1. School of Business and Economics
Advertising in a Recession
The Effects of Advertising on Brand Equity
Maastricht University
School of Business and Economics
Maastricht, 17.01.2011
Author: Benedikt Laufenberg
i409170
Study: MSc IB / Marketing-Finance
Assignment: Master Thesis
Supervisor: Dr. Elisabeth Brüggen
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2. “There’s no more exiting time to be in the advertising business than during a
recession. All great enterprises move forward in a recession, and the weaklings
move back. The dumbbells cut back on advertising. The smart people don’t.”
Ed McCabe, founding partner, Scali, McCabe, Sloves, Inc.
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3. Table of Contents
Abstract ..................................................................................................................................... 1
I. Introduction........................................................................................................................... 2
II. Literature Review................................................................................................................ 4
1. Effects of Advertising ......................................................................................................................4
1.1. Advertising and Sales Response...............................................................................................4
1.2. Advertising and Firm Value Response .....................................................................................6
2. Advertising in a Recession.............................................................................................................11
2.1. Declining Advertising Expenditures ......................................................................................11
2.2. Effects of Advertising in a Recession.....................................................................................12
3. Hypotheses .....................................................................................................................................14
III. Data and Methodology .................................................................................................... 16
1. Advertising.....................................................................................................................................16
2. Brand Equity ..................................................................................................................................16
3. Other Variables ..............................................................................................................................17
3.1. Three-Year Advertising Growth.............................................................................................17
3.2. Industry Sector........................................................................................................................17
4. Dataset............................................................................................................................................17
5. Regression Modeling .....................................................................................................................18
IV. Analysis and Results ........................................................................................................ 20
1. Descriptive Statistics......................................................................................................................20
1.1. Advertising .............................................................................................................................20
1.2. Brand Equity...........................................................................................................................21
2. Preliminary Analysis......................................................................................................................22
3. Regression Analysis.......................................................................................................................24
3.1. Pre-Tests .................................................................................................................................24
3.2. Results ....................................................................................................................................25
V. Discussion ........................................................................................................................... 28
1. Managerial Implications ................................................................................................................28
2. Theoretical Implications ................................................................................................................29
VI. Limitations and Future Research................................................................................... 30
VII. Conclusion....................................................................................................................... 32
Appendix ................................................................................................................................. 33
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4. Abstract
The main objective of this study is to contribute to the discussion of how firms should adjust
their advertising budget in a recession. Prior researchers find that companies, which increase
their recessionary advertising, mainly benefit in terms of sales and market share. Their studies
are, however, criticized because sales and market share only reflect a firm’s relative
competitive position and are not good indicators of financial success. Literature, which is
dealing with the accountability of marketing, recommends to measure the effects of marketing
on the long-term market value of firms and in particular on the so called market-based assets.
No study has yet analyzed the effects of recessionary advertising on market-based assets. To
close this gap in the literature, this paper relates advertising expenditures to the market-based
asset that is mainly created and maintained by advertising efforts, the firm’s brand equity. By
the means of multiple regression analysis, the relation between advertising and brand equity is
analyzed for an expansion year (2004/2005) and a recession year (2007/2008). It is found that
the relation is positive during both periods which implies that advertising increasers generally
build brand equity, whereas advertising decreasers destroy it. Second, it can be shown that the
relation is stronger during a recession than during an expansion. This suggests that advertising
is a very effective tool to increase brand equity during economic downturns. Overall, this
study finds strong arguments to resist the cost cutting pressure during recessions and to
maintain or even increase the recessionary advertising budget. An overview of the managerial
and theoretical implications of the results, as well as some recommendations for future
research are given at the end of the paper.
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5. I. Introduction
Today’s globalized business world is characterized by fierce competition (Rogoff, 2006) and
requires companies to operate in a very cost efficient way. The different departments within a
firm have to carefully account for their spending and to demonstrate the contribution of their
efforts to financial performance. In the past, marketers often failed to do so because they
evaluated their activities based on sales and market share that only reflect a firm’s relative
competitive position (Day and Fahey, 1988). Hence, they often had problems to identify,
measure and communicate the financial value of their activities (Srivastava, Shervani, and
Fahey, 1998). This lack of financial accountability undermined marketing’s credibility and
challenged its existence within the firm (Rust, Ambler, Carpenter, Kumar, and Srivastava,
2004). With the emergence of the shareholder value concept in the 1980s it became
increasingly important to demonstrate the contribution of business decisions to the firm’s
long-term market value. In line with that development, researchers started to analyze the
impact of marketing activities on shareholder value (e.g. Anderson, Fornell, and
Mazvancheryl, 2004; Gruca and Rego, 2005; Srivastava et al., 1998; Wang, Zhang, and
Ouyang, 2008). Those investigations set a milestone in the ‘accountability of marketing
discussion’ because it could be shown that marketing develops so-called market-based assets
that, in turn, have a positive impact on shareholder value. The current study is an attempt to
extend this literature stream by analyzing advertising effects on market-based assets in the
context of a recession.
During recessions, managers are often looking for expenses that can be easily reduced
without disrupting the firm’s operations. Marketing expenditures are predestinated for this
and, therefore, usually the first to be cut (Shaw and Merrick, 2005). How those cutbacks
affect the value of firms is not very clear. Despite the severe effects of recessions on
marketing, little research exists about it. A few researchers study recessionary advertising
effects on a firm’s level of sales, market share or earnings (e.g. Aaker and Carman, 1982;
Clarke, 1976; Graham and Frankenberger, 2000; Leone, 1995; Tellis, 2009; Tull, 1986). No
study, however, examines the long-term effects of advertising on the firm’s most valuable
assets, its market-based assets. In an attempt to close this gap in the literature, this paper
analyzes the relationship between recessionary advertising and brand equity, one of the most
important market-based assets. In a second step, the relation between advertising and brand
equity is analyzed in a non-recessionary period. A comparison of the results will help to
answer the central question:
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6. “How should firms adjust their advertising budget in a recession?”
The remainder of this study is structured as follows: Chapter II reviews relevant literature on
advertising effectiveness and introduces the hypotheses. Chapter III presents the data and
develops the methodology used for this investigation. The results are reported in chapter IV
and discussed in chapter V. Chapter VI highlights the study’s limitations and provides
suggestions for future research. The conclusion, outlined in chapter VII, summarizes the main
findings and gives an answer to the central question of this research.
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7. II. Literature Review
Before answering the question of how firms should adjust their advertising budget in a
recession, it is necessary to understand how advertising works and how it affects a company.
This understanding is provided in the first part of this chapter followed by a review of studies
on advertising in a recession.
1. Effects of Advertising
Advertising can be defined as “any non-personal presentation and promotion of ideas, goods
or services by an identified sponsor” (Keller, Apéria and Georgson, 2008, p.230). It is usually
communicated through various media channels, such as television, radio, newspapers,
magazines, internet or billboards, and it intends to persuade potential customers to purchase a
certain product or service. In order to show how value-adding advertising is for a company,
marketers need to measure the return on their efforts. This chapter discusses two common
ways of how to measure the return on marketing. The first one is more short-term oriented
and considers market-response measures such as sales or market share. The second takes a
long-term perspective and measures the economic (cash flow-derived) benefits created by
marketing. The focus of this second approach is on the value components of firms. Mainly
discussed are the effects of advertising on market-based assets as well as on the firm’s
shareholder value. An extensive overview of literature on sales and firm value response to
advertising is provided in the following two subsections.
1.1. Advertising and Sales Response
The marketing literature to date mainly focuses on the sales response to advertising (Joshi and
Hannsens, 2010). This might be due to the fact that advertising is often understood as a tool
that helps to produce sales (Lavidge and Steiner, 1961). This was already taught in the 1960s
when Lavidge and Steiner developed the hierarchy-of-effects model (see Figure 1). At the
bottom of the hierarchy are the potential customers who are not yet aware of the existence of
a product or service while at the top are the ones who are already purchasing it. The main task
of the advertiser is to guide the potential customer through the different stages of the
hierarchy (awareness, knowledge, liking, preference, conviction and purchase) and make her
loyal to the company’s products or services. Frequent purchases of loyal customers finally
increase the sales of a company. Hence, it makes sense to measure advertising effectiveness
by relating advertising expenditures to the company’s sales. In the past, researchers agreed
that this is one of the most difficult and complex problems in marketing (e.g. Bass, 1969;
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8. Simon and Arndt, 1980). Although it is still a big challenge today, it became easier over the
last two decades. The ability to accurately evaluate the effects of advertising has grown
because technology became more advanced and databases more extensive. According to Hess
and Ambach (2002), researchers in the 60´s still relied on data of warehouse withdrawals to
measure sales and market share. Then, in the 70’s, universal-product-code scanners emerged
which made it possible to correlate information on customer purchases directly with the
information on advertisements those customers receive. Today, comprehensive tools, such as
the Nielsen TV Audience Measurement, accurately track a program’s minute-to-minute
audiences and help firms to measure the effectiveness of their campaigns.
Figure 1. Hierarchy of Effects Model
Purchase
Conviction
Preference
Liking
Knowledge
Awareness
Research focusing on sales response to advertising, is referred to as sales or market response
analysis (Vakratsas and Ambler, 1999). In order to estimate how the market responds to
advertising, researchers often calculate advertising elasticity, which is the percentage change
in sales for a 1% change in the level of advertising. After summarizing a great number of
studies using data across many time-periods, brands, product categories and countries, Tellis
(2009) arrives at the empirical generalization that sales change by about 0.1% if advertising
changes by 1%. Additionally, the author concludes that the elasticity is higher in Europe than
in the United States, for durables than for non-durables, for new products than for established
products, and for print advertisements than for TV advertisements. Next to the impact of
advertising also the duration of its effects is important. As one of the first researchers, Clarke
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9. (1976) provides a general answer to the question of how long advertising affects sales. After
reviewing 69 studies of the econometrics literature he concludes that the effect only lasts for
months rather than years. Many researchers after Clarke also analyzed the duration period but
arrive at widely varying estimates. The inconsistency of those results was not helping
marketers to make accurate decisions about an appropriate size of their advertising budget.
Leone (1995) brought an end to this uncertainty. He reasons that the level of data aggregation
(e.g. monthly data) across the studies is responsible for the variation in results. After
reviewing relevant literature and adjusting for aggregation bias he finds that the effects last
between six and nine months.
Overall, it can be concluded that advertising has an impact on sales and that it can be
quantified by its strength and the duration of effects. However, it should not be forgotten that
the success of an advertising strategy also depends on external factors, such as competitor
behavior or customer trends, which are often not predictable. Many companies, therefore,
have difficulties to determine the optimal advertising budget and often allocate too much
money to it (Aaker and Carman, 1982; Tull, 1986). According to Aaker, Carman and Tull
this might not necessarily be a disadvantage if it stays within a certain band around the
theoretical optimum. Tull states that overspending on advertising by as much as 25% may be
relatively inexpensive and can even produce long-term benefits by increasing sales and
market share.
1.2. Advertising and Firm Value Response
Relating marketing activities all the way to a firm’s financial position has been widely
neglected in the literature and only recently attracted researcher’s attention. In the previous
section it is shown that marketing effectiveness was traditionally determined by looking at
sales responses. According to Day and Fahey (1988) those responses do, however, only
reflect a firm’s relative competitive position and are not appropriate indicators of financial
success. As a consequence, the marketing function often has problems to justify its
expenditures and to demonstrate the value it adds to the firm. This lack of financial
accountability has not only undermined marketing’s credibility; it “even threatened
marketing’s existence as a distinct capability within the firm” (Rust, Ambler, Carpenter,
Kumar, and Srivastava, 2004, p.76). The accountability of marketing expenditures is one of
the major research priorities of the Marketing Science Institute (2010) for the years 2008-
2010 and, therefore, it is of crucial importance to investigate the link between marketing
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10. activities and the value of a firm. Traditionally, the marketer’s goal was to create value for
customers, ignoring the fact that shareholders are the true owners of a company (Srivastava,
Shervani, and Fahey, 1998). Today, researchers (Day and Fahey, 1988; Srivastava et al.,
1998) suggest that every investment, be it in the area of human resources, operations or
marketing, should be evaluated based on its contribution to shareholder value. For marketers
it means that they should go for marketing strategies that achieve returns exceeding the cost
of invested capital and that result in positive net present values (Day and Fahey, 1988; Koller,
1994). Those strategies help to increase the share price of a company or more specifically the
firm’s shareholder value. The main advantage of taking shareholder value as a performance
measure is its risk-adjusted and forward-looking characteristic and that it integrates different
performance dimensions, such as earnings volatility, cash flows, and profits (Day and Fahey,
1988; Deleersnyder, Dekimpe, Steenkamp, and Leeflang, 2009). It reflects the long-term
value of a firm and, therefore, is a better indicator of financial health than other, short-term
oriented measures such as sales or market share. The shareholder value approach became
popular in the 1980s (Bloomberg Businessweek, 2009) when Jack Welch, former CEO of
General Electric, suggested that every business decision should first and foremost benefit the
shareholders of a company. Ever since, shareholder value gained in importance (Day and
Fahey, 1988; Lukas, Whitwell, and Doyle, 2005; Srivastava et al., 1998) and became a
corporate performance standard to evaluate investment proposals.
Evaluating marketing expenditures based on their contribution to shareholder value is a rather
new trend in the marketing literature. It was done by, for example, Chauvin and Hirschey
(1993), Conchar, Crask, and Zinkhan (2005), Graham and Frankenberger (2000) and Miller
and Mathisen (2008) who find that advertising affects firm value over multiple periods of
time. Due to the potential of advertising to increase the long-term value of a firm the
researchers even argue that advertising should be treated as a capital expenditure rather than
as an expense1. Miller and Mathisen show that investments in advertising are more valuable
than investments in any recorded assets and that they have a lifetime value of two years.
Chauvin and Hirschey observe a positive relation between advertising and market value for
companies across manufacturing and non-manufacturing sectors. They control for firm size
and, thereby, find that the valuation effects are typically greater for larger firms than for
smaller firms. Graham and Frankenberger compare companies in different industries and
1
US GAAP requires marketing expenditures to be expensed against revenues.
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11. show that advertising expenditures affect earnings up to five years after the year of the
expenditure. Those effects have a subsequent impact on the market values of companies,
being shortest lived for companies in the sales and services industry and longest lived for
companies in the industrial products industry. On average, Graham and Frankenberger report
that the asset value of advertising expenditures has a three-year life with the greatest value in
the current year and declining value in subsequent years. The study by Conchar et al.
aggregates the findings of a great number of market valuation models in a meta-analysis. The
results strongly support the positive effects of advertising on a firm’s market value and,
hence, on the wealth of shareholders.
The next three sections go more into detail on the effects of advertising on firm value. In
particular, it is reviewed how advertising effects the intangible value of firms. Since
intangible assets play an increasing role in today’s business world (Lindemann, 2004)
researchers start to focus particularly on the relationship between advertising and the so-
called intangible market-based assets.
a) Intangible Firm Value
The importance of intangible firm value only emerged in the last quarter of the 20th century
(Lindemann, 2004). Before that time, tangible assets such as manufacturing assets, land,
buildings or financial assets were seen as the main source of firm value. In the 1980s, large
premiums were paid in mergers and acquisitions, and the gap between market and book
values of companies was increasing. Today it is widely accepted that this gap is due to
intangible assets and that the majority of firm value is derived from those assets (Lindemann,
2004; Srivastava et al., 1998). Srivastava et al., for example, find that more than 70% of a
company’s market value lies in intangible assets.
In an attempt to relate marketing activities to intangible assets, Srivastava et al. (1998)
developed a framework which proposes that marketing develops and manages intangible
market-based assets that, in turn, increase shareholder value by accelerating and enhancing
cash flows, reducing the volatility and vulnerability of cash flows, and by increasing their
residual value. The authors distinguish between intellectual market-based assets that are
created through the knowledge a firm possesses about an environment, and relational market-
based assets that are the outcome of relationships with different stakeholders of the company.
Since advertising establishes relationships between a company and its customers it mainly
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12. contributes to the development of relational market-based assets, such as brand equity
(Srivastava et al., 1998).
b) Brand Equity
The first precise definition for brand equity was given in 1988 when The Marketing Science
Institute organized a conference on “Defining, Measuring, and Managing Brand Equity”. At
this conference, brand equity was defined as: “the set of associations and behavior on the part
of a brand's customers, channel members and parent corporation that permits the brand to
earn greater volume or greater margins than it could without the brand name” (as cited in
Wood, 2000, p.663). In short, brands influence the choices of different stakeholders and
thereby contribute to the profitability of a firm.
The idea that brands contribute to business success is widely accepted today. It is also known
that brands often account for the majority of overall firm value. The McDonalds brand equity,
for example, accounted for more than 70% of shareholder value in the year 2004 (Lindemann,
2004). PricewaterhouseCoopers and Sattler (2005) show that the brand of an average German
firm represented about 56% (67%) of total firm value in the year 1999 (2005). Despite the
importance of brand equity in today’s organizations, quantitative brand valuations are rarely
conducted (Zimmermann, Klein-Bölting, Sander and Murad-Aga, 2002). This is surprising
because value-oriented brand management does not only concern brand managers; it also
plays a major role for other business functions, such as controlling. Zimmermann et al., from
the worldwide advertising agency BBDO, mention four reasons why brands should be
evaluated. First, they argue that brand valuations allow for better brand controlling. Due to
rising marketing expenditures, managers need a quantifiable basis to justify the investment
character of their expenditures. By reporting the monetary value of brands over time, they can
better assess the long-term effects of their marketing activities. Second, it facilitates the
negotiation process when selling/buying a brand. Third, it helps to negotiate a license fee in
case the brand is licensed to another company. Fourth, in case of trademark infringement,
monetary brand values can be used to determine a compensation for the suffered loss.
Lindemann (2004), Managing Director of Interbrand Global Brand Valuation, states that
brand valuation models can be categorized into two groups: Research-based brand equity
valuations and purely financially driven approaches. Research-based brand equity valuations
use consumer research to analyze the relative performance of brands. They do not consider
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13. any financial value but measure consumer behavior and attitudes that influence the economic
performance of brands. Perceptive measures are used in those models as, for example,
different levels of familiarity, purchase consideration, preference, satisfaction or awareness.
The financially driven approaches can be sub-categorized into cost-based approaches,
comparables approach, premium price approach and economic use approach. Lindemann
argues that the economic use approach is the most widely recognized and accepted
methodology for brand valuation because it combines marketing and financial components,
and it is not like the other approaches, just driven by one of them. It incorporates marketing,
financial and legal aspects, follows fundamental accounting concepts, allows for regular
evaluation in a consistent way and is suitable for acquired and home grown brands (Keller et
al., 2008). Overall, the approach evaluates brand value by determining the present value of
cash flows that a brand is expected to generate in the future.
A few years ago Interbrand as well as some other firms (e.g. MillwardBrown and BBDO)
recognized the need to express brands in monetary terms and started to report brand values on
a regular basis. The economic use approach applied by Interbrand evaluates brands by going
through the following steps. First, the consumer market for a brand is split into non-
overlapping and homogenous groups of customers. Second, the earnings generated by a brand
are forecasted for every segment by subtracting operating costs, applicable taxes and a charge
for employed capital from the branded revenues. Third, the role2 that a brand plays in driving
demand is assessed. By multiplying the role of branding by the intangible earnings derived in
the second step the brand’s earnings are calculated. Fourth, the competitive strengths and
weaknesses of the brand are assessed. Based on that fourth step, the brand discount rate,
which reflects the risk profile of the expected future earnings, is derived. Finally, the
forecasted earnings are discounted at the brand discount rate in order to arrive at the net
present value of the brand.
c) Advertising – Brand Equity – Shareholder Value
According to Srivastava et al. (1998), brand equity is the result of extensive advertising.
Although other marketing efforts are also important in building and maintaining brand equity,
Ailawadi, Farris and Parry (1994) and Keller et al. (2008) argue that advertising plays the
greatest role. The relation between advertising and brand equity is confirmed by a very recent
2
The role that a brand plays in driving demand is expressed by the “role of branding index”. This index stands
for the percentage of intangible earnings that are generated by a brand.
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14. study from Wang, Zhang, and Ouyang (2008). The results indicate that the intermediate
effects of advertising on shareholder value (i.e. the effects of advertising on brand equity) are
accumulative and sustainable and support the investment-like characteristic of advertising
expenditures. Other researchers (Kerin and Sethuraman, 1998) focus on the relation between
brand equity and shareholder value and observe that brand equity is positively associated with
the market value of firms. Furthermore, it is found that this relation is often stronger than the
relation between book value, or net income and the firm’s market value (Barth, Clement,
Foster, and Kaszkik, 1998).
This first part of the literature review critically examined studies which illustrate the effects of
advertising on different performance measures. It becomes clear that most of them
concentrate on the sales response to advertising. There is, however, an increasing interest in
the effects of advertising on shareholder value. In order to relate marketing efforts, such as
advertising, to shareholder value, researchers (e.g. Srivastava et al., 1998) suggest to focus on
the intermediate market-based assets. Since brand equity is one of the most important
(market-based) firm assets (PricewaterhouseCoopers and Sattler, 2005) and directly
dependent on advertising, special attention was, and further is, directed to the relationship
between advertising and brand equity in this study. In the following, the terms brand equity
and brand value are used interchangeably.
2. Advertising in a Recession
During recessions marketers usually decrease their advertising budgets. So far, only a few
researchers studied in how far those changes affect the performance of firms. Before
reviewing those studies in subsection 2.2 it is examined how firms usually adjust their
advertising budgets in a recession.
2.1. Declining Advertising Expenditures
What is a recession? Analysts usually refer to a recession when economic activity, measured
by real GDP, is declining for at least two consecutive quarters (Claessens and Kose, 2009).
The National Bureau of Economic Research (NBER) uses a broader definition. NBER’s
Business Cycle Dating Committee (Hall et al. 2003, p.1) defines a recession as “a significant
decline in economic activity spread across the economy, lasting more than a few months,
normally visible in real GDP, real income, employment, industrial production, and
wholesale-retail sales. A recession begins just after the economy reaches a peak of activity
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15. and ends as the economy reaches its trough. Between trough and peak, the economy is in an
expansion. Expansion is the normal state of the economy; most recessions are brief and they
have been rare in recent decades.”
It is widely known that companies often cut back their costs during recessions. Marketing
budgets in general and advertising budgets in particular are such endangered targets. This is
supported by an investigation of KPMG which illustrates that the budget most likely to be cut
is the one of marketing. Marketing budgets are reduced with a probability of more than 20%
followed by cuts in Human Resources, Training, R&D and IT budgets (Shaw and Merrick,
2005). Picard (2001) was one of the first who studied economy effects on advertising
expenditures and concludes that a 1% (3%, 6%) decline in GDP is generally accompanied by
a 5% (10%, 15%) decline in advertising expenditures. Another study (Deleersnyder et al.,
2009) observes that 88% of firms cut their advertising expenditures during economic
downturns and increase them during expansions. On average, Deleersnyder et al. find that a
1% change in GDP results in a 1.4% change in advertising expenditures in the same direction.
Two main reasons are discussed in the marketing literature why advertising budgets are cut in
a recession (Dhalla, 1980; Tellis, 2009). First, executives hope to increase short-term
profitability. Second, executives think that they can maintain their market position by reacting
in the same way as their competitors. By reviewing literature on the effectiveness of
recessionary advertising in the next section, it is determined whether those arguments can be
justified.
2.2. Effects of Advertising in a Recession
The previously reviewed studies demonstrate that companies usually decrease their
advertising expenditures in a recession. Although there might be good reasons for doing so
(e.g. companies become financially constrained and consequently have to cut back their
costs), one should be aware of the subsequent effects of lowering the marketing budget.
Thomas Garbett (1988) analyzes the dramatic case of discontinuing advertising and finds that
the customer’s attitude about a company is likely to quickly deteriorate and to shift in
unintended directions. This, in turn, has a negative impact on the firm’s profitability. Some
researchers argue that an increase of advertising during a recession would generally be a
better choice. The idea to maintain or increase advertising expenditures during a recession
first came up in the 1920s when Vaile (1926) analyzed 200 companies in the 1923 recession.
Overall, he finds that an increase of advertising is associated with sales growth for up to four
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16. years after the recession. The more recent article by Kamber (2002) concludes that an
advertising increase during a recession leads to an immediate boost of sales that diminishes in
the years thereafter. Other studies investigate the effects on market share rather than on sales.
Kijewski (1982), for example, finds that it is a lot easier to capture market share from
competitors by making use of countercyclical advertising. In particular, she finds that 80% of
business units in her sample increase advertising expenditures during an expansion, while
only 25% increase advertising expenditures during a recession. Overall, she concludes that
the effectiveness of advertising is a lot higher during a recession when companies are
operating in a soft advertising market in which advertising competition is reduced. Biel and
King (1990) arrive at a similar conclusion and additionally emphasize that large increases of
recessionary advertising are much more productive than modest increases. It can be
concluded that a drastic increase of advertising expenditures in a recession is more effective
(with respect to sales and market-share growth) than an increase of advertising expenditures
during an expansion.
As it is stated in section 1.2 in the literature review, focusing on sales and market share alone
only informs about a firm’s relative competitive position but does not provide information
about a company’s financial success. To the author’s knowledge, no study exists that relates
recessionary advertising directly to the shareholder value or market-based assets of
companies. However, the studies discussed in the following take some other financial
measures into account. Kijewski (1982) analyzes the impact of advertising expenditures on
the return on investment and concludes that increases as well as decreases in advertising
neither lead to a major loss nor an increase in profits. Biel and King (1990) find that a modest
increase in advertising has about the same negative impact on ROI as a decrease in
advertising. A more recent study from Frankenberger and Graham (2003) investigates the
effects of advertising expenditures on earnings under normal economic conditions and
compares them with the effects of decreased and increased advertising expenditures during
recessionary periods. The authors concentrate on consumer products, industrial products and
services firms and find that the latter show no benefit from increased advertising spending
while the others do benefit due to an increase in short-term and long-term earnings. They also
demonstrate that firms, which reduce advertising in a recession, maintain their status quo
because they are carried through by past advertising efforts as long as they survive.
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17. Overall, the results in this section are not consistent enough to provide clear recommendations
on how to deal with advertising expenditures in a recession. Sales and market share are likely
to be positively affected by an increase of advertising, yet financial measures, such as ROI or
earnings, do not necessarily move upwards. Furthermore, most of the studies evaluate
advertising based on its short-term effects. Earlier, it was explained that firm investments
should be evaluated based on their contribution to long-term shareholder value. In particular,
marketing expenditures should be evaluated based on their contribution to market-based
assets (Srivastava et al, 1998). To the author’s knowledge this has not been done with
recessionary advertising expenditures so far. The current paper aims to close this gap in order
to better advise managers on how to adjust their advertising budget in a recession. To do that,
advertising expenditures are related to the market-based asset that is mainly created and
maintained by advertising efforts, the firm’s brand value.
3. Hypotheses
After having reviewed literature on market-based assets in section 1.2., it should be clear how
important advertising is as a source of brand equity and brand equity as a contributor to total
firm value. So far, no study exists that examines the relation between advertising and brand
equity in a recession. Hence, it is rather difficult for marketers to justify why they should
maintain or even increase their budgets in periods when most of the other functions cut back
their costs. Although some firms might not have the financial resources to maintain or even
increase their budgets in a recession, it is questionable whether the general trend to reduce
advertising expenditures can be justified. Managers might defend their decisions based on the
two arguments mentioned earlier: First, by cutting marketing expenditures short-term
profitability can be increased. Second, if competitors cut their advertising one can do the
same because the market position would be maintained. As it is shown earlier, those
arguments are not necessarily correct (in terms of ROI, advertising decreasers are not better
off than advertising increasers; in terms of sales, market share and earnings, advertising
increasers do benefit) and only reflect a short-term orientation that is not in line with the long-
term shareholder value orientation that companies should apply.
Analyzing the relation between recessionary advertising and brand equity should provide
deeper insights on how to adjust the advertising budget in a recession. Prior researchers
confirm a positive relation between advertising and brand equity during non-recessionary
periods (e.g. Wang et al., 2008). Whether the relation is also positive during recessions still
14

