Intellectual Property and the U.S. Economy: 2016 Update

JOIN POJC M

Inellecual

Proper and he

U.S. conom:

016 Updae

conomics  Saisics

dminisraion

Justin Antonipillai

Counselor to the Secretary

Delegated Duties of the Under Secretary

for Economic Aairs

Robert Rubinovitz, Deputy Chief Economist

David Langdon, Economist and Policy Advisor

Fenwick Yu, Economist

William Hawk, Economist

U.S. Paen and

rademar Oce

Michelle K. Lee

Under Secretary of Commerce for

Intellectual Property and Director,

U.S. Patent and Trademark Oce

Alan C. Marco, Chief Economist

Andrew A. Toole, Deputy Chief Economist

Asrat Tesfayesus, Economist

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CNODMNS

e Project Team would like to thank Vikrum Aiyer, Alexander Beck, David Carson, Amy Cotton,

Edward Elliot, Jim Hirabayashi, Amanda Myers, Nicholas Pairolero, Sandy Phetsaenngam, Shi-

ra Perlmutter, Bridget Petruczok, Roy Rabindranath, Patrick Ross, and Daina Spencer from the

USPTO; Nikolas Zolas and Cynthia Davis Hollingsworth from the Census Bureau; omas How-

ells, Gabriel Medeiros, and Amanda Lyndaker from the Bureau of Economic Analysis; and Ryan

Noonan and Rodolfo Telles from the Economics and Statistics Administration’s Oce of the Chief

Economist for their valuable contributions to this report.

ecuie Summar

Innovation and creative endeavors are indispensable elements that drive economