What’s a Brand Worth? Trademark Protection, Profits and

Product Quality

Davidson Heath and Christopher Mace∗

February 10, 2017

Abstract

We study the effects of trademark protection on firm profits and strategy through a new dataset of all

U.S. trademarks registered since 1870. We exploit the Federal Trademark Dilution Act (FTDA) and its

subsequent cancellation, and find that trademark protection is of first-order importance for firm profits

and strategy. We estimate that from 1996 to 2002 the FTDA raised treated firms’ profits by 1.8% on

average and channeled $729 billion in additional profits to incumbents. Firms responded to the shock by

lowering product quality and innovation and extending protected brands into new product markets.

∗Eccles School of Business, University of Utah. Email: davidson.heath@eccles.utah.edu. We thank Kenneth Ahern, JeffColes, Mike Cooper, Joey Engelberg, Sam Hartzmark, Gerard Hoberg, Karl Lins, Amanda Myers, Yihui Pan, Chris Parsons,Matt Ringgenberg, Nathan Seegert, Giorgo Sertsios, Andrew Toole, Feng Zhang and seminar participants at the Paris FinanceConference, Utah, and the USPTO for comments.

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1 Introduction

Differentiation in product markets is a key determinant of firm value and industry structure.1 Firms devote

vast resources to managing their product market position. Legally, firms define and protect their product

market position with trademarks – unique intangible assets that confer the exclusive right to market a

branded product. For economists, a firm’s product market position is a key element that determines profits,

value and strategy. For policymakers, evaluating intellectual property law, antitrust policy and product

market regulation requires an understanding of the role served by trademarks.

Surprisingly given the age and economic importance of the trademark system, there is little or no evidence

on the importance of trademark protection for firm profits and strategy. This gap in our knowledge is due

to, first, a lack of comprehensive data and, second, the endogeneity of trademark holdings with other firm

and industry characteristics. To address the lack of data we construct a new dataset that covers all 4.2

million trademarks granted by the U.S. Patent and Trademark Office (USPTO) since its inception in 1870.

The comprehensive historical sample is necessary because unlike patents and copyrights, which expire after

a finite lifespan, trademarks can be renewed perpetually.2

To address causal inference we exploit a change in trademark law, the 1996 Federal Trademark Dilution

Act (FTDA), which strengthened the protection of a subset of existing trademarks, and its subsequent nul-

lification in 2003. Using a difference-in-differences approach we estimate that stronger trademark protection

raised treated firms’ operating profits by 1.8% and their market value of equity by 15% on average. We

estimate that from 1996 to 2002 the FTDA channeled an additional $729 billion dollars of additional profits

to treated firms, more than the total operating profits of the entire telecom sector over the same period.

Were these higher profits accompanied by welfare increasing effects such as higher product quality or

innovation? The relationship between trademark protection and firm strategy is ambiguous both theoretically

and empirically. On one hand, trademarks “...foster competition and the maintenance of quality by securing

to the producer the benefits of good reputation.”3 According to this view trademark protection incentivizes

firms to produce and develop high quality products and prevents a race to the bottom, by allowing firms to

distinguish their products from inferior imitations (Klein and Leffler, 1981; Landes and Posner, 1987). On1See Chamberlin (1933); Robinson (1934); Dixit and Stiglitz (1977); Shaked and Sutton (1987); Scherer and Ross (1990)2 For example, Coca-Cola’s trademark for soft drinks has been continuously registered since 1893 and by one estimate

accounts for 42% of the firm’s total value.3Registration of Trademarks: Congress of The United States Joint Committee on Patents, January 20, 1925

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the other hand, Chamberlin (1933) argues that trademarks do not encourage quality or innovation but only

foster monopoly and channel rents to incumbents. Indeed Chamberlin (1933) goes so far as to state that

“...[I]mitation of competitors’ goods ought to be permitted and even encouraged.”

Our paper presents the first causal evidence on this topic. After the FTDA became effective, treated

firms sharply reduced R&D spending, patenting activity and new product announcements. At the same

time, they had higher frequency and dollar values of recalls of unsafe products, and were slightly less likely

to recall faulty products voluntarily. The FTDA also altered firms’ product mix. Treated firms introduced

brand extending goods and services in all-new product classes, relative to both the firm’s current and

lifetime product mix. These new products were more likely to be opposed by competitors upon trademark

registration, and conditional on passing opposition, were more likely to still be sold 10 years later. Taken

together these results suggest that stronger trademark protection leads firms to extend their protected brands

into new product markets at the expense of product quality and innovation in their core offerings.

At the industry level we find that industries more affected by the FTDA disproportionately reduced

the number of active firms, employment and payrolls looking across both public and private firms. Our

results appear consistent across the board with the contention of Chamberlin (1933) that trademarks foster

monopoly by funneling rents to incumbent firms.

Our empirical specification relies on the FTDA’s enhancement of trademark protection for a subset of

trademarks deemed “famous.” The causal interpretation of our findings rests on the assumption of parallel

trends – that absent the FTDA, changes in the profits and behavior of firms that held famous trademarks

would have been similar to those of control firms. The main threat to validity is that unobserved changes

in market conditions or investment opportunities that were specific to famous trademark holders coincided

with the FTDA. We perform a battery of tests which provide additional depth and lend confidence to our

interpretation.

First, the timing of the estimated effect is sharply limited to the treatment window. Inspection of the

year-by-year differences between treated and control firms shows similar trends pre-treatment and a positive

break in treated-firm profits in the year the FTDA became effective. Importantly, the treatment effect is

reversed after a 2003 Supreme Court decision that nullified the key provision of the FTDA, and our results

are similar when we include both events in a switching research design. We conduct placebo tests which

suggest that reverse causality or unobserved shocks are unlikely to be a factor; a similar trademark protection

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provision was narrowly withdrawn from a prior bill which passed in 1988, and treated firms’ profits around

this placebo event show no effect. Second, we show that our estimates are stable across a range of alternative

specifications, including industry-by-year fixed effects which sweep out arbitrary industry-level trends, booms

and busts. Our results are also unaffected by controlling for firms’ total trademark holdings and their age,

size, and growth opportunities.

Third, our results are robust to varying both the treatment and control groups. Our main specification

requires that a trademark has been in active use for at least 21 years to qualify as plausibly famous. As

this definition can result in a mismatch on firm age, we explore an alternate specification based on popular

usage of trademark text and our estimates are very similar. The treatment effect is also similar when we

limit the control group to non-trademark holders or to holders of non-famous trademarks. Fourth, we find

that the estimated value of trademark protection varies with industry characteristics in directions that are

consistent with our proposed causal interpretation. The value of stronger trademark protection is localized

to industries that ex ante held more trademarks and spent more on advertising and selling expenses.

Our results reveal the effects of treatment – Federal protection from trademark dilution – on the treated

group, which is incumbents who own established brands. As such, we do not observe the effects of enhanced

protection on all trademark holders or, for example, a policy targeted at new entrants. However as our

treated firms are large established incumbents who are most likely to hold and aggressively protect their

trademarks, and since they account for a large proportion of total sales, we plausibly measure the lion’s

share of the economy-wide response to a change in trademark enforcement.

This paper makes several contributions. First, for the first time, we both demonstrate and measure a

causal link between trademark protection and firm profits and strategy. Second, we greatly expand the

available data on this topic by compiling a comprehensive dataset on U.S. trademarks and linking it to

Compustat firm data. Third, we provide new evidence that is broadly consistent with the contention of

Chamberlin (1933) that trademark protection fosters monopoly, funnels rents to incumbents, and actually

lowers innovation and product quality. We further find that incumbents receiving enhanced trademark

protection do not simply enjoy the quiet life (Bertrand and Mullainathan, 2003) but extend their protected

brands into all-new product markets.

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1.1 Related Literature

The marketing literature finds that consumers have significant brand awareness and brand loyalty which

translate into customer capture and retention (Aaker, 1996; Oliver, 1999; Ailawadi, Lehmann and Neslin,

2003). Brand premiums are highly material to prices and profit margins: for example, Bronnenberg et al.

(2015) estimate a 29% average premium of brand-name goods over identical generics ($44 billion out of

$196 billion total revenues) across a broad sample of consumer packaged goods. Bronnenberg, Dube and

Gentzkow (2012) find that past experience with a brand explains up to 40 percent of consumers’ purchasing

decisions.