18. needs to be tested. This is done the means of the following hypothesis:
H1: The relation between recessionary advertising and brand equity is positive.
A confirmation of the hypothesis would mean that an increase of recessionary advertising
would be value enhancing, and a decrease of recessionary advertising would be value
destroying. This finding alone might, however, not be strong enough to provide a
recommendation on how to adjust the advertising budget in a recession. A more solid
suggestion could be provided if it could be proven that the effects of advertising on brand
equity are stronger during a recession than during an expansion. In that case, firms should
truly consider to at least maintain or even increase their recessionary advertising budgets.
Based on the fact that competitive advertising is generally reduced during economic
downturns, the previously reviewed studies reveal that advertising is more effective during
recessions than during expansions with respect to sales, market share (Biel and King, 1990;
Kijewski, 1982) and earnings (Frankenberger and Graham, 2003). It can be expected that this
is also true with respect to brand equity. By the means of the following hypothesis, this can be
tested.
H2: The relation between advertising and brand equity is stronger during a recession than
during an expansion.
A graphical representation of the hypotheses is shown in Figure 2. The left hand side
visualizes the expected positive relation (indicated by the plus signs) between recessionary
advertising and brand equity (hypothesis 1). The right hand side visualizes hypothesis 2. The
thickness of the arrows indicates that the relation between advertising and brand equity is
expected to be stronger during a recession than during an expansion.
Figure 2. Hypotheses
15

