for both sign tests are below 0.10, with the share
of abnormal returns negative at 56% (57%) over the 10-day (15-day) horizons. Results for the
subsamples are more significant. For the Big Five, both sign test p-values are below 0.05, with
the share of abnormal returns negative at 60% (62%) over the 10-day (15-day) horizons. For the
Big Three both sign test p-values are below 0.02, with the share of abnormal returns negative at
12
64% (73%) over the 10-day (15-day) horizons. The pattern for the rank tests is similar. In all,
these results provide strong evidence that returns after the scandal are systematically negative,
particularly for the Big Five/Three groups.
The last two columns shed further light on whether the PepsiCo negative earnings revision on
December 9, 2009 contaminates our results. In the fourth and fifth columns of Table 3, we break
our ‘Big Three’ subsample of EA, Nike into two groups: PepsiCo and the other two firms. The
abnormal return for PepsiCo on December 9 is indeed negative and significant (-2.9%), but so are
abnormal returns for the other two firms (-2.4%), and the point estimates are very close. While
one cannot rule out a negative stock price effect of the announcement, the pattern of results is
consistent with the release on December 9 of bad news common to Nike, EA and PepsiCo. What’s
more, the p-values for the sign and rank tests using only EA and Nike returns are both close to 0.01
over the 10-day window, and are much larger for PepsiCo, which experienced several fairly large
positive returns, and the only significantly positive abnormal return in the group. That evidence
suggests that if anything, the inclusion of PepsiCo pushes against the overall results. One can see
that even more clearly in Figure 2, which shows CARs for the Big Three as a group, and also for
Nike, EA and PepsiCo individually. CARs for Nike and EA are negative immediately following the
accident and remain so over the entire 15-day event window, while PepsiCo experiences positive
returns early on, then only turns negative later. Our choice to weight abnormal returns and CARs
by value only pushes against our main results, because PepsiCo has by far the biggest market
capitalization in the Big Three (note how closely the solid line in Figure 3 tracks PepsiCo’s CAR).
In all, these results provide strong evidence that our sponsor firms lost value as the scandal
unfolded. While we do not report the results, we have estimated the losses out to the end of the
year (December 31, 2009), and find no evidence of any reversion in prices. The point estimates for
all of our sponsor groups are larger on December 31st than they are ten days into the scandal, and
are still statistically significant. The effects are stronger when we control for competitors’ returns,
suggesting that competitors may have benefited relative to the rest of the market. We now turn to
that question.
4.2 Competitor Returns and Endorsement Intensity
In this section, we examine returns for our sponsors’ competitors. For each of the seven firms in
our sponsor sample we collect daily return data for ten competitors, meaning that we examine
13
returns for as many as seventy competitors in the work below. Some competitors move in or out
of the sample during the estimation window, are not traded on a U.S. exchange, or are one of our
sponsors, meaning that we do not always have data for all seventy firms.
The model for this analysis is a standard market model:
Rc
it =αi+βiRm
t+X
s
δsDst +it,(3)
where,
Rc
it = the return on shares of competitor i at time t,
Rm
t= the return on the CRSP equally-weighted portfolio at time t,
δs= the abnormal return for competitor i from day s after the accident,
Dst = a dummy variable equal to one during day s after the accident,
it = an error term.
The specification is identical to our previous specification but for the fact that we no longer
control for competitors’ returns, since the competitors’ returns are now the dependent variable.15 It
allows for competitor-specific daily mean returns (alphas) and correlations with market returns (be-
tas). We weight the returns by competitor value (market capitalization). We estimate competitors’
returns for all competitors, as well as competitors to the Big Five/Three.
The first three columns of Table 4 shows ten-day CARs for the competitor sample. The general
pattern is that competitors’ CARs are positive, and rise as sponsors’ returns fall - with the greatest
changes occurring after day seven. The point estimates are more positive for the Big Five and
Big Three, although only the CARs for the Big Five are significantly different from zero. This is
weak evidence that overall, the set of competitors experienced stock market gains as the sponsors
experienced losses. It also dovetails with the evidence from Table 2 showing that sponsors’ returns
are more negative measured relative to competitors than simply relative to the market overall.16
15Including sponsors’ returns in this model would be incorrect, since we want to measure returns for competitors
relative to the market rather than sponsors.