Previous research has found effects on firms’ product market strategy and product quality from leveraged

buyouts, mergers, and increased competition; Matsa (2010) and Matsa (2011) find that increased leverage

raises product quality while increased competition lowers product quality, as measured by supermarket stock-

outs. Sheen (2014) finds when competitors merge, their product market offerings tend to converge. Ailawadi,

Lehmann and Neslin (2003) explores band management though brand premiums – the difference in price

between a branded and generic good. Keller (1993) develops a consumer based brand equity measurement

that relates brand loyalty and awareness to differential marketing responses. Hoberg and Phillips (2016)

analyze endogenous product market differentiation through textual analysis of firms’ 10-Ks and find that

firm R&D and advertising are associated with subsequent differentiation from competitors. Sutton (1991)

and Shaked and Sutton (1987) suggest that barriers to entry are endogenous and depend on product dif-

ferentiation; in particular, advertising and R&D allow firms to differentiate their products, raise barriers to

entry and capture endogenous rents.

Krasnikov, Mishra and Orozco (2009) find that greater consumer brand awareness is correlated with

higher ROA, lower cash flow volatility, and lower risk of bankruptcy. Others find that a firm’s stock of

trademarks is positively correlated with cash flow, Tobin’s Q, return on assets, and stock returns while neg-

atively correlated with cash flow volatility(Sandner and Block, 2011; Krasnikov, Mishra and Orozco, 2009).

Trademark holdings are positively correlated with firm value (Kerin and Sethuraman, 1998; Madden, Fehle

and Fournier, 2006; Belo, Lin and Vitorino, 2014; Sandner and Block, 2011) and new trademark registration

is positively correlated with productivity, employment, wages, and growth rates (Greenhalgh et al., 2011).

Trademark filings, when used as a proxy for new advertising, can have a spillover effect on the market value

of rivals (Fosfuri and Giarratana, 2009), and several studies have shown a correlation between trademark

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activity and various measures of innovation (Mendonca, Pereira and Godinho, 2004; Faurel et al., 2016).

Block et al. (2014) find that venture capital valuations tend to be higher for firms with trademarks.

The rest of the paper is organized as follows. Section 2 presents background on U.S. trademarks and

trademark law. Section 3 describes our data and presents summary statistics and associations. Section

4 presents our main estimates of the effects of trademark protection on firm profits and value, as well as

robustness and specification checks. Section 5 investigates across-industry heterogeneity in the value of

trademark protection and the effects on firms’ operating strategy, innovation and product market strategy.

Section 6 concludes.

2 Background on U.S. Trademarks

2.1 Trademark Registration and Renewal

The USPTO defines a trademark as a “word, phrase, symbol, design, color, smell, sound, or combination

thereof that identifies and distinguishes the goods and services of one party from those of others.”4 Examples

of trademarks include the word “Pepsi,” the McDonald’s “Golden Arches” symbol, and NBC’s musical

notes G, E, C played on chimes. A trademark’s distinctiveness can change over time; the once-strong

trademarks Dry Ice, Escalator and Aspirin eventually became ’genericized’ and ineligible for renewal (Cohen,

1986; Graham et al., 2013).

The symbol TM signifies an unregistered trademark which is protected from infringement by state-level

common law within the geographic area in which the mark is used. The main statute of modern trademark

law, the Lanham Act of 1946, defines infringement as “use of an identical or similar mark that would cause

confusion as to the source of goods or services.” The symbol R© signifies that a trademark is officially

registered with the USPTO. Registration extends protection against infringement to the national level,

provides prima facie evidence of ownership, the power to file actions in Federal court to obtain injunctions

and/or recover damages, and the mark is listed with the US Customs and Border Protection Service which

interdicts the import of counterfeit goods.5

The registrant specifies one or more goods-and-services classes, which define the scope of trademark4Trademark Basics5USPTO Rights of Trademark Registration

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protection.6 Registration costs a small fee (as of 2016, $325 per class) and requires that the applicant

demonstrate “use in commerce,” that is, provide a specimen and documentation that the mark is currently

used to identify a good or service that they sell. Applications can be filed on an “intent-to-use” basis, but the

registrant must demonstrate use in commerce before the registration can be completed. Each class in which

a trademark is registered is subject to the use-in-commerce requirement at registration and renewal. The

use-in-commerce requirement is important for our purposes, because it means that registered trademarks

reflect products and services that firms were verified to produce and sell (Graham et al., 2013).

Unlike patents and copyrights which expire after a limited time, trademarks may be renewed indefinitely.

Prior to 1989 trademarks were renewed every 20 years; subsequently they are renewed every 10 years. For

the 1990 cohort of new trademark registrations, 64% were renewed in 2000 and 53% of those were renewed

a second time in 2010 (Graham et al., 2013). Proof of use in commerce is required again six years after

registration and upon renewal.7

2.2 Trademark Dilution

In the decades after the Lanham Act of 1946, the concept of trademark dilution began to play an increasing

role in the trademark legal system (Derenberg, 1956). Dilution is a much broader concept than infringement,

and posits that a trademark has broader importance than simply allowing the buyer to identify the seller.8

Dilution is legally defined as any action “weakening...a famous mark’s ability to identify and distinguish

goods or services regardless of competition in the marketplace.”9 (emphasis added)

Prior to 1996 protection or remedy from trademark dilution was adjudicated at the state level in cases

of proven dilution (Oswald, 1999). For example, in Dallas Cowboys Cheerleaders, Inc. v. Pussycat Cinema,

Ltd. (1979) the Dallas Cowboys Cheerleaders won an injunction in New York State against the producers of

the adult film Debbie Does Dallas on the basis of trademark dilution. However, the injunction did not stop

the film from going on to become one of the most successful adult films ever made (Williams, 1999). This

patchwork of state-level statutes and precedents prompted calls for federal antidilution legislation (Duffy,

1997; Welkowitz, 2012).6The current U.S. trademark classification system contains 52 goods codes and 8 services codes.7Registration Renewal, Maintenance, and Correction8“The value is in the ’aura’ of the mark...and the feelings it evokes from consumers about anything associated with that

brand name.”(Welkowitz, 2012)9INTA- Trademark Dilution

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The first attempt was in the Trademark Law Revision Act (TLRA) which was enacted in 1988. The

antidilution provisions of the TLRA in draft form were almost identical to those of the later FTDA, but

freedom of speech concerns led to the removal of the antidilution section from the TLRA shortly before its

passage (Denicola, 1997). We make use of the 1988 passage of the TLRA as a placebo test.

The Federal Trademark Dilution Act (FTDA), which was signed into law on January 16, 1996, for the

first time granted federal protection to U.S. trademarks against dilution. The FTDA was a major expansion

of trademark rights for two reasons. First, infringement i.e. direct competition between the plaintiff’s and

defendant’s goods or services was no longer necessary to win an injunction or damages.10 Second, the FTDA

explicitly granted protection against not just actual but likely dilution. As a result, a trademark holder was

no longer required to prove actual harm but only to convince a judge of the likelihood of harm in order to

obtain an injunction (Kim, 2001; Bickley, 2011). As an example of the law’s sweeping effects, in Nabisco, Inc.

v. PF Brands, Ltd. (1999) Pepperidge Farms, the producer of Goldfish crackers, obtained an injunction to

stop Nabisco’s intended selling of crackers based on cartoon characters some of which would be fish-shaped.11

In the case filings Nabisco estimated they had already spent $3.4 million on the project for licensing and

development.12

A key limitation was that the FTDA specified that only “famous” trademarks qualified for federal pro-

tection against likely dilution. However, the FTDA did not explicitly define the term “famous”. What

constituted a “famous” mark was subsequently interpreted on a case-by-case basis and was the subject of

much debate (Duffy, 1997; Becker, 2000; Dollinger, 2001).

Figure 1 plots the number of court cases by year in the LexisNexis database that included a claim of

trademark dilution. We split cases by whether they contained state dilution claims alone or a federal dilution

claim.13 Starting in 1996, we see a significant jump in trademark dilution cases that is entirely due to new

federal dilution claims. This observation is consistent with the view in the legal literature that the FTDA

provided famous trademark holders with significant new protections (Zando-Dennis, 2004; Jacobs, 2004).