19. III. Data and Methodology
This chapter presents the methodology used to test the two hypotheses. First, the different
variables and data sources are discussed followed by a presentation of the final dataset. Next,
the regression model applied for this research is introduced.
1. Advertising
As discussed earlier, many researchers relate expenditures of advertising to different
performance measures in order to analyze the effectiveness of advertising. Hence, advertising
expenditures seem to be a good measure to quantify the advertising efforts of firms.
Advertising expenditure data is obtained from the Standard & Poor’s Compustat North
America database which provides U.S. and Canadian market information on more than
24,000 active and inactive publicly held companies. Compustat is considered the most
reliable source of corporate financial data available (Kamber, 2002) and it is widely used by
academic researchers. The previously mentioned studies by Chauvin and Hirschey (1993),
Frankenberger and Graham (2003), Graham and Frankenerberger (2000), Kamber (2002) and
Miller and Mathisen (2008) do, for example, rely on Compustat data. The yearly advertising
expenditures available from the database represent the cost of advertising media (i.e., radio,
television, and periodicals) and promotional expenses. This study is mainly interested in the
effects of changes in advertising expenditures. Therefore, not absolute advertising
expenditures are used in the analysis but the percentage change of advertising from one year
to another. As it is shown later, those changes are regressed on changes in brand equity by the
means of multiple regression analysis.
2. Brand Equity
Brand equity is an intangible asset that is not consistently recognized in the financial
statements of firms. This has three reasons. First, US GAAP does not require the reporting of
internally developed brands. Second, only acquired brands have to be recognized and
amortized against net income over the brand’s estimated life. Third, changes in brand values
are largely unaccounted for, even for brands recognized as assets (Barth, Clement, Foster, and
Kaszkik, 1998). Due to the lack of brand equity information in the financial statements, it is
not possible to retrieve brand values from the Compustat database. Fortunately, a few firms
(e.g. MillwardBrown, BBDO Consulting, Interbrand) are specialized in the evaluation of
brands and make their estimates publicly available. The 100 Best Global Brands rankings
16

20. from Interbrand make up the largest3 available dataset of such data. Brand values are,
therefore, retrieved from these rankings.
3. Other Variables
Other factors, such as the remaining components of the marketing mix, also have an impact
on brand equity (Srivastava et al., 1998). Hence, they should be controlled for in the
regression analysis. However, due to data availability constraints as well as for practical
reasons, those components are excluded from the present analysis. Additional variables,
which are considered in the regression analysis, are described in the following.
3.1. Three-Year Advertising Growth
Wang, Zhang, and Ouyang, (2008) find that the effects of advertising on brand equity are
sustainable and accumulative. Hence, the advertising efforts of previous periods are likely to
affect future brand equity growth as well. Therefore, a variable explaining three-year
advertising growth prior to the year of interest is included in the regression analysis.
3.2. Industry Sector
The most recent Best Global Brands report from Interbrand (Interbrand, 2010) shows that
there are large differences of brand equity growth across industries. For example, the Best
Global Brands from the financial services sector experienced a -5% (-40%) brand value
decline in 2008 (2009), while the average brand value of the Fast Moving Consumer Goods
sector increased by 4% (12%) in 2008 (2009). Hence, there seems to be a relation between
brand equity growth and a company’s industry belonging. To avoid bias in the results,
industry effects are accounted for by adding industry dummies (based on two-digit Standard
Industry Classification codes) to the regression model.
4. Dataset
To obtain a suitable sample for the present analysis Interbrand data is merged with Compustat
data. The following points discuss the factors that determine the size of the final sample.
- Data from Interbrand constrains the sample to brands that were listed as one of the 100
Best Global Brands since the year 2001.
3
The brand value rankings from Interbrand last back until the year 2001. Therewith, it is the largest publicly
available dataset to the knowledge of the author.
17

21. - Compustat provides advertising data for companies and not the individual brands of
companies. This further limits the sample to corporate brands.
- Data on advertising expenditures is only provided for firms that voluntarily publish
how much they spend on advertising and that are listed on North American stock
exchanges.
The time period used in the present analysis further constrains the sample. For the recession
period, the most recent economic recession in the US is chosen. Only shortly before the
completion of this study, the National Bureau of Economic Research announced that the most
recent recession lasted from December 2007 until June 2009 (NBER, 2010). During that
period real GDP declined in the first, third and fourth quarter of the year 2008 and in the first
and second quarter of the year 2009 (see appendix, exhibit 1.1). With a duration of 18 months
it was the longest recession since World War II (NBER, 2010). Since advertising, as well as
brand value data is only available on a yearly rather than on a monthly basis, it would be
relatively difficult to account for advertising effects in December 2007 and during the first
two quarters of the year 2009. Hence, it is decided to not investigate the entire recession
period but to focus on the year 2008 as the recession year (i.e. January 2008 – December
2008). To determine the effects of advertising during an expansion a period is chosen that
experienced relatively high growth in real GDP. Furthermore, it is considered that the time
interval between recession and expansion is small. Based on these criteria the year 2005
(GDP grew by a about 3% from 2004 to 2005, see appendix, exhibit 1.2) is chosen as the
expansion year.
The final sample consists of 32 corporate US brands (see appendix, exhibit 2). The reader
should be aware that this number is larger than the number of brands available in any one
year. This is due to the fact that a brand listed on the Best Global Brand list in one year might
not be listed in the year after.
5. Regression Modeling
The study at hand aims to analyze the relationship between a response variable (change in
brand value) and some independent variables (change in advertising, prior advertising growth,
and industry dummies). A powerful procedure to analyze relationships between a dependent
and independent variable is regression analysis (e.g. Malhotra, 2007; Pallant, 2007). It
determines whether the independent variable can explain a significant variation in the
18

22. dependent variable as well as how much of this variation can be explained. Furthermore, it
allows to control for additional independent variables. Two multiple regressions are run in
this study; one to determine the strength of advertising effects on brand value in a recession;
and another to determine the same effects during a non-recession period. A comparison of the
regression results is expected to provide insights on how to adjust the advertising budget in a
recession.
Based on the discussion in this chapter the following regression equation is set up to analyze
the relationship between changes in advertising and changes in brand value:
Change in Brand Equity = a + β1* Change in Advertising + β2* Prior Three-Year
Advertising Growth + β3* Industry dummies + error
To test hypothesis I, the following regression model (Model 1) is derived from the equation:
BE0708 = a + β1* Adv0708 + β2* Adv0407 + β3* Industry dummies + ε
A second regression model (Model 2) tests hypothesis II. This model investigates the non-
recessionary advertising effects on brand equity:
BE0405 = a + β1* Adv0405 + β2* Adv0104 + β3* Industry dummies + ε
19

23. IV. Analysis and Results
This chapter presents the empirical results. To get an overview of the data and to better
understand the relationships underlying the analysis, descriptive statistics are discussed in the
first part of this chapter. After that, preliminary findings based on bivariate correlations are
presented. The last part provides a first discussion of the regression results.
1. Descriptive Statistics
1.1. Advertising
Figure 3. Average percentage change in advertising expenditures for the years 2004-2005,
2005-2006, 2006-2007, 2007-2008
14.00%
12.00%
10.00%
8.00%
6.00%
4.00%
2.00%
0.00%
-2.00% Adv0405 Adv0506 Adv0607 Adv0708
-4.00%
Note: Figure 3 is based on mean value data from Exhibit 2.1.b
Adv0405, Adv0506, Adv0607, Adv0708 stand for the percentage change of advertising from one year to another.
For example, the Adv0405 bar shows that the average firm spent almost 12% more on advertising in 2005 than in 2004.
The literature review illustrates that companies usually decreased their advertising
expenditures during previous recessions. Figures from the marketing and advertising
Research Company Nielsen indicate that firms also cut back on advertising during the 2008
recession. Nielsen finds that U.S. advertising expenditures declined by almost $3.7 billion to a
total amount of $136.8 billion in the year 2008 (Nielsen, 2009). A recessionary downward
trend of advertising can also be observed for the companies in the present sample. Figure 3
demonstrates the average yearly percentage change of advertising expenditures between the
years 2004 and 2008 (see appendix, exhibit 2.1 for a complete overview of the descriptive
statistics on advertising data). During the non-recession years between 2004 and 2007, the
average company increased its advertising every year. On the contrary, advertising
expenditures were decreased during the 2008 recession period. By comparing these changes
with the yearly changes in GDP over that same time frame (see appendix, exhibit 1.2 for
changes in real GDP), one gets an idea of how companies adjust their advertising
20

24. expenditures in different economic situations. Advertising and GDP changes move in the
same direction for each of the years which indicates that the average company is likely to be a
procyclical advertising spender. In other words, the average company tends to increase
advertising during an expansion and to decrease it during a recession.
Exhibit 2.2 in the appendix shows the recessionary and non-recessionary advertising growth
rates for the individual companies in the sample. It can be seen that Ford, Dell, Yahoo and
Oracle are typical procyclical advertising spenders. They all spent over 20% more on
advertising in 2005 than in 2004, and they decreased their spending by more than 14% from
2007 to 2008. While most of the firms cut back on advertising or maintained their level, some
firms spent a lot more. Visa (41%) and Amazon (27%), for example, invested heavily in their
advertising campaigns during the year 2008. In absolute terms, Ford was the firm that
invested the most in advertising. The car manufacturer spent about $4.6 billion during the
recession year and $5.4 billion during the expansion year. Accenture, for example, spent far
less money on advertising. In 2005 the consulting firm invested about $66 million in its
advertising campaigns; in 2008 it was about $91 million.
1.2. Brand Equity
The average brand value was between $14.8 billion (in 2005) and $17.1 billion (in 2008)
during the analyzed period. (see appendix, exhibit 2.3 for a complete overview of descriptive
statistics on brand equity data). Earlier, it was illustrated that brand value often accounts for a
large part of overall firm value. In an attempt to check how much of the market value is made
up by brand value for the firms used in the present analysis, brand-to-market value ratios
(BE/MV) are calculated for all brands for which sufficient data is available (see Table 1).
50% of the companies have brand values that represent more than one third of their overall
value. The three firms with the largest ratios are Harley Davidson, Tiffany and Co and Ford.
With ratios of more than 75%, these firms derive the majority of firm value from their brands.
Although the second column in Table 1 shows corporate brands with smaller BE/MV ratios,
it can be concluded that brand value generally makes up a significant value component for the
companies in the sample.
The brand value estimates and brand value changes for the individual companies are shown in
exhibit 2.4 in the appendix. The firms that experienced the largest brand value increase during
the recession year were Apple and Google. Google’s brand value rose by about 30%, while
21

25. Apple was the closest follower with an increase of almost 20%. On the contrary, Ford (-
13.75%) and GAP (-25.80%) experienced the greatest decline during that period. In absolute
terms, Coca Cola ($66.7 billion) was the most valuable brand. IBM and Microsoft closely
followed with brand values of about $59 billion. Starbucks, Motorola and Visa were situated
at the bottom of the brand value ranking with values between $3 billion and $4 billion.
Table 1. Brand-to-market value ratios 2008
Rank Corporate Brand BE/MV 2008 Rank Corporate Brand BE/MV 2008
1 Harley Davidson 100% 15 Intel 29%
2 Tiffany & Co 90% 16 Ebay 26%
3 Ford 76% 17 Microsoft 25%
4 Coca Cola 55% 18 Motorola 23%
5 Disney 54% 19 Amazon 23%
6 Kellogs 51% 20 Hewlett-Packard 22%
7 McDonalds 47% 21 Yahoo 20%
8 Heinz 46% 22 Google 19%
9 IBM 40% 23 Colgate 18%
10 Starbucks 37% 24 Oracle 14%
11 GAP 36% 25 Pepsi 13%
12 Accenture 36% 26 Apple 12%
13 Avon 35% 27 JP Morgan 8%
14 DELL 31% 28 VISA 6%
2. Preliminary Analysis
Companies that increase their advertising in a recession are expected to benefit more in terms
of brand equity than companies that decrease their advertising efforts. Figure 4 shows how
the recessionary advertising decision affects the future brand value for advertising increasers
and decreasers. For the construction of this chart yearly brand value changes are calculated
for each of the companies and are then averaged for the years 2008, 2009 and 2010. The dark
grey bar illustrates the average brand value change for advertising decreasers. The bright grey
bar demonstrates the average brand value change for advertising increasers. As expected, the
increaser group experiences rising brand values in the recession year while the brands of
decreasers become less valuable. In 2009, both groups report an average decline. This can be
explained by the fact that the recession went through its trough in the first months of that year
(NBER, 2010). Interesting to see is that the increaser group is again slightly better off. In
2010, brand values grew again for both groups with the strongest boost for the increasers.
Overall, the figure provides some first insights on how brand values change for advertising
increasers and decreasers in different economic situations. It becomes clear that recessionary
22