16The difference in sponsors’ abnormal returns when measured relative to competitors need not equal competitors’
abnormal returns. The net difference will depend both on the level of competitors’ returns, and on the correlation
between sponsors’ and competitors’ returns - the βicoefficients on competitors’ returns in our primary model. As
those coefficients approach zero, sponsors’ estimated abnormal returns depend less on whether they are measured
relative to competitors’ returns.
14
The more interesting results are those in the next six columns, which distinguish between com-
petitors with and without celebrity endorsement deals. We classify a competitor as “endorsement
intensive” if a web search reveals that the competitor has at least one celebrity endorsement deal.
This is probably conservative, in the sense that relatively few of these firms are as endorsement-
intensive as the large sponsors that have Tiger Woods as an endorser.17
The results in the last six columns suggest that competitors without endorsements fared better,
in a relative sense, than those with endorsements. For those firms, in the Big Five and Big Three
subsamples the CARs are significantly different from zero over nearly any window beyond ten days.
The pattern of magnitudes also corresponds to the pattern for sponsors - smallest in absolute value
for the “all firms” group, larger for the Big Five subsample, and still larger for the Big Three
subsample. In contrast, the last three columns show that CARs for competitors with endorsements
are not significantly different from zero for any event window. We also test whether the daily
abnormal returns are significantly different across the two groups, and find that the returns are
significantly more negative (at ten percent) for the Big Five and Big Three endorsement-intensive
subsamples, on two days: the third and ninth trading days after the accident.18 The abnormal
returns on all other days are not significantly different across the endorsement-intensive and non-
intensive subsamples.
The relative gains for competitors without endorsement deals suggest the losses for sponsor firms
were at least in part gains for competitors - in other words, that celebrity endorsements transfer
value across firms. But the fact that being endorsement-intensive was treated more harshly in the
market suggests a second effect - that the scandal sent a negative market-wide signal, as suggested
in the New York Times article above, about the possible downside of celebrity endorsements. For
endorsement-intensive competitors, the net effect of the business-stealing effect (a gain) and the
reputation risk effect (a loss) appears to be a wash.
The overall pattern of results is summarized by Figure 3, which highlights the differences be-
tween our three groups of affected firms: sponsors, competitors with endorsement deals, and com-
petitors without endorsement deals.19 The relative differences across the groups are economically
meaningful; the scandal appears to have had far-reaching and substantive effects on a large set of
17We experimented with several ways of classifying endorsement intensity, with little variation in the qualitative
results.
18The latter is the first trading day following the largest single-day gains for sponsors. See Table 3.
19The sponsor coefficients here are those from the model without competitors’ returns, to avoid double-counting.
15
firms. Moreover, the timing of gains and losses is consistent; the onset of losses for sponsors occurs
on days 8-10 after the accident (leading up to the ‘indefinite leave’ announcement, and that is also
when the onset of gains for competitors occurs. That pattern affirms the view that our results for
both sponsors and competitors are related to the scandal.
5 Discussion and Conclusion
The Tiger Woods scandal provides a unique opportunity to understand more about the relationship
between stock market value and celebrity endorsements. Our first result confirms a direct dimension
of that link: the market value of Tiger Woods’ sponsors fell substantively after the scandal broke,
relative to the market values of firms without such endorsement deals. That finding is particularly
informative in the context of the mixed evidence from previous work. It appears that the firms we
examine were indeed able to capture some of the rents associated with the endorsement partnership
- while we cannot measure the initial upside of the deals, our results probably provide a lower bound
on those values.
Beyond that, we shed light on some previously under-studied aspects of the endorsement/stock
price relationship. Firms with substantial co-investments in new products linked to the “Tiger
brand” suffered greater declines in value, presumably reflecting declines in the asset values or
brand equity associated with those products. This result highlights a further downside risk of
pairing celebrity endorsements with endorser-specific investments in products or branding.
Our estimates of competitors’ gains represent new evidence regarding how far-reaching the stock
market effects of celebrity endorsements can be. Competitors to sponsor firms measurably gained
value after the scandal, relative to the rest of the market. That finding has implications for business
strategy, in that competitors’ endorsement deals are one more factor affecting firm value. While
we cannot quantify whether all sponsors’ losses were competitors’ gains, our findings do bear on a
broader point: it appears that celebrity endorsements transfer value, at least in part, rather than
purely creating value.