There were two major legal developments post-FTDA. In 2003 the U.S. Supreme Court ruled in Moseley10“Once a mark is protected from dilution, it has reached the zenith of its power to exclude others, regardless of whether the

goods in connection with which the marks are used are in competition. That is, once the mark becomes famous and eligible fordilution protection, competition no longer is relevant." (Port, 2007)

11Nabisco, Inc. v. PF Brands, Inc.12The Internet Appendix describes a number of additional court cases post-1995 which illustrate the expansive protection

the FTDA granted to trademark holders.13As state-level dilution claims are much more limited in scope and importance, we consider a case with both federal and

state dilution claims to be a federal dilution case.

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v. V. Secret Catalogue, Inc. (2003) that a successful dilution claim required proof of actual economic

damages, effectively nullifying the FTDA’s key provision. The Moseley ruling was seen as a rebuke to the

FTDA’s overly broad legal standard for dilution (Pulliam, 2003). Consistent with this view, in Figure 1 the

number of federal dilution claims fell sharply in 2003.

The Trademark Dilution Revision Act (TDRA) of 2006, explicitly drafted by legislators as a response

to Moseley, restored the ability of famous trademark holders to sue on the basis of likely dilution without

proving damages. However the TDRA added provisions that substantially altered and reduced the scope

of protection relative to the FTDA (Cendali and Schriefer, 2006), and was perceived as failing to restore

the pre-Moseley status quo (Barber, 2005; Beebe, 2007). Since the legal protection provided to famous

trademarks by the TDRA is less broad and less distinctive than the FTDA, we end our sample in 2005.

3 Data and Methods

3.1 Trademark Data

Trademark data comes directly from the USPTO files which are cross hosted by Google.14 As with patents,

the USPTO does not maintain unique identifiers of trademark grantees but only records the name specified

on the registration. This creates a difficulty because there are often different abbreviations and punctuations

that refer to the same firm (e.g. “COCA COLA”; “COCA-COLA”; “COCA-COLA INC”; “THE COCA-

COLA COMPANY”; etc). Also, many firms have subsidiaries that hold trademarks (e.g. trademarks

belonging to Toys R Us are held in subsidiary Geoffrey Inc.)

We map trademarks in the year they were granted to Compustat firm-years using a variety of methods to

ensure a comprehensive match. First, we collect all names of trademark grantees and run a fuzzy match to

firm names from CRSP and Compustat and to parent and subsidiary firm names from CapitalIQ. We make

use of the name-to-gvkey associations from the NBER patent database because many trademark assignees

are also patent assignees (Hall, Jaffe and Trajtenberg, 2001).15 We double-check and supplement these four

automated matches with manual verification and disambiguation. Finally, we manually match by firm and

year. In total we map 521,997 trademarks registered between 1888 and 2012 to 14,703 Compustat firms.16

14https://www.google.com/googlebooks/uspto-trademarks.html15https://sites.google.com/site/patentdataproject/Home16The oldest trademark we map to a firm is Octagon Soap, which was registered to Colgate on January 10, 1888 and expired

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The USPTO data indicate whether each trademark is active or expired and the dates when it was renewed

or canceled. This information is important for two reasons. First, when a trademark is renewed the holder

must again provide proof of current use in commerce. Second, we use renewals to compute the number of

live trademarks that a firm holds in each year. It would not be appropriate to compute rolling depreciated

stock as is commonly done in the patents literature, because unlike patents trademarks can be renewed

indefinitely. Additional details on the trademark data can be found in the Internet Appendix.

Altogether 4,201,200 trademarks were registered at the USPTO between 1870 and 2012. Figure 2 plots

the number of new trademark registrations by year. As Faurel et al. (2016) observe in a sample of large

firms, the use of trademarks is less concentrated in particular industries than the use of patents. We find

that 213 out of 276 SIC3 industries (77%) had registered 100 or more trademarks as of 2012, compared to

127 industries (46%) that had registered 100 or more patents.17

3.2 Firm Data

Firm accounting data comes from the Compustat North America annual files from 1982-2005. We retain

all observations for U.S. firms with nonmissing and nonnegative total revenue and market value of equity

and book assets of at least $1 million. These screens yield a sample of 151,614 firm-years for 18,156 firms.

Accounting and other variables are defined in the Internet Appendix. All accounting variables are winsorized

at the 1% and 99% levels.

We determine a firm’s stock of trademarks directly using registration, renewal and expiry dates for each

trademark. Our sample firms hold 317,139 active trademarks 176,781 of which were registered for the first

time during 1982-2005.

Table 1 presents summary statistics of the sample, divided between firms that do and do not hold at

least one trademark in the sample. 50.3% of sample firms are trademark holders. On average, trademark

holders are significantly larger and more profitable; have similar average Tobin’s Q, market-to-book ratio,

investment, leverage, cash holdings and R&D spending; and spend more on advertising, compared to firms

that never hold a trademark.in 1998.

17Trademarks are even more widespread relative to patents than this comparison suggests, as more than 8 million patentshad been granted by 2012 compared to 4.2 million trademarks.

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4 The Effects of the Federal Trademark Dilution Act

4.1 Identification Strategy

The literature on branding and trademarks has documented positive cross-sectional correlations between

trademark holdings and firm value and profitability.18 Isolating the causal impact of trademark policy is

more challenging because industry structure, product differentiation, and firm profits and value are jointly

determined (Shaked and Sutton, 1987; Sutton, 1991). More profitable firms might take out more trademarks

to protect their brand value (reverse causation) and higher-quality firms might be more likely to file or renew

trademarks and also be more profitable (omitted variables).

To study the causal impact of trademark protection on firm profits and behavior, we exploit variation

in the legal protection of a subset of trademarks over time. Two features of the 1996 Federal Trademark

Dilution Act (FTDA) are important for our purposes. First, until the passage of the FTDA, federal law

protected against direct infringement and not the much broader concept of likely dilution. Thus the FTDA

represented a significant strengthening of trademark protection relative to previous years. Second, the FTDA

explicitly limited protection against likely dilution to “famous” trademarks, although it did not define the

term (Faurel et al., 1997; Becker, 2000; Dollinger, 2001; Bickley, 2011).

In our main specification we classify a trademark as plausibly affected by the FTDA if it was registered

in 1974 or earlier and was still active on January 16, 1996. Thus, as of the FTDA’s effective date, a plausibly

famous trademark had been renewed at least once and had been active in commerce for at least the previous

21 years.19 Renewals of trademarks after 1995 provide a check of whether our construct is plausibly valid.

Using our criterion, 55.7% of famous trademarks were renewed ten years later compared to 44.6% of non-

famous trademarks (p < 0.001), consistent with famous trademarks being more established and valuable.

The accuracy of our estimates depends on how accurately we classify trademarks that were covered by

the FTDA. Because the FTDA itself did not specify objective criteria for famousness, any definition will

likely produce both false negatives and false positives. Note that both types of error represent errors-in-18See e.g. Krasnikov, Mishra and Orozco (2009); Sandner and Block (2011); Block et al. (2014); Crass, Czarnitzki and Toole

(2016)19We define the registration cutoff at the end of 1974 to allow one year for notifications and processing of renewals and

expiries. The one year lag pre-treatment also makes it less likely that treatment status is endogenous i.e. that firms at themargin renewed trademarks in anticipation of the FTDA. To check if endogenous renewals are a threat to validity, in unreportedchecks we move the registration cutoff to 1973 and 1972 and require that the trademark was renewed by the end of 1994 and1993 respectively; all our results are identical.

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variables in our research design and thus attenuate our estimates downward, toward finding no difference

between treated and control firms. In robustness checks (Section 4.3.1) we explore an alternative textual

classification and our results are similar.

As it is common to take out multiple trademarks covering the same brand across different subproducts

and goods and service classes (i.e. Ford Taurus, Ford F-150, Ford F-250, Ford hats, Ford keychains, Ford

financing programs), the number of famous trademarks that a firm holds need not correspond with the size

of the market or importance of the brand. Therefore, we classify firms as treated or control based on whether

they held zero (control group) or one or more (treated group) plausibly famous trademarks as of 1995 – the

last pretreatment year in the sample. We classify 806 firms across 191 SIC3 industries as treated and 6,710

firms as controls.