26. advertising increasers are the ones that benefited the most during and after the recession of
2008.
Figure 4. Brand value change (in %) for adv. increasers and decreasers in 2008, 2009 & 2010
10.00%
8.00%
6.00%
4.00%
2.00%
0.00%
BE0708 BE0809 BE0910
-2.00%
-4.00%
-6.00%
Decreasers
Series1 Increasers
Series2
Another way to analyze the relationship between changes in advertising expenditures and
changes in brand value is to calculate the bivariate correlations between the two variables.
Hereby, it is assessed to which degree changes of advertising are associated with similar
changes in brand equity. Instead of dividing the data set into two distinct groups, this form of
analysis compares changes in advertising expenditures and changes in brand value for every
single company. The second column in Table 2 shows the correlation coefficient for the
relation between changes in advertising and changes in brand equity in the recession year.
The statistically significant and positive figure indicates that a higher growth (decline) in
recessionary advertising is likely to result in a higher growth (decline) in brand value. The
two additional correlation coefficients in the third and fourth column are calculated to check
whether advertising increasers also remain to be better off, in terms of brand equity, in the
time after the recession. Those coefficients are, however, not significant. It is, therefore, not
possible to say anything about the success of a recessionary advertising strategy beyond the
recession period.
Table 2. Pearson Correlations: Change in advertising versus change in brand value
BE0708 BE0709 BE0710
Adv0708 .539** .209 .103
** Significant at the 0.05 level
23

27. 3. Regression Analysis
Multiple regression analysis, compared to bivariate correlation analysis, has the advantage to
account for the effects of other variables that also might have an influence on the dependent
variable. Hence, the regression equations introduced earlier, can provide deeper insights into
the relation between recessionary advertising and brand equity than the preliminary analysis
in the previous section. Before running the two regressions, the explanatory power of the
models is checked for.
3.1. Pre-Tests
To justify the use of linear regression models and to ensure the accuracy of their results, the
analyzed data has to meet certain criteria. In particular, it is assumed that the residuals
(differences between the obtained and predicted dependent variable scores), which are
generated as part of the regression analysis, are normally distributed, linear, independent and
have a constant variance. To check weather those assumptions are true, the residual scatter
plots, histograms (see appendix, exhibit 3.1 and 3.2) and Durbin-Watson statistics are
examined. The histograms show that the error terms are relatively normally distributed. The
random pattern of the scatter plots indicates that the residuals are linear and have a constant
variance. The Durbin-Watson statistics presented in the “model-summary” table in exhibit 4.1
and 4.2 (see appendix) confirm that the independence assumption is also not violated.
To determine the utility of a regression model one needs to look at the adjusted R-square
scores in the ‘model summary’ and the F-Statistics in the ‘ANOVA’ table (see appendix,
exhibit 4.1 and 4.2). The adjusted R-square scores are 0.584 and 0.727. This means that the
independent variables are explaining a relatively high variation in the dependent variable. The
F-statistics show that both models are statistically significant at the 5 percent level. Overall
those results suggest that both models are well suited to analyze the relation between the
independent and dependent variables.
After having checked the regression assumptions and the appropriateness of the overall model
the variance inflation factors (VIF scores) are examined to make sure that multicollinearity is
not a problem. Although multicollinearity does not reduce the explanatory power or reliability
of a regression model as a whole, it may bias the coefficients of the independent variables.
Since the VIF scores, presented in the collinearity statistics column in exhibit 5.1 and 5.2 (see
appendix), are far below 10, multicollinearity is not a problem.
24

28. 3.2. Results
Model 1 is used to test the first hypothesis and the results are presented in Table 3 (see
appendix, exhibit 5.1 for the complete output). The most important figure in this table is the
unstandardized coefficient for the Adv0708 variable (0.517). Since it is positive and
statistically significant at the 5 percent significance level, it can be concluded that an increase
(decrease) of advertising in the year 2008 is associated with an increase (decrease) of brand
equity in that same year.
Table 3. Results, Model 1. Dependent variable BE0708
Unstandardized Standardized
Variable Coefficients Coefficients Sig.
B Beta
Adv0708 ,517 ,570 **
Adv0407 ,071 ,205
Note: Industry dummies are excluded from this table. For a complete overview
of the results, see appendix, exhibit 5.1.
** Significant at the 0.05 level
The unstandardized coefficient column in Table 3 shows how much the dependent variable
(BE0708) is expected to change if the independent variable (Adv0708) changes by one unit.
So, if Adv0708 increases by 1%, BE0708 rises by 0.517%. By the means of the following
example this can be put into dollar terms. As presented in exhibit 2.1 and exhibit 2.3 in the
appendix, the average firm spent around $1.04 billion on advertising in the pre-recession year
(2007) and had a brand value of $15.6 billion. It means that a 1% increase of advertising
expenditures would cost $10.40 million (1.04 x 0.01) and correspond to a brand value boost
of $80.65 (15.6 x 0.00517) million. Hence, increasing advertising by just 1% can have a
tremendous positive impact on the brand value of a firm. If one considers that a firm’s brand
often makes up a significant part of overall firm value it becomes clear how important it is to
invest in advertising. Overall, the results in this subsection strongly support the expectation
that the relation between recessionary advertising and brand equity is positive. Hence,
hypothesis I can be confirmed.
To test whether firms can more effectively advertise during a recession than during an
expansion (in terms of brand equity growth), one needs to find out whether the relation
between advertising and brand equity differs across the two periods. By the means of Model
2 this can be tested. The results are presented in Table 4. The change in advertising
25

29. expenditure variable is again significant and positive (0.287). When comparing this outcome
with the outcome of the first regression it can be seen that the unstandardized coefficient of
the Adv0405 variable is about half as big as the one from the Adv0708 variable. This implies
that an increase of advertising during a recession has an impact on brand value that is two
times stronger than the impact of an advertising increase during a non-recession period.
Table 4. Results, Model 2. Dependent variable BE0405
Unstandardized Standardized
Model Coefficients Coefficients Sig.
B Beta
Adv0405 ,287 ,800 ***
Adv0104 ,094 ,651 ***
Note: Industry dummies are excluded from this table. For a complete overview
of the results, see appendix, exhibit 5.2.
*** Significant at the 0.01 level
In order to illustrate the strength of recessionary advertising, the regression results are again
expressed in monetary terms. Earlier it is illustrated that a 1% increase of recessionary
advertising would cost an average of $10.40 million and correspond to a brand value boost of
$80.65 million. During the non-recession period (between 2004 and 2005) the average brand
value change corresponding to a 1% change in advertising is far less. As presented in exhibit
2.1 and exhibit 2.3 in the appendix, the average firm spent about $0.95 billion on advertising
in the year 2004 and had a brand value of $14.9 billion. Hence, a 1% increase of advertising
would cost $9.5 million (0.95 x 0.01) and the average brand value would consequently go up
by $42.8 million (14.9 x 0.00287). The bar chart in Figure 5 illustrates both scenarios. The
main message to be derived from that chart is that advertising is a lot more effective during a
recession than during an expansion. Overall, the regression results confirm hypothesis II.
The prior advertising variable Adv0104 in Table 4 provides some additional information. It
indicates that a 1% increase of prior advertising during an expansion leads to an increase of
0.094% in brand value. Hence, during expansion periods one can rely on prior advertising
efforts. The Adv0407 variable in Table 3 is not significant and, therefore, it is not possible
say anything about the effects of prior advertising during recessions.
26

30. Figure 5. Average Advertising and Brand Value growth (in million US$) during a recession
and expansion (when advertising increases by 1%).
$100.00
$80.00
$60.00
$40.00
$20.00
$0.00
Expansion Recession
Advertising Brand Equity
27

31. V. Discussion
The previous chapter starts off with a preliminary analysis (correlation analysis) that finds
first evidence for a positive relation between changes in advertising and changes in brand
value. The two-variable model, however, explains very little about the ability of one variable
to predict the other (Kamber, 2002), and it ignores the effects of other factors that also might
have an effect on a firm’s brand equity. Therefore, multivariate regressions (Model 1 and
Model 2) are conducted. They incorporate a prior three-year advertising growth variable and
control for industry effects at the same time. The empirical evidence confirms the expectation
that advertising has a positive impact on brand equity and that this impact is stronger during a
recession than during an expansion. Keeping in mind that the effects of advertising on
market-based assets are sustainable and accumulative (Wang et al., 2008) it becomes clear
how valuable it is, in terms of brand value growth, to increase advertising expenditures in a
recession.
The fact that advertising is more effective during recessions than during expansions seems to
be related to the company’s cost cutting behavior during recessions. When economists study
strategic situations, or ‘games’, in which the outcome of one decision is directly dependent on
the choices of others, they call it game theory. What has been done in the study at hand is an
analysis of the advertising ‘game’ that is played by US firms in a recession. It is assumed that
advertising increasers only win this game (in terms of brand value growth) because most of
the other companies decrease their advertising. In case the majority of firms would suddenly
start to spend more on advertising in future recessions, the relation between advertising and
brand equity is likely to change. Taking into account that other researchers also recommend to
increase advertising expenditures in a recession (e.g. Frankenberger and Graham, 2003), it
can be expected that firms are actually going to do so in the future. The results of this study
should, therefore, be taken with some degree of caution. Based on historical data it was found
that recessionary advertising increasers are better off (in terms of brand value) than
advertising decreasers. Whether this remains to be true in future recessions strongly depends
on the aggregate advertising behavior of companies.
1. Managerial Implications
Marketing managers are confronted with a difficult dilemma in recessionary periods. On the
one hand, they feel the pressure to reduce costs, by for example, cutting their advertising
budgets. On the other hand, they are advised to increase their advertising in order to benefit in
28

32. terms of sales & market share (Biel and King, 1990; Kijewski, 1982), earnings
(Frankenberger and Graham, 2003) and brand value. How should managers deal with this
dilemma? Of course managers cannot simply increase their advertising budget if major losses
or even bankruptcy is at risk. Hence, it is crucial to first check whether a firm has the
financial resources to spend more on advertising. If that is the case, managers should carefully
examine the advertising behavior of their competitors. The current study shows that during
economic situations in which the majority of firms decrease their advertising (i.e. during a
recession), an increase can be a very effective move. Hence, if the majority of competitors
decrease their advertising efforts in a recession, a company should not miss the opportunity to
increase their advertising spending. Brand equity, which accounts for a large part of
intangible firm value (PricewaterhouseCoopers and Sattler, 2005), is likely to increase, and
this would be highly valued by the shareholders of a company (Barth, et al., 1998; Kerin and
Sethuraman, 1998; Wang et al., 2008). Hence, it is proven that recessionary advertising has a
positive and strong impact on the value of a firm. Managers can, therefore, justify an increase
of recessionary advertising with the argument to operate in the best interest of the firm’s
shareholders.
2. Theoretical Implications
The “accountability of marketing expenditures” is one of the major research priorities of the
Marketing Science Institute (MSI) for the years 2008-2010 (Marketing Science Institute,
2010) and, therefore, it is of crucial importance to investigate the link between marketing
activities and the long-term value of a firm. During economic downturns, when cost cutting
pressure is very high, it is particularly difficult for marketers to justify their marketing
expenditures. An analysis of the relation between marketing and firm value during those
downturns can, therefore, make significant contributions to the marketing literature. So far, a
few researchers investigated the relation between recessionary advertising and sales, market
share and earnings, and found that advertising increasers are often more successful than
advertising decreasers. Furthermore, they observe that advertising efforts are more effective
during recessions than during expansions. Those studies do, however, ignore the effects of
advertising on the value of a firm. The main contribution of this study is to establish the link
between recessionary advertising and the firm’s intangible firm value.
29

33. VI. Limitations and Future Research
The major limitation of the present study is the sample size. For the investigated time period,
Compustat provides advertising expenditures for about 2800 firms, yet only 32 of those
values can be matched with brand value data from Interbrand’s 100 Best Global Brands lists.
The small sample, consisting of companies with extremely high brand values is, therefore, not
representative for the entire population of US firms. The sample size further reduces the
statistical power of the present analysis. Hence, future research should gather more brand
value estimates and repeat this study with a larger sample size.
Other shortcomings concern the data itself. The brand values reported by Interbrand are only
estimates and not perfect measures of brand equity. As stated earlier, they are calculated by
the economic use approach which is just one of many methods to derive brand value
estimates. Criticisms against this approach are “(1) the method for estimating future earnings
and cash flows over and above the future earnings and cash flows that an unbranded product
can produce, (2) the choice of a discount rate based on seemingly subjective assessments of
brand strength, and (3) the tendency to overlook asset synergies and brand or trademark
extension potential when valuing brands” (Kerin and Sethurman, 1998, p. 271). Nevertheless,
according to Kerin and Sethurman as well as to other researchers, Interbrand’s brand values
estimates are generally considered as very reliable. This justifies its use for the present
analysis.
The advertising data from Compustat also brings along some limitations. First of all, this
study only focuses on the amount of advertising spent and not on how effectively the
advertising dollars are used. Second, this study is constrained to traditional advertising efforts
(television, radio, newspaper, magazines and billboards) and, thus, ignores the increasing
expenditures into new media channels, such as the Internet. In developed countries, Internet
advertising is on a rise at the expense of traditional media (The Economist, 2008). Hence, the
reported decline of advertising expenditures in Figure 3 could partly be explained by the fact
that only traditional advertising efforts are considered. This in turn would distort the results of
this study. Therefore, future research should also account for expenditures into new media in
order to accurately reflect a firms advertising spending today. Such studies could further
examine whether online advertising is better able to resist recessions than traditional
advertising. Since the effects of online advertising are easier to measure and thus to justify, it
can be expected that online advertising is better able to resist the cost-cutting pressure during
30

34. recessions (The Economist, 2008).
Other shortcomings concern the industry dummies in the regression analysis. The problem is
that only a few firms represent one industry group. Hence, a dummy coefficient would tell
something about the brand value growth of certain companies but nothing about the effects of
an entire industry. Nevertheless, all industry dummies are kept in the regression models
because they capture additional information that cause an increase of the adjusted R square
scores. In other words, the incorporation of those dummies improves the overall model. To
accurately account for industry effects in future research, the current study should be repeated
with a larger sample that better represents the different industries.
Another limitation considers the length of the recession period. As stated earlier, the analyzed
recession period began in December 2007 and ended in June 2009. Due to data availability
constraints it is not possible to consider the entire period in the analysis. In particular, the
advertising effects during the years 2007 and 2009 are excluded. If future researchers could
repeat the present study with monthly rather than yearly advertising and brand value data,
their results could better reflect the advertising brand value relation during a recession.
31

35. VII. Conclusion
The goal of this study was to find out how marketing managers should adjust their advertising
budget during a recession. To answer this question it was important to first understand how
advertising affects a firm. A discussion of the different effectiveness measures revealed that
there is an increasing need to evaluate marketing activities based on their contribution to
market-based assets, and in particular, to brand equity. Therefore, it was decided to analyze
the relation between recessionary advertising and a firm’s brand equity. By the means of
regression analysis this relation was studied for a recession and a non-recession period. A
comparison of the results revealed that advertising has an impact on brand value that is two
times stronger during a recession than during an expansion. Overall, this suggests that value-
oriented marketing managers should see a recession as an opportunity rather than as a threat.
They should consider to maintain or even to increase their advertising budget in a recession.
32

36. Appendix
Exhibit 1. US Real Gross Domestic Product
1.1 Quarterly Growth, Real Gross Domestic Product, 2007 – 2009
Change in real GDP to
Year Quarter
previous quarter
2007q1 0.22%
2007q2 0.79%
2007q3 0.56%
2007q4 0.71%
2008q1 -0.18%
2008q2 0.15%
2008q3 -1.02%
2008q4 -1.77%
2009q1 -1.26%
2009q2 -0.18%
2009q3 0.39%
2009q4 1.22%
Data retrieved 28th August from: http://www.bea.gov/national/index.htm#gdp
1.2 Yearly Growth, Real Gross Domestic Product, 2005 – 2008
Change in real GDP to
Year
previous year
2005 3.05%
2006 2,67%
2007 1,95%
2008 -0.0008%
Data retrieved 28th August from: http://www.bea.gov/national/index.htm#gdp
33

37. Exhibit 2. Descriptive Statistics
2.1. Advertising Data
a) Absolute Advertising Expenditures
Minimum Maximum Mean Std.
Variable N
(in million $) (in million $) (in million $) Deviation
Adv04 30 37.70 3490 950.22 1005.43159
Adv05 30 65.90 5000 1066.51 1198.81271
Adv06 31 68.81 5100 1040.85 1110.45272
Adv07 31 76.90 5400 1035.31 1113.88475
Adv08 31 71.00 4600 1009.58 1033.91448
b) Changes in Advertising Expenditures
Variable N Minimum Maximum Mean Std. Deviation
Adv04/05 30 -.64 .64 .1140 .21222
Adv05/06 30 -.35 .45 .0545 .17356
Adv06/07 30 -.38 .32 .0533 .15359
Adv07/08 31 -.39 .41 -.0085 .15044
34