Finally, the anecdotal evidence regarding how the scandal altered perceptions of celebrity en-
dorsement reputation risk, in concert with our direct evidence on how competitors fared based on
whether they also had celebrity endorsers or not, suggests a regime change in how equity markets
priced reputation risk. Whether that regime change persists is an open question, but if insur-
16
ance companies indeed start offering “reputation risk insurance” then that view will have passed a
convincing market test.
17
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18
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19
6 Tables
Sponsor Parent Company Endorsement value (/yr.) Market Cap
Nike Nike $20-30 million $32 Billion
Gatorade Pepsico $20 million $95 Billion
Accenture Accenture $20 million $26 Billion
Gillette Procter and Gamble $15 million $179 Billion
Tiger Woods PGA Tour Golf Electronic Arts $8 million $5.76 Billion
AT& T AT& T n/a $165 Billion
TLC Laser Eye Centers TLC n/a $4.04 Million
Table 1. Sponsors, Parent Companies, Endorsement Values and Market Capitalizations.
Notes: We include all sponsors for which we can obtain stock price data. Market cap values are as of
mid-December 2009. AT&T's relationship with Woods involves sponsoring a golf tournament and
charity events, in exchange for product placement (e.g., on Tiger Woods' golf bag.)
20
Table 2. Cumulative abnormal returns for sponsor firms.
Relative to:
Days after event All Firms Big Five Big Three All Firms Big Five Big Three
One -0.002 -0.002 -0.002 -0.004 -0.003 -0.004
(0.004) (0.005) (0.006) (0.004) (0.005) (0.007)
Two -0.000 0.001 0.008 -0.000 0.003 0.010
(0.006) (0.006) (0.009) (0.006) (0.007) (0.010)
Three 0.001 0.000 0.004 0.002 0.004 0.005
(0.007) (0.008) (0.011) (0.007) (0.008) (0.012)
Four 0.000 -0.006 -0.002 0.002 -0.002 -0.003
(0.008) (0.009) (0.013) (0.009) (0.010) (0.014)
Five 0.003 -0.003 0.005 0.003 0.001 0.005
(0.009) (0.010) (0.014) (0.010) (0.011) (0.015)
Six 0.009 -0.001 0.008 0.008 0.002 0.010
(0.010) (0.011) (0.015) (0.010) (0.012) (0.017)
Seven 0.003 -0.006 0.001 0.004 -0.002 0.004
(0.011) (0.012) (0.017) (0.011) (0.013) (0.018)
Eight -0.007 -0.016 -0.026 -0.004 -0.011 -0.023
(0.011) (0.013) (0.018) (0.012) (0.014) (0.019)
Nine -0.008 -0.019 -0.030 -0.004 -0.013 -0.023
(0.012) (0.014) (0.019) (0.013) (0.015) (0.020)
Ten -0.010 -0.026* -0.040** -0.005 -0.018 -0.030
(0.013) (0.014) (0.020) (0.014) (0.016) (0.021)
Eleven -0.011 -0.025 -0.045** -0.007 -0.018 -0.037*
(0.013) (0.015) (0.021) (0.014) (0.016) (0.023)
Twelve -0.017 -0.031* -0.042* -0.015 -0.023 -0.034
(0.014) (0.016) (0.022) (0.015) (0.017) (0.024)
Thirteen -0.019 -0.031* -0.044* -0.018 -0.025 -0.039
(0.015) (0.016) (0.023) (0.015) (0.018) (0.024)
Fourteen -0.019 -0.031* -0.043* -0.020 -0.028 -0.044*
(0.015) (0.017) (0.024) (0.016) (0.018) (0.025)
Fifteen -0.022 -0.034* -0.048** -0.024 -0.034* -0.050*
(0.016) (0.018) (0.024) (0.017) (0.019) (0.026)
Observations 8802 6295 3777 8802 6295 3777
R-squared 0.530 0.497 0.497 0.468 0.415 0.414
Market, competitors
Market only
Notes: Coefficients are cumulative abnormal returns (CARs) weighted by firm value (market capitalization). First three columns show
results of the full model with market and competitors' returns, from equation (1). Second three columns show results of the simple market
model omitting competitors' returns. Event date is November 27, 2009. Standard errors are adjusted for contemporaneous correlation
across firms. "All firms" include all listed in Table 1. "Big Five" includes Nike, EA, Accenture, PepsiCo (Gatorade) and P&G (Gillette).