For our main difference-in-differences analysis we keep observations in the seven years before (1989-1995)

and after (1996-2002) the FTDA’s effective date in 1996. We require that firms are present in 1995 and at

least one year in the post-treatment period. We use a seven year window before and after the FTDA for

two reasons: first, the pretreatment window produces a more balanced panel and makes us more confident

that pre- and post-treatment observations are comparable within firms. Second, the post-treatment window

covers the period after the FTDA’s passage in 1996 and before the 2003 Moseley ruling that nullified the

FTDA’s key provision.

4.2 Main Estimates

Table 2 presents difference-in-differences estimates of the effect of the Federal Trademark Dilution Act on

treated firms’ profits and value. The specification is

ROAit = β ∗ PostFTDAt × FamousTM1995i + γXit + φi + τt + λjt + εit

where firms are indexed by i, industries are indexed by j and φi, τt, λjt are firm, year, and industry-by-

year fixed effects. FamousTM1995i is a dummy variable that equals 1 if the firm held one or more famous

trademarks in 1995. PostFTDAt is a dummy variable that equals 0 if the year is in 1989-1995 and 1 if the

year is in 1996-2002.

Xit is a set of contemporaneous firm-year covariates: logAssetsit, ageit, Qit, Capex/Assetsit, logTrademarkStockit.

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Including them estimates the treatment effect on ROA controlling for yearly changes in the covariates – in-

cluding treatment effects on the covariates. Xit includes the log of the firm’s trademark holdings, which

controls directly for the size of each firm’s trademark portfolio by year, and Tobin’s Q which proxies for

changing growth opportunities at the firm-year level. Our estimates through the rest of the paper do not

include covariates because including them may produce a biased estimate of the true treatment effects.

However, we verify that all our estimates are similar if we include contemporaneous or lagged covariates.

Table 2 Column 1 uses firm and year fixed effects and finds a 1.8% (t = 5.3) post-FTDA increase in

profitability for treated firms relative to control firms. Column 2 adds firm-year covariates Xit and the main

estimate is very similar. Column 3 uses SIC3 industry-by-year fixed effects which absorb the yearly average

profits in each industry, sweeping out arbitrary trends, booms or busts so that the identifying variation is

purely cross-sectional within each industry-year. This specification also drops any industry-years without at

least one treated firm. The estimated treatment effect is virtually unchanged at 1.8% (t = 4.4), and again

adding firm-year covariates does not change the estimate.

4.2.1 Moseley v Victoria’s Secret

On March 4, 2003 the U.S. Supreme Court ruled in Moseley v Victoria’s Secret that a federal claim of

trademark dilution required proof of actual economic damages, considered a de facto nullification of the

broad protection granted by the FTDA. Columns 5 and 6 present difference-in-differences estimates that use

the Moseley ruling:

ROAit = β ∗ Post2002t × FamousTM2002i + φi + τt + λjt + εit

Here, the pretreatment period of 1996-2002 is when the FTDA was in effect and the post-treatment period of

2003-2005 is after its key provision was nullified. If our hypothesis is correct then we expect treatment effects

that are opposite in sign and similar in magnitude to those of the FTDA. Indeed, columns 5 and 6 show

that the Moseley ruling was accompanied by a change in profits among treated firms relative to controls of

−1.1% (t = 2.4) or −1.3% (t = 2.5), both opposite in sign and similar in magnitude to our estimates using

the FTDA’s introduction.

In Table 2 columns 7 and 8 we pool the samples and estimate a switching research design. Specifically,

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we estimate

ROAit = β1 ∗ PostFTDAt × FamousTM1995i + β2 ∗ Post2002t × FamousTM2002i + φi + τt + λjt + εit

across all firm-years from 1989-2005 so that the effects of the FTDA in 1996 and the Moseley decision in

2003 are estimated simultaneously and jointly over the full sample period. We see that the estimated effects

of strengthening trademark protection in 1996 and removing it in 2003 are again consistent with our main

estimates and our hypothesis of the FTDA’s effects.

4.2.2 Graphical Evidence

Figure 3 plots the average ROA for the treated and control groups in each year after firm and industry-

by-year fixed effects. The trends for the two groups in the pretreatment period are similar and there is no

significant difference between the groups in any pretreatment year. Consistent with our hypothesis, there is

a clear break when the FTDA took effect in 1996; ROA rose in treated firms while remaining unchanged in

control firms. The difference between treated and control firms is positive and significant at the 10% level

in every year during which the FTDA’s antidilution provision was in effect.

Also consistent with our hypothesis the difference in ROA disappears and is not statistically significant

in 2003 and 2004 after the Moseley decision. The difference between treated and control groups does become

positive and marginally significant in 2005. We note that the Trademark Dilution Revision Act of 2006,

which restored some of the FTDA’s provisions, first passed the House in April 2005 so it is possible that its

effects were anticipated.

4.2.3 Economic Magnitude

The average ROA across treated firms in 1995 was 14.2%, so an increase of 1.8% is very material, corre-

sponding to a rise of 13% in the average treated firm’s operating profits from 1996 to 2002. Moreover, most

treated firms were large incumbents. To put a dollar value to the FTDA’s effects we sum the book assets of

treated firms across the treatment period, adjusting all values to year-2000 dollars. The total book assets

for all treated firms from 1996-2002 was $40.5 trillion. If their profits were higher by 1.8% of book assets,

on average, due to the FTDA then the FTDA resulted in $40.5T × 0.018 = $729 billion of additional profits

14

to treated firms. To put this figure in perspective, it is more than the total operating profits of the entire

telecom sector over the same period (SIC3 481, $665 billion in year-2000 dollars from 1996 to 2002).

The magnitude is robust to the choice of specification and treatment group. Using the textual definition

of famousness in Section 4.3.1 yields a larger estimate of $949 billion. If we use the sample splits of Section

4.4 and limit the treated group to firms in high ad-spending, high SG&A, or high trademark-stock industries

we obtain estimates of $501 billion, $479 billion and $607 billion respectively.

4.3 Robustness

In this section we examine the robustness of our main results to alternative specifications and constructions

of the treatment and control group.

Table 3 Column 1 directly controls for differences between treated and control firms in their pre-treatment

trends. The variable pretrendi is the average yearly change in ROA for firm i from 1989 to 1995. Thus this

specification individually controls for each firm’s pretreatment ROA growth. The pretrend term is strongly

significant – firms that had growing profits pretreatment tended to continue. However, the estimated effect

of the FTDA after adding this control is similar to our main estimates at 1.3%.

Our main specification codes a firm as treated if it held at least one famous trademark in 1995. Column

2 examines the importance of the “intensive margin”: the treatment variable nFamousTM95i is the number

of famous trademarks held by firm i in 1995. The coefficient is positive and strongly significant; firms gained

on average 0.016% of ROA after the passage of the FTDA for each famous trademark they held ex ante.

Columns 3 and 4 examine the effects on our estimates of varying the control group. Column 3 drops firms

that did not hold a trademark as of 1995 from the sample, so that the control group consists of firms that

were trademark holders but had no famous trademarks as of 1995. Conversely, Column 4 drops trademark

holders from the control group, so the comparison is between holders of famous trademarks and firms in the

same industry-year that did not hold any trademarks at all. This specification eliminates “false negatives”

from the control group at the cost of comparability to treated firms. In both cases the estimated treatment

effect is similar to the main estimates (2.0%, 1.6%).

Column 5 investigates the role of attrition – whether firm entry or exit drive our findings. Here we require

all firms in both control and treated groups to have full pre- and post periods so that the panel is balanced.

The estimate is similar to the main estimates at 1.5%, indicating that firm entry and exit do not explain our

15

findings.

We next conduct a placebo test. In November 1988 the Trademark Law Revision Act (TLRA) was

enacted which changed several aspects of the trademark registration and renewal process. In its draft form,

the TLRA contained an antidilution provision which was almost identical to that of the later FTDA, but

freedom of speech concerns led to the removal of that provision from the TLRA shortly before its passage

(Denicola, 1997). We reestimate our main specifications using 1982-1988 as the pretreatment period, 1989-

1995 as the posttreatment period, and firms that held famous trademarks as of November 1988 as the

treatment group. Columns 6 and 7 show that the estimated effect of the TLRA on treated-firm profits is

statistically insignificant and slightly negative at −0.5% with firm- and year-fixed effects, −0.4% with firm-

and industry-year fixed effects. The negative placebo test suggests that alternatives such as reverse causality

(e.g., anticipated increases in incumbent firms’ profits causing passage of trademark-protection laws) are

unlikely to explain our main results.