38. 2.2 Absolute advertising expenditures (in million US$) and changes in advertising
expenditures for the years 2005 and 2008
Change in Change in
Adv. Adv.
Adv. Adv.
Company Expenditure Expenditure
Expenditure Expenditure
08 05
(07/08) (04/05)
1 VISA 41.48% 588
2 Amazon 27.14% 16.07% 420 168
3 Starbucks 19.77% 22.12% 129 88
4 Harley Davidson 13.79% 26.62% 89 67
5 Google 11.15% 63.85% 266 104
6 Disney 10.34% -3.45% 2,900 2,900
7 Tiffany & Co 8.17% 1.87% 189 138
8 Coca Cola 7.47% 12.00% 2,998 2,500
9 Colgate 6.29% 10.94% 1,650 1,194
10 Avon 5.66% -1.47% 391 136
11 Kraft 5.19% 4.26% 1,639 1,314
12 Apple 3.91% 28.22% 486 287
13 IBM 1.35% -3.97% 1,259 1,284
14 Kellogs 1.21% 6.00% 1,076 858
15 McDonalds -2.12% 6.33% 703 771
16 Intel -2.15% 19.23% 1,860 2,600
17 Accenture -3.70% 6.02% 91 66
18 Pepsi -5.56% 5.56% 1,800 1,800
19 Hertz -6.31% 0.55% 163 165
20 Heinz -7.37% 2.53% 316 297
21 JP Morgan -8.21% 30.36% 1,913 1,917
22 Ebay -8.30% 30.91% 923 665
23 GAP -9.43% -2.92% 435 513
24 Hewlett-Packard -10.00% -63.64% 1,000 1,100
25 Microsoft -10.83% 9.15% 1,200 995
26 Kodak -12.57% -4.69% 350 490
27 Oracle -14.08% 37.26% 71 106
28 Yahoo -15.79% 20.40% 190 201
29 DELL -16.28% 25.49% 811 773
30 Ford -17.39% 36.00% 4,600 5,000
31 Motorola -39.24% 790
32 Pfizer 0.29% 3,500
th
Data retrieved 15 August from: https://wrds-web-wharton-upenn-edu.ezproxy.ub.unimaas.nl/wrds/
35

39. 2.3 Descriptive Statistics – Brand Equity Data
a) Absolute Brand Values
Minimum Maximum Mean
Variable N Std. Deviation
(in million $) (in million $) (in million $)
BE04 30 2400 67394 14887.43 17411.877
BE05 31 2576 67525 14794.93 16987.370
BE06 30 3099 67000 15364.16 16920.079
BE07 30 3026 65324 15597.26 17110.883
BE08 28 3338 66667 17127.53 17860.307
b) Changes in Brand Values
Variable N Minimum Maximum Mean Std. Deviation
BE04/05 30 -.11 .18 .0270 .06802
BE05/06 30 -.28 .32 .0249 .11967
BE06/07 29 -.23 .31 .0266 .10720
BE07/08 27 -.26 .30 .0257 .10630
36

40. 2.4 Absolute brand values (in billion US$) and changes in brand values for the years 2005 and
2008
Change in
Change in
Brand Brand Brand
Company Brand Value
Value Value 08 Value 05
(07/08)
(04/05)
1 Google 30.30% 25,590 8,461
2 Apple 19.58% 13.95% 13,724 7,985
3 Amazon 15.90% 2.17% 6,434 4,248
4 Oracle 10.00% -0.44% 13,831 10,887
5 Accenture 8.20% 6.02% 7,948 6,142
6 Ebay 6.70% 17.56% 7,991 5,701
7 Colgate 6.40% 4.96% 6,437 5,186
8 Starbucks 6.39% 6.83% 3,879 2,576
9 Hewlett-Packard 5.58% -11.19% 23,509 18,866
10 McDonalds 5.32% 3.89% 31,049 26,014
11 Tiffany & Co 4.87% -0.55% 4,208 3,618
12 Kellogs 3.80% 3.33% 9,710 8,306
13 IBM 3.29% -0.78% 59,031 53,376
14 Avon 3.06% 6.98% 5,264 5,213
15 Pepsi 2.72% 2.69% 13,249 12,399
16 Coca Cola 2.01% 0.19% 66,667 67,525
17 Heinz 1.53% -1.36% 6,646 6,932
18 DELL 1.21% 13.08% 11,695 13,231
19 Intel 0.98% 5.87% 31,261 35,588
20 Microsoft 0.51% -2.39% 59,007 59,941
21 Disney 0.14% -2.54% 29,251 26,441
22 Harley Davidson -1.43% 3.93% 7,609 7,346
23 JP Morgan -6.13% -3.46% 10,773 9,455
24 Yahoo -10.39% 13.53% 5,496 5,256
25 Motorola -11.50% 10.16% 3,721 3,877
26 Ford -13.75% -10.00% 7,896 13,159
27 GAP -25.80% 3.93% 4,357 8,195
28 Kodak -5.06% 4,979
29 Hertz 3.12% 3,521
30 Kraft 2.97% 4,238
31 Pfizer -6.55% 9,981
32 VISA 3,338
Data retrieved 26th August from: http://www.interbrand.com/en/best-global-brands/best-global-brands-
2005/best-global-brands-2005.aspx, http://www.interbrand.com/en/best-global-brands/best-global-
brands-2008/best-global-brands-2008.aspx
37

41. Exhibit 3. Residual Analysis
3.1. Histogram and scatterplot of residuals for the recession model (Model 1)
3.2. Histogram and scatterplot for the non-recession model (Model 2)
38

42. Exhibit 4. Model Utility
4.1. Model Summary & ANOVA table (Model 1)
Model Summaryb
Adjusted R Std. Error of the Durbin-
Model R R Square
Square Estimate Watson
1 ,895a ,800 ,584 ,0674552 2,929
a. Predictors: (Constant), 87, 73, 60, 56, 48, 59, 58, 37, 28, 35, 20, Adv0407, Adv0708
b. Dependent Variable: BE0708
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression ,219 13 ,017 3,696 ,015a
Residual ,055 12 ,005
Total ,273 25
a. Predictors: (Constant), 87, 73, 60, 56, 48, 59, 58, 37, 28, 35, 20, Adv0407, Adv0708
b. Dependent Variable: BE0708
4.2. Model Summary & ANOVA table (Model 2)
Model Summaryb
Adjusted R Std. Error of the Durbin-
Model R R Square
Square Estimate Watson
1 ,924a ,853 ,727 ,0363126 2,464
a. Predictors: (Constant), 87, 73, 60, 56, 48, 59, 58, 37, 28, 35, 20, Adv0104, Adv0405
b. Dependent Variable: BE0405
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression ,107 12 ,009 6,775 ,001a
Residual ,018 14 ,001
Total ,126 26
a. Predictors: (Constant), 87, 73, 60, 56, 48, 59, 58, 37, 28, 35, 20, Adv0104, Adv0405
b. Dependent Variable: BE0405
39

43. Exhibit 5. Coefficient Tables
5.1. Coefficient Table (Model 1)
Unstandardized Standardized Collinearity
Model Coefficients Coefficients t Sig. Statistics
B Std. Error Beta Tolerance VIF
(Constant) ,028 ,068 ,420 ,682
Adv0708 ,517 ,171 ,570 3,034 ,010 ,471 2,121
Adv0407 ,071 ,059 ,205 1,207 ,251 ,579 1,728
20 -,010 ,077 -,036 -,133 ,897 ,226 4,421
28 -,045 ,088 -,118 -,514 ,617 ,315 3,176
35 ,091 ,080 ,282 1,134 ,279 ,269 3,722
37 -,123 ,087 -,319 -1,401 ,187 ,322 3,106
48 -,070 ,098 -,131 -,710 ,491 ,493 2,030
56 -,230 ,096 -,431 -2,390 ,034 ,511 1,955
58 -,027 ,085 -,071 -,323 ,752 ,341 2,929
59 -,043 ,090 -,112 -,479 ,640 ,304 3,285
60 -,073 ,101 -,136 -,720 ,485 ,466 2,144
73 ,046 ,079 ,188 ,581 ,572 ,159 6,280
87 ,048 ,099 ,091 ,486 ,636 ,480 2,084
40

44. 5.2. Coefficient Table (Model 2)
Unstandardized Standardized Collinearity
Model Coefficients Coefficients t Sig. Statistics
B Std. Error Beta Tolerance VIF
(Constant) -,006 ,021 -,301 ,768
Adv0405 ,287 ,043 ,800 6,698 ,000 ,735 1,360
Adv0204 ,094 ,022 ,651 4,300 ,001 ,458 2,186
20 ,003 ,027 ,017 ,113 ,912 ,460 2,175
28 -,016 ,030 -,075 -,537 ,600 ,540 1,852
35 ,051 ,030 ,237 1,715 ,108 ,551 1,816
37 -,200 ,044 -,554 -4,548 ,000 ,708 1,412
56 ,035 ,042 ,098 ,838 ,416 ,770 1,298
58 -,016 ,034 -,061 -,467 ,648 ,609 1,642
59 -,040 ,034 -,153 -1,187 ,255 ,628 1,592
60 -,167 ,045 -,463 -3,720 ,002 ,679 1,474
73 ,021 ,027 ,118 ,754 ,463 ,431 2,320
87 ,183 ,053 ,506 3,458 ,004 ,490 2,039
41

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