"Big Three" includes Nike, EA and PepsiCo.
21
Table 3. Daily Abnormal Returns for Sponsors.
Days after event
All Firms Big Five Big Three Nike, EA Pepsi
One -0.002 -0.002 -0.003 -0.005 -0.002
(0.004) (0.005) (0.007) (0.013) (0.009)
Two 0.002 0.003 0.011* -0.007 0.016*
(0.004) (0.005) (0.007) (0.013) (0.009)
Three 0.001 -0.001 -0.005 -0.007 -0.004
(0.004) (0.005) (0.007) (0.013) (0.009)
Four -0.001 -0.007 -0.006 -0.004 -0.006
(0.004) (0.005) (0.007) (0.013) (0.009)
Five 0.003 0.003 0.007 -0.016 0.014
(0.004) (0.005) (0.007) (0.013) (0.009)
Six 0.006 0.002 0.003 0.003 0.003
(0.004) (0.005) (0.007) (0.013) (0.009)
Seven -0.006 -0.005 -0.007 -0.005 -0.007
(0.004) (0.005) (0.007) (0.013) (0.009)
Eight -0.011*** -0.010** -0.028*** -0.024* -0.029***
(0.004) (0.005) (0.007) (0.013) (0.009)
Nine -0.001 -0.004 -0.004 0.005 -0.007
(0.004) (0.005) (0.007) (0.013) (0.009)
Ten -0.002 -0.006 -0.010 0.006 -0.015*
(0.004) (0.005) (0.007) (0.013) (0.009)
Eleven -0.001 0.001 -0.005 -0.002 -0.006
(0.004) (0.005) (0.007) (0.013) (0.009)
Twelve -0.007* -0.006 0.003 0.008 0.001
(0.004) (0.005) (0.007) (0.013) (0.009)
Thirteen -0.001 -0.000 -0.001 -0.002 -0.001
(0.004) (0.005) (0.007) (0.013) (0.009)
Fourteen -0.000 -0.000 0.000 -0.005 0.002
(0.004) (0.005) (0.007) (0.013) (0.009)
Fifteen -0.003 -0.004 -0.005 0.014 -0.011
(0.004) (0.005) (0.007) (0.013) (0.009)
Observations 8802 6295 3777 2518 1259
R-squared 0.530 0.497 0.465 0.403 0.540
10-day sign test p-value 0.060 0.027 0.005 0.015 0.117
15-day sign test p-value 0.030 0.021 0.018 0.051 0.092
10-day rank test p-value 0.117 0.028 0.007 0.009 0.420
15-day rank test p-value 0.065 0.046 0.038 0.110 0.389
Notes: Coefficients are abnormal returns weighted by firm value, estimated using the model in equation (1).
Event date is November 27, 2009. Standard errors are adjusted for contemporaneous correlation across
firms. "All firms" include all listed in Table 1. "Big Five" includes Nike, EA, Accenture, PepsiCo
(Gatorade) and P&G (Gillette). "Big Three" includes Nike, EA and PepsiCo. Shaded cells indicate negative
values. Sign and rank tests p-values use the full set of firm-day-specific abnormal returns, estimaed using
the model in equation (2). For the sign and rank tests the null hypothesis is that returns are centered on zero.