4.3.1 Alternative Textual Classification of Trademarks

Our main estimates require that a trademark was registered by 1974 and was still active on January 16,

1996 to qualify as plausibly famous. Thus as of the FTDA’s effective date, a plausibly famous trademark

was renewed at least once and had been active in commerce continuously for at least the previous 21 years.

While this criterion has the benefit of simplicity it has at least two limitations: first, it results in treated

firms being older on average than control firms. This difference does not appear to drive our results, which

we find are robust to controlling for firm age – and, in the Internet Appendix, to matching on age as well.

Second, it wrongly classifies trademarks and firms that were registered later than 1974 but became famous

by 1996. Examples include Microsoft (first registered in 1975), Apple Computer (1976) and Costco (1983), all

of which are wrongly classified as control firms in our main specification, but clearly held famous trademarks

as of 1995 that were plausibly affected by the FTDA.

To examine the effects of these shortcomings on our identification strategy, we use an alternative measure

of famousness that relies on popular usage. We use the Google Books API and classify a trademark as famous

if 1) it is not a common dictionary word or phrase and 2) it was mentioned in fiction or non-fiction books

published in 5 of the 10 years prior to treatment (1986-1995) to qualify as famous. This textual criterion

avoids the requirement for treated trademarks and firms to be of a minimum age. In particular, all three

16

example firms that are incorrectly classified as controls using the renewal criterion (Microsoft, Apple and

Costco) are correctly classified as treated using the textual criterion. However, some trademarks such as

“Apple” and “Ford” and design marks with no text (i.e. the Apple logo) are wrongly classified as non-famous

and the set of control firms contains a number of false negatives that held famous trademarks in 1995 but

had generic names, such as Intel, Cooper and Dole.

Under the textual criterion 855 firms in 191 SIC3 industries are classified as treated and 6,661 as controls.

The overlap with the treatment group in our main specification is modest at 48% (444 treated firms in

common). Table 4 presents estimates of the FTDA’s effects on firm profits using the textual criterion.

Columns 1 and 2 show a positive effect on treated firms’ ROA of 1.0% and 1.4% using firm and year and

firm and industry-year fixed effects respectively. Columns 3 and 4 show a similar drop in ROA of −2.4%

and −1.3% with the Moseley nullification. Columns 5 and 6 utilize a switching research design and again

find similar results. Thus, the estimates using the alternative textual measure are consistent with our main

estimates albeit noisier.

We present additional robustness checks in the Internet Appendix. In particular, we find our estimates

are robust to 1) enforcing common support and covariate balance using coarsened exact matching (Iacus,

King and Porro, 2012) and 2) a nonparametric comparison of pre-post changes by firm as recommended by

Bertrand, Duflo and Mullainathan (2004).

4.4 The Value of Trademark Protection by Industry

We hypothesize that the value of trademark protection should vary with industry characteristics. Specifically,

enhanced trademark protection should be more valuable in industries with more specialized products (Titman

and Wessels, 1988), industries that are more focused on sales and marketing and industries that rely more

on trademark protection. Table 5 Panel A presents sample splits on industry-level characteristics as of

1995. Columns 1 and 2 split the sample on industry ad spending over sales as of 1995. Treated firms in

ad-intensive industries had a relative increase in ROA of 2.7% post-FTDA while those in non-ad-intensive

industries increased ROA by 0.4%. Columns 3 and 4 split the sample on industry selling, general and

administrative (SG&A) expense over sales as of 1995. Treated firms in SG&A-intensive industries increased

ROA by 2.9%, while those in other industries increased ROA by 0.6%. Columns 5 and 6 split the sample

on the industry stock of trademarks as of 1995. Treated firms in trademark-intensive industries increased

17

ROA by 2.2%, while those in non-trademark-intensive industries increased ROA by 0.7% on average. These

findings are all consistent with our hypothesis; the effects of the FTDA were localized in industries that were

ad-intensive, selling-intensive and trademark-intensive ex ante.20

Table 5 Panel B presents the same sample splits in the form of triple-differences estimates where we

interact the difference-in-differences term Post1995t × FamousTM1995i with a dummy variable for each

industry split as of 1995. These results mirror the sample splits. The triple-differences estimates also

represent a useful check on the robustness of our main estimates. If we now think of the treatment group

as treated firms in ad-intensive, selling-intensive and trademark-intensive industries and the control group

as treated firms in non-ad-intensive, selling-intensive or trademark-intensive industries respectively, then the

triple-difference coefficients represent the treatment effect in industries where trademarks are hypothesized

to matter more ex ante. In this setting the exclusion restriction is no longer that treated firms would have

had parallel trends with control firms in the absence of treatment. Instead, it is that any violation of parallel

trends by treated firms would have been similar across the industry splits. The fact that the triple-difference

coefficients remain positive, significant and of similar magnitude to our main estimates suggests that changes

in trademark policy rather than unobserved correlated shocks are driving our main estimates.

5 Effects on Firm Strategy and Industry Dynamics

One of the questions addressed theoretically in Chamberlin (1933) is optimal trademark policy and the

effects of trademark policy on firm behavior. In this section we investigate the effects of the FTDA through

the lens of treated firms’ operating strategy, innovation, and product market strategy.

5.1 Firm Value and Operating Strategy

Table 6 columns 1 and 2 suggest that the equity markets recognized the value of the profits that followed

the FTDA for treated firms. Post-FTDA treated firms’ average Tobin’s Q increased by 9.9% (t = 10.0) and

their market-to-book ratio increased by 15% (t = 8.9) relative to their industry-years. Recall that the rise

in ROA for treated firms was 13% of the average pretreatment profit margin (Section 4.2.3).21

20The correlations between the categories are modest: between selling-intensive and trademark-intensive, 46%; betweenad-intensive and selling-intensive, 18%; between ad-intensive and trademark-intensive, 14%.

21We take logs for easier interpretation and because both variables have highly right-skewed distributions. The coefficientson Q and Mkt/Book are also positive and highly significant.

18

We next investigate the effects of the FTDA on firms’ operating strategy. Columns 3, 4, and 5 show

that treated firms had higher sales growth (8.9%), cash holdings (2.4%) and capital investment (0.59%),

consistent with stronger trademark protection leading to a more aggressive operating strategy. Columns 6

and 7 show that treated firms did not significantly alter their selling or ad spending following the FTDA.

Taken together, these results suggest that treated firms used the positive shock to market power to adopt

a more aggressive operating strategy. Increased capital investment, sales growth, and cash levels suggest that

treated firms were more able to exploit investment opportunities as they became available. The observed

changes do not appear to be accompanied by major changes in marketing strategy as treated firms’ SG&A

and advertising expenses did not significantly change.

5.2 Product Quality

The central argument in favor of stronger trademark protection is that trademarks incentivize firms to

produce high quality products and prevent a race to the bottom in product quality. Most measures of product

quality are limited to specific industries and settings (e.g. Matsa (2010); Rose (1990); Fang (2005); Phillips

and Sertsios (2013)), and thus are not well suited to our broad cross-section of firms and industries. We

examine evidence on this fundamental question using a broad and objective measure of quality: recalls of

unsafe products.

The Consumer Product Safety Commission (CPSC) conducts safety testing and enforces recalls of most

consumer products in the United States; the National Highway Traffic Safety Administration (NHTSA)

conducts safety testing and enforces recalls of automotive products in the United States. Unsafe products

are detected through several channels. First, firms are required by law to conduct appropriate internal safety

tests and report defects as soon as they are discovered. Second, the agencies conduct proactive testing in

their own labs. Third, the agencies operate hotlines and websites that allow consumers to report unsafe

products.

We collect all 12,839 product recalls announced by the CPSC and NHTSA between 1989 and 2002. Using

a combination of fuzzy matching and manual matching, we match 6,780 recalls to Compustat firm-years where

we identify the firm as the manufacturer of the defective good.