22
Table 4. CARs for competitors, and for competitors by endorsement intensiveness
All competitors
Days after event All Firms Big Five Big Three All Big Five Big Three All Firms Big Five Big Three
One -0.002 -0.001 -0.002 -0.004* -0.002 -0.009* 0.000 0.000 0.000
(0.002) (0.002) (0.003) (0.002) (0.002) (0.005) (0.004) (0.004) (0.005)
Two 0.001 0.005 0.006 -0.003 0.002 -0.006 0.006 0.006 0.009
(0.003) (0.003) (0.005) (0.003) (0.003) (0.007) (0.006) (0.006) (0.007)
Three -0.003 0.001 0.000 -0.003 0.004 -0.008 -0.002 -0.002 0.002
(0.003) (0.004) (0.006) (0.004) (0.004) (0.008) (0.007) (0.007) (0.009)
Four 0.003 0.006 0.004 0.003 0.010** -0.004 0.003 0.003 0.006
(0.004) (0.004) (0.006) (0.004) (0.005) (0.009) (0.008) (0.008) (0.010)
Five 0.001 0.006 0.004 -0.002 0.009* 0.003 0.004 0.004 0.004
(0.004) (0.005) (0.007) (0.005) (0.005) (0.011) (0.009) (0.009) (0.011)
Six -0.002 0.003 0.004 -0.004 0.006 0.007 0.001 0.001 0.004
(0.005) (0.005) (0.008) (0.005) (0.006) (0.012) (0.010) (0.010) (0.012)
Seven 0.000 0.003 0.005 -0.001 0.005 0.004 0.002 0.002 0.005
(0.005) (0.006) (0.008) (0.005) (0.006) (0.012) (0.011) (0.011) (0.013)
Eight 0.007 0.006 0.007 0.008 0.008 0.009 0.005 0.005 0.006
(0.005) (0.006) (0.009) (0.006) (0.007) (0.013) (0.012) (0.012) (0.014)
Nine 0.009 0.011* 0.013 0.011* 0.016** 0.026* 0.007 0.007 0.009
(0.006) (0.006) (0.010) (0.006) (0.007) (0.014) (0.012) (0.012) (0.015)
Ten 0.007 0.010 0.013 0.010 0.018** 0.030** 0.004 0.004 0.009
(0.006) (0.007) (0.010) (0.007) (0.007) (0.015) (0.013) (0.013) (0.016)
Eleven 0.007 0.011 0.012 0.009 0.019** 0.025 0.005 0.005 0.008
(0.006) (0.007) (0.011) (0.007) (0.008) (0.016) (0.014) (0.014) (0.017)
Twelve 0.007 0.013* 0.015 0.005 0.018** 0.032** 0.009 0.009 0.011
(0.006) (0.007) (0.011) (0.007) (0.008) (0.016) (0.014) (0.014) (0.017)
Thirteen 0.007 0.013* 0.014 0.004 0.018** 0.035** 0.009 0.009 0.008
(0.007) (0.008) (0.012) (0.007) (0.008) (0.017) (0.015) (0.015) (0.018)
Fourteen 0.003 0.009 0.006 0.003 0.016* 0.033* 0.002 0.002 -0.001
(0.007) (0.008) (0.012) (0.008) (0.009) (0.018) (0.016) (0.016) (0.019)
Fifteen 0.012 0.020** 0.014 0.008 0.023*** 0.028 0.017 0.017 0.011
(0.007) (0.008) (0.012) (0.008) (0.009) (0.018) (0.016) (0.016) (0.019)
Observations 62508 46530 25180 49501 33523 15950 13007 13007 9230
R-squared 0.437 0.454 0.470 0.407 0.452 0.477 0.461 0.457 0.470
Endorsement intensive
Not endorsement intensive
Notes: Coefficients are CARs weighted by firm value, estimated using the model in equation (2). Event date is November 27, 2009. Standard errors are
adjusted for contemporaneous correlation across firms. "Competitors" are the first ten firms listed by Google Finance for each sponsor firm - there are
seventy competitors in all, although some have missing data during the estimation or event window. "All firms," "Big Five" and "Big Three" include
competitors of each group. "Endorsement intensive" firms are those for which a Google search of the company name followed by "endorsement deals"
yields information about at least one current celebrity endorsement deal.
23
PROCTER & GAMBLE CO NIKE INC PEPSICO INC
Church & Dwight Co., Inc. Deckers Outdoor Corp. The Coca-Cola Company
The Clorox Company Crocs, Inc. Coca-Cola Enterprises (bottler)
Colgate-Palmolive Company Skechers USA, Inc. Hansen Natural Corporation
Johnson & Johnson K-Swiss Inc. Jones Soda Co. ( USA )
CCA Industries, Inc. Steven Madden, Ltd. Cott Corporation (USA)
Kimberly-Clark Corporation Heelys, Inc. Dr Pepper Snapple Group
Energizer Holdings, Inc. LaCrosse Footwear, Inc. National Beverage Corp.
Zep, Inc. The Global Housing Group Reed's, Inc.
PC Group, Inc. adidas AG (ADR) Celsius Holdings, Inc.