Table 7 Panel A presents difference-in-differences estimates of the FTDA’s effects on product recalls.

Column 1 (logit) shows that treated firms were more than twice as likely (+141%) to announce a product

19

recall in any given year post-FTDA relative to control firms. The results are similar using a linear probability

model, where the estimated effect of the FTDA is +1.1% compared to a base rate of 0.9%, or using the

number of product recalls, either in logs or in a generalized negative binomial model. Column 5 shows that

the number of product units recalled rose by 12% post-FTDA for treated firms. Changes in the number of

units might reflect changes in firms’ product mix: Column 6 multiplies quantity by price to arrive at the

dollar value of products recalled. The dollar value of products recalled rose by 28% for treated firms relative

to control firms in the same industry-year.

These results suggest that the FTDA’s enhanced trademark protection actually resulted in lower product

quality among treated firms. An alternative explanation is that the sharp rise in recall frequency reflects

greater caution by treated firms; for example, if the increased profitability and value of their brands led

treated firms to conduct more careful testing and proactively recall defective products to protect the brand.

In Table 7 column 7, the dependent variable voluntary is the fraction of the firm’s NHTSA recalls that

were initiated by the firm. The estimated treatment effect is not statistically significant, which suggests that

firms’ likelihood of voluntarily recalling a faulty product did not change. Moreover the point estimate is

negative (-15%), that is, post-FTDA treated firms were less likely to initiate a recall voluntarily.

In a similar vein, the estimates in Panel A could be driven by changes in firm size or profitability: the

number and size of recalls should increase as treated firms’ sales increased and their brands became more

ubiquitous. Moreover, larger firms that sell more might be less able to conceal product defects and subject to

more testing. Table 7 Panel B adds controls for total sales, firm size (book value of assets) and profitability

(ROA) by firm-year. The correlation of total sales with the frequency and size of product recalls is indeed

positive. However, the diff-in-diff coefficients are almost unchanged in all cases, which suggests that changes

in firm size or profitability are not driving the results.

To sum up, across a range of specifications, firms treated by the FTDA were more likely to declare more

product recalls of more units with a higher dollar value and were slightly less likely to do so voluntarily.

These results suggest that treated firms actually lowered product quality in the post-FTDA period and are

inconsistent with the claim that trademark protection incentivizes firms to produce high quality products.

These results are, however, consistent with the quiet life (Bertrand and Mullainathan, 2003) and trademarks-

foster-monopoly (Chamberlin, 1933) hypotheses. In the absence of an incentive for higher quality, stronger

product market protection will lead firms to both raise prices and cut costs, since they face fewer competitive

20

threats. If product quality is costly to maintain via more internal testing and lower production yields, then

firms are likely to cut at these margins as well.

Our results are potentially also consistent with the quality-incentive hypothesis because we measure the

effects of dilution protection on treated firms which in the case of the FTDA were incumbents that owned

famous brands. The quality-incentive argument suggests that firms will produce high quality products in

order to build a reputation for their brand which cannot be stolen by imitators. Once that reputation is

established, an incumbent granted stronger protection will trade off the costs of higher quality (hiring more

inspectors, lower production yields) against the business lost by producing a lower quality product. But

if consumers have, or perceive, no close substitutes for the established brand – as Bronnenberg, Dube and

Gentzkow (2012) find – then demand will be more inelastic and the firm is more likely to cut corners.

5.3 Innovation and New Products

Next we investigate the relationship between trademark protection and firms’ innovation and new product

introductions. On one hand, a neoclassical model would suggest that when firms’ market power increases,

marginal new projects might become feasible due to a lower cost of capital or relaxing of financial constraints.

On the other hand, the quiet life hypothesis (Bertrand and Mullainathan, 2003) and the Chamberlin (1933)

foster-monopoly hypothesis suggest that stronger trademark protection leads to more managerial slack and

more cost-cutting and hence less innovation.

Table 8 investigates several measures of firms’ innovative activities. Treated firms reduced R&D spending

per total assets by 0.92% of book assets following the FTDA. This is a significant change relative to the

pretreatment average (3.4%) and standard deviation (3.8%) of treated firms’ R&D over book assets. Treated

firms took out fewer patents, with OLS regressions showing a 8.9% reduction in new patents. When we weight

patents by the adjusted citations they received, as a measure of patent quality, the results are even stronger

with treated firms generating 24% fewer adjusted citations. Thus, R&D spending and both the quantity and

quality of innovation strongly decreased among treated firms following the FTDA’s passage.

Column 4 finds that treated firms were 7.7% less likely to announce at least one new product in the Wall

Street Journal in the post-treatment period, with OLS in logs of the number of new products announced

showing similar results in Column 5. Taken together these results appear consistent with the quiet life and

trademarks-foster-monopoly hypotheses. While treated firms do experience higher value and profits and a

21

relaxation of financial constraints, the additional resources are not directed to innovative activities, but quite

the opposite.

5.4 Product Market Strategy

Table 9 investigates the FTDA’s effects on firms’ product market strategy as revealed by their trademark

activity. Column 1 shows that treated firms registered slightly fewer new trademarks post-FTDA, although

the change was not statistically significant. However, Column 2 shows that treated firms sharply increased the

number of goods-and-services classes in which they were active, by an additional 1.4 product classes. Probit

regressions (not shown) confirm that treated firms post-FTDA were more likely to register trademarks in

product classes in which they had never previously registered. Thus, the FTDA’s strengthening of trademark

protection led treated firms to expand their product mix into all-new classes of goods and services.

Column 3 shows that treated firms were more likely to register new trademarks that extended an existing

brand post-FTDA. This observation is consistent with the FTDA providing treated firms with incentives to

extend their protected brands into new product markets. Finally, Column 4 shows that treated firms were

more likely to renew the new trademarks registered post-FTDA. Thus treated firms were not only more

likely to extend their brands into new markets, but their new products were also more likely to be active in

commerce 10 years later, suggesting that they tended to remain a part of the firm’s product portfolio.

A stark example is Campbell’s Inc, which is a member of our treated group of firms under both the

renewal and textual criteria. The red-and-white Campbell’s logo that represents their core brand was first

registered in 1932 in a single trademark class, Foods (46). It was renewed in 1952, 1972, and 1993 and was

still active in the same one class in 1995, 63 years after its initial registration. In 1996 the firm registered

the Campbell’s logo in fifteen new trademark classes including Cutlery (25), Crockery and Porcelain (30),

Glassware (33), Paper and Stationery (37), Clothing (39), Jewelry (28), Furniture (32) and Unclassified (50).

Considering that each of these new classes was subject to the use-in-commerce requirement,22 it seems clear

that the new registrations represented a significant broadening of Campbell’s product market offerings in

precisely the year the FTDA became effective.22The Internet Appendix shows examples of Campbell’s branded furniture and jewelry that were produced and sold in the

late 1990s.

22

5.5 Industry Dynamics

Last we investigate the changes in industry dynamics that accompanied the FTDA’s shock to trademark

protection. We collapse the data to a SIC3 industry by year panel. We compute the fraction of industry

sales in 1995 that belonged to treated firms and this is our measure of the intensity with which each industry

was affected by the FTDA. 191 industries have a positive treated fraction (ranging from 0.007 to 1) and 80

industries have a treated fraction of zero.

Table 10 Panel A presents the results at the industry-year level using the Compustat data. Our specifica-

tions all use industry fixed effects which adjust for unobserved time-invariant characteristics of each industry,

and year fixed effects which adjust for aggregate trends. The number of public firms in industries with a

higher treated fraction fell post-FTDA. Moreover, the number of workers employed in treated industries fell

sharply post-FTDA.

Since the Compustat data contains only public firms, these results might reflect reallocation from public

to private firms rather than changes in the industries in question. To examine this possibility we use data

from the Synthetic Longitudinal Business Data (LBD).23 The Synthetic LBD is a synthetic dataset which

accurately reflects Census data at the industry-year level but preserves the confidential nature of the true

Census data. Thus, the Synthetic LBD presents an accurate picture of industry dynamics that covers both

public and private firms. Table 10 Panel B presents the results using the Synthetic LBD data. The results

are consistent with the Compustat estimates; the number of active plants fell significantly in industries with

a higher treated fraction post-FTDA, and total payrolls in more treated industries also fell by more.