The Stephan Co. Puma AG Rudolf Dassler Fomento Economico Mexi
T L C VISION CORP ACCENTURE LTD BERMUDA ELECTRONIC ARTS INC
LCA-Vision Inc. Microsoft Corporation THQ Inc.
Hanger Orthopedic Grou Hewlett-Packard Company Microsoft Corporation
U.S. Physical Therapy, Intl. Business Machine Activision Blizzard, Inc.
NovaMed, Inc. Genpact Limited Take-Two Interactive Software
UCI Medical Affiliates Oracle Corporation The Walt Disney Company
Pacific Health Care Or Infosys Tech. Ltd. (ADR) KONAMI CORPORATION (ADR)
Clinica de Marly S.A. Hewitt Associates, Inc. Sony Corporation (ADR)
SHL TeleMedicine Ltd. Dell Inc. Majesco Entertainment Co.
Feelgood Svenska AB Towers Watson & Co Time Warner Inc.
European Lifecare Grou Accenture Plc (Germany) Nintendo Co., Ltd (ADR)
A T & T INC
Verizon Communications
Sprint Nextel Corporation
Qwest Communications I
CenturyTel, Inc.
Apple Inc.
General Communication,
Cbeyond, Inc.
Cincinnati Bell Inc.
Intl. Business Machine
Deutsche Telekom AG (ADR)
Table A1. Sponsors, competitors and "endorsement intensity."
Notes: Each underlined heading is for one of the sponsors listed in Table 1. Next ten rows under each heading
show the first ten firms listed, in order, by Google Finance under "competitors." Competitors are measured
relative to the parent company. Bold competitors are those classified as "endorsement-intensive," meaning that
a Google search for the company name followed by "endorsement deals" yields at least one mention of a
celebrity endorsement contract. Competitor names in italics are not listed on U.S. stock exchanges.
24
7 Figures
Notes: Figure plots the daily cumulative abnormal returns (CARs) from Table 2, cols. 1-3 for
sponsor firms. "Big Five" includes Nike, EA, Accenture, PepsiCo (Gatorade) and P&G
(Gillette). "Big Three" includes Nike, EA and PepsiCo. Horizontal axis indicates number of
trading days after accident.
-0.06
-0.05
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Figure 1. Cumulative Abnormal Returns for Sponsors.
All Sponsors
Big Five Sponsors
Big 3 Spons
25
Notes: Figure plots the daily cumulative abnormal returns (CARs) from Equation 1 for the
"Big Three" of Nike, EA and PepsiCo. Solid line shows the value-weighted average of the
coefficients, and dotted lines show coefficients for the individual sponsors. Horizontal axis
indicates number of trading days after accident.
-0.08
-0.07
-0.06
-0.05
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Figure 2. Big Three Cumulative Abnormal Returns.
Big Three
EA
Nike
Pepsi
26
Notes: Figure plots the daily cumulative abnormal returns (CARs) for Big Three (Table 2,
column 6), endorsement-intensive competitors ("Comps, Endorsers") to the Big Three
(Table 4, column 6) and non-endorsement-intensive competitors ("Comps, Non-endorsers")
to the Big Three (Table 4, column 9). Horizontal axis indicates number of trading days after
accident.
-0.06
-0.05
-0.04
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-0.02
-0.01
0
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0.03
0.04
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Figure 3. CARs for Sponsors and Competitors
Big 3 Spons
Comps, Endorsers
Comps, Non-endorsers
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... Much research has examined the effect of a celebrity's negative publicity on endorsed brands (Bartz et al., 2013;Carrillat et al., 2013;Chung et al., 2013;Fong & Wyer, 2012;Hock & Raithel, 2020;Knittel & Stango, 2013;Louie & Obermiller, 2002;Thwaites et al., 2012; see Table 1). Similarly, research has also investigated the effect of brand crises (negative brand publicity) on consumer perceptions of the firm (see Khamitov et al., 2020;. ...
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... Specifically, positive spillover effects on firm sales were shown after scandals related to toy recalls by Ni et al. (2016). Furthermore, utilizing the scandal related to Tiger Woods' extramarital affairs in 2009, Knittel and Stango (2014) following scandals related to sexual abuse in the U.S. Catholic Church. Piazza and Jourdan (2018) show that these positive spillover effects are particularly concentrated on organizations with similar offerings but with a stricter organizational code of conduct. ...
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