These results are broadly consistent with the Chamberlin (1933) hypothesis that trademark protection

fosters monopoly and strengthens incumbents. Our estimates say that the FTDA’s effect on more inten-

sively treated industries resulted in greater industry concentration via fewer firms, fewer active plants, lower

employment and lower payrolls for both public and private firms.

6 Conclusion

We construct a new dataset of all trademarks registered at the USPTO since inception in 1870 to 2012, and

document evidence of a causal link between trademark protection and firm profits and strategy. Making use23http://www.census.gov/ces/dataproducts/synlbd/

23

of the 1996 Federal Trademark Dilution Act as a shock to the protection of a subset of trademarks, we find

that increased trademark protection resulted in sharply higher profits for treated firms which disappeared

after the key provision of the Act was nullified in 2003. We also document that the value of trademark

protection is localized in industries that had high ex ante advertising costs, selling costs and trademark

intensity.

We further investigate changes in firm strategy that follow enhanced trademark protection. Treated firms

altered their operating strategy with higher revenue growth, cash holdings and capital investment. Treated

firms also reduced product quality post-FTDA as measured by increased incidence and value of product

recalls, and curtailed innovation by reducing R&D spending, patenting, and new product announcements.

While these observations are broadly consistent with the quiet life hypothesis, we also find that treated

firms introduced new products into previously unexplored markets by extending their brands into all-new

goods and service classes. Trademarks associated with these new products are more likely to be opposed

by competing firms and subsequently renewed 10 years later. Taken together, these observations suggest

that stronger trademark protection leads firms to an exploitative rather than exploratory product market

strategy. At the industry level, we also find that industries that were more affected by the FTDA were more

concentrated and had lower employment and payrolls post-treatment relative to industries that were less

affected.

In sum, our paper makes three main contributions. First, we provide the first causal evidence that

trademark protection is a first-order determinant of firm profits and strategy. Second, we provide new evi-

dence that is broadly consistent with the contention of Chamberlin (1933) that trademark protection fosters

monopoly, funnels rents to incumbents, and actually lowers innovation and product quality. Incumbents

granted increased trademark protection do not simply enjoy the quiet life (Bertrand and Mullainathan,

2003) but extend their protected brands and pursue an exploitative rather than exploratory product market

strategy. Third, we generate the most comprehensive dataset of U.S. trademarks to date, greatly expanding

future research opportunities in the important area of trademark economics.

24

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010

2030

4050

6070

8090

Num

ber o

f Dilu

tion

Cas

es

1990 1995 2000 2005Year

Federal State

Figure 1: Number of trademark dilution cases filed in U.S. district courts by year, 1990-2005. We split thetotal number by year by the type of dilution claim: the grey area under the graph represents cases withfederal dilution claims while the blue area represents cases with state dilution claims.

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050

000

1000

0015

0000

2000

00N

ew T

rade

mar

ks R

egis

tere

d

1870 1890 1910 1930 1950 1970 1990 2010Year

Figure 2: Number of trademarks issued by the USPTO per year from 1870-2012

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-­‐0.01  

-­‐0.005  

0  

0.005  

0.01  

0.015  

0.02  

1990   1991   1992   1993   1994   1995   1996   1997   1998   1999   2000   2001   2002   2003   2004   2005  

Average  RO

A  

Treated   Control  

Moseley  FTDA  

Figure 3: The figure displays the average residual ROA for the treated and control firm groups, after firmand industry-by-year fixed effects, yearly from 1989-2005. The figure also displays standard errors for eachgroup mean in each year. To ease comparison we align the two series at zero in 1989.

34

Table 1: Summary statistics of the Compustat firm data panel for U.S. firms between 1982-2005.

Non-trademark holders Trademark holdersMean Median SD Mean Median SD

logSale 3.44 3.37 1.96 4.93 4.94 2.20logAssets 4.22 4.04 2.12 5.13 4.95 2.23ROA -0.014 0.038 0.283 0.050 0.104 0.244Q 2.07 1.26 2.36 2.09 1.40 2.06

Market/Book 3.14 1.48 5.52 3.13 1.79 4.63BookLeverage 0.276 0.217 0.264 0.236 0.190 0.229Capex/Assets 0.076 0.034 0.114 0.071 0.047 0.084Cash/Assets 0.145 0.058 0.204 0.171 0.079 0.212

Advertising/Assets 0.026 0.005 0.054 0.043 0.021 0.064R&D/Assets 0.080 0.009 0.154 0.090 0.041 0.136

TrademarkStock 0 0 0 25.6 4 87.7Firms 9,031 9,125

Observations 59,104 92,510

35

Table 2: Difference-in-differences estimates of the effects of the 1996 passage of the Federal TrademarkDilution Act on treated firms’ profits (ROA). Standard errors are robust and clustered by firm. ∗ : p <0.1, ∗∗ : p < 0.05, ∗∗∗ : p < 0.01.

(1) (2) (3) (4) (5) (6) (7) (8)ROA ROA ROA ROA ROA ROA ROA ROA

P ostF T DAt × 0.018*** 0.021*** 0.018*** 0.015*** 0.018*** 0.018***F amousT M1995i (5.3) (5.1) (4.4) (3.3) (4.6) (3.8)

P ost2002t × -0.011** -0.013** -0.012*** -0.016***F amousT M2002i (-2.4) (-2.5) (-2.7) (-3.2)

logAssetsit 0.066*** 0.068*** 0.10*** 0.075***(22.0) (21.8) (25.8) (27.9)

Qit -0.0084*** -0.0092*** -0.0043*** -0.0077***(-5.7) (-6.2) (-3.2) (-6.7)

Capex/Assetsit 0.13*** 0.12*** 0.095*** 0.13***(9.5) (8.7) (5.6) (10.4)

Ageit -76.6 0.77 -0.48 0.18(-0.0) (0.0) (-0.0) (0.0)

logT rademarkStockit -0.013*** -0.0094*** -0.0082*** -0.0098***(-4.8) (-3.3) (-2.6) (-4.2)

Observations 69,559 56,757 69,329 56,500 67,632 52,930 107,779 84,950R-squared 0.633 0.671 0.666 0.703 0.749 0.777 0.703 0.736Period 1989-2002 1989-2002 1989-2002 1989-2002 1996-2005 1996-2005 1989-2005 1989-2005Firm FE Yes Yes Yes Yes Yes Yes Yes YesYear FE Yes Yes No No No No No NoIndustry x Year FE No No Yes Yes Yes Yes Yes Yes

36

Table 3: Robustness and specification checks estimating the effects of the 1996 passage of the FederalTrademark Dilution Act on treated firms’ profits. Standard errors are robust and clustered by firm. ∗ : p <0.1, ∗∗ : p < 0.05, ∗∗∗ : p < 0.01.

(1) (2) (3) (4) (5) (6) (7)ROA ROA ROA ROA ROA ROA ROA

P ost1995t × 0.013*** 0.020*** 0.016*** 0.015***F amousT M1995i (3.2) (3.7) (3.6) (3.0)

pretrendi × t 0.076***(6.4)

P ostF T DAt × 0.000163***nF amousT M95i (2.7)

P ost1988t × -0.0053* -0.0040F amousT M1988i (-1.7) (-1.0)

Observations 63,927 69,329 45,151 33,058 30,251 77,468 77,300R-squared 0.662 0.666 0.675 0.680 0.641 0.668 0.692Firm FE Yes Yes Yes Yes Yes Yes YesYear FE No No No No No Yes NoIndustry x Year FE Yes Yes Yes Yes Yes No Yes

No TM Controls Only TM Controls Balanced Panel TLRA Placebo TLRA PlaceboRobust t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1

37

Table 4: Difference-in-differences estimates of the effects of the 1996 passage of the Federal TrademarkDilution Act on firm profits using the alternative textual definition of “famous” trademarks based on thescanned texts in Google Books published between 1986-1995. Standard errors are robust and clustered byfirm. ∗ : p < 0.1, ∗∗ : p < 0.05, ∗∗∗ : p < 0.01.

(1) (2) (3) (4) (5) (6)ROA ROA ROA ROA ROA ROA

P ostF T DAt × 0.010*** 0.014*** 0.013*** 0.015***T extualF amousT M1995i (2.6) (3.0) (3.4) (3.2)

P ost2002t × -0.024*** -0.013*** -0.024*** -0.014***T extualF amousT M1995i (-6.0) (-2.9) (-5.9) (-3.0)

Observations 69,559 69,329 67,815 67,632 109,261 108,998R-squared 0.633 0.666 0.729 0.749 0.684 0.708Period 1989-2002 1989-2002 1996-2005 1996-2005 1989-2005 1989-2005Firm FE Yes Yes Yes Yes Yes YesYear FE Yes No Yes No Yes NoIndustry x Year FE No Yes No Yes No Yes

38

Table 5: Difference-in-differences estimates of the effects of the 1996 passage of the Federal TrademarkDilution Act on treated firms’ profits (ROA), splitting the sample by industry-level measures of advertising,SG&A, and trademark stock as of 1995. Standard errors are robust and clustered by firm. ∗ : p < 0.1, ∗∗ :p < 0.05, ∗∗∗ : p < 0.01.

Panel A: Sample Splits

(1) (2) (3) (4) (5) (6)High Low High Low High Low

Advertising Advertising SG&A SG&A TrademarkStock TrademarkStock

PostFTDAt × 0.027*** 0.004 0.029*** 0.006 0.022*** 0.007FamousTM1995i (4.6) (0.8) (4.9) (1.2) (4.4) (1.2)

Observations 33,525 35,587 35,290 33,826 35,274 33,884R-squared 0.691 0.664 0.689 0.654 0.692 0.664Firm FE Yes Yes Yes Yes Yes YesYear FE No No No No No NoIndustry x Year FE Yes Yes Yes Yes Yes Yes

Panel B: Triple-Differences Estimates

(1) (2) (3)ROA ROA ROA

PostFTDAt × FamousTM1995i 0.004 0.003 0.007(0.7) (0.7) (1.1)

PostFTDAt × FamousTM1995i × HighAdvertising 0.026***(3.3)

PostFTDAt × FamousTM1995i × HighSG&A 0.026***(3.4)

PostFTDAt × FamousTM1995i × HighTrademarks 0.016**(2.1)

Observations 69,329 69,329 69,329R-squared 0.655 0.676 0.644Firm FE Yes Yes YesIndustry x Year FE Yes Yes Yes

39

Table 6: Difference-in-differences estimates of the effects of the 1996 passage of the Federal TrademarkDilution Act on firm value and operating strategy. Standard errors are robust and clustered by firm. ∗ : p <0.1, ∗∗ : p < 0.05, ∗∗∗ : p < 0.01.

(1) (2) (3) (4) (5) (6) (7)logQ logMarket/Book SalesGrowth Cash/Assets Capex/Assets SG&A/Sale Advertising/Assets

PostFTDAt × 0.099*** 0.15*** 0.089*** 0.024*** 0.0059*** 0.012 -0.0027FamousTM1995i (10.0) (8.9) (7.6) (5.8) (3.1) (1.0) (-0.9)

Observations 63,307 66,866 66,023 71,304 60,249 57,040 19,939R-squared 0.678 0.652 0.265 0.736 0.572 0.649 0.866Firm FE Yes Yes Yes Yes Yes Yes YesIndustry X Year FE Yes Yes Yes Yes Yes Yes Yes

40

Table 7: Difference-in-differences estimates of the effects of the 1996 passage of the Federal TrademarkDilution Act on product recalls. Standard errors are robust and clustered by firm. ∗ : p < 0.1, ∗∗ : p <0.05, ∗∗∗ : p < 0.01.

Panel A

(1) (2) (3) (4) (5) (6) (7)had_recall had_recall nrecalls log(recalls) log(units) log(recallvalue) voluntary

PostFTDAt × 1.41*** 0.011*** 0.45* 0.011*** 0.12*** 0.28*** -0.15FamousTM1995i (2.9) (3.0) (1.9) (2.7) (3.0) (4.3) (-1.0)

Observations 71,541 71,318 71,541 71,318 71,318 70,826 213R-squared 0.562 0.789 0.586 0.305 0.459Model Logit OLS Neg.Bin OLS OLS OLS OLSFirm FE Yes Yes Yes Yes Yes Yes YesYear FE Yes No Yes No No No NoIndustry x Year FE No Yes No Yes Yes Yes Yes

Panel B: Firm-year controls for size and profitability

(1) (2) (3) (4) (5) (6) (7)had_recall had_recall nrecalls log(recalls) log(units) log(recallvalue) voluntary

PostFTDAt × 1.10*** 0.011*** 0.43** 0.011*** 0.13*** 0.27*** -0.19FamousTM1995i (4.6) (3.1) (2.4) (2.8) (3.2) (4.3) (-1.2)

ROA -1.13** -0.0018 -1.42*** -0.0018 -0.018 -0.014 -0.29(-2.0) (-1.4) (-2.6) (-1.2) (-1.2) (-0.7) (-0.7)

logSales 2.24*** 0.0016** 1.85*** 0.0017*** 0.015*** 0.0050 -0.17(13.1) (2.5) (11.5) (2.8) (2.7) (0.8) (-0.7)

logAssets -1.19*** 0.00061 -0.93*** 0.00029 0.0079 0.0025 0.13(-8.8) (0.9) (-6.1) (0.4) (1.1) (0.3) (0.7)

Observations 69,575 69,329 69,575 69,575 69,329 68,838 213R-squared 0.563 0.790 0.587 0.306 0.468Model Logit OLS Neg.Bin OLS OLS OLS OLSFirm FE Yes Yes Yes Yes Yes Yes YesYear FE Yes No Yes No No No NoIndustry x Year FE No Yes No Yes Yes Yes Yes

41

Table 8: Difference-in-differences estimates of the effects of the 1996 passage of the Federal TrademarkDilution Act on firm innovation. Standard errors are robust and clustered by firm. ∗ : p < 0.1, ∗∗ : p <0.05, ∗∗∗ : p < 0.01.

(1) (2) (3) (4) (5)R&D/Assets logNewPatents logPatentCites NewProduct logNewProducts

PostFTDAt × -0.0092*** -0.089*** -0.24*** -0.077*** -0.16***FamousTM1995i (-4.0) (-3.8) (-5.5) (-7.7) (-10.2)

Observations 34,124 71,318 71,318 58,487 58,487R-squared 0.742 0.865 0.798 0.670 0.784Model OLS OLS OLS LPM OLSFirm FE Yes Yes Yes Yes YesIndustry X Year FE Yes Yes Yes Yes Yes

42

Table 9: Difference-in-differences estimates of the effects of the 1996 passage of the Federal TrademarkDilution Act on firms’ trademark activity. Standard errors are robust and clustered by firm. ∗ : p < 0.1, ∗∗ :p < 0.05, ∗∗∗ : p < 0.01.

(1) (2) (3) (4)logNewTrademarks ActiveClasses BrandExtending WasRenewed

PostFTDAt × -0.026 1.40*** 0.038*** 0.052***FamousTM1995i (-1.1) (6.6) (3.6) (3.1)

Observations 71,318 71,318 16,782 16,782R-squared 0.747 0.918 0.852 0.461Firm FE Yes Yes Yes YesIndustry X Year FE Yes Yes Yes Yes

43

Table 10: Difference-in-differences estimates of the effects of the 1996 passage of the Federal TrademarkDilution Act on industry dynamics. Observations are at the SIC3 industry-year level. Standard errors arerobust and clustered by industry. ∗ : p < 0.1, ∗∗ : p < 0.05, ∗∗∗ : p < 0.01.

(1) (2) (3)logF irms nFirms logEmployees

PostFTDAt × -0.12* -0.11 -0.58***FamousTM1995i (-1.9) (-1.5) (-4.8)

Observations 3,756 3,756 3,756R-squared 0.948 0.923Model OLS Neg.Bin. OLSIndustry FE Yes Yes YesYear FE Yes Yes Yes

(1) (2) (3)logP lants nP lants logPay

PostFTDAt × -0.065** -0.082*** -0.098**FamousTM1995i (-2.2) (-2.9) (-2.3)

Observations 2,647 2,647 2,647R-squared 0.997 0.981Model OLS Neg.Bin. OLSIndustry FE Yes Yes YesYear FE Yes Yes Yes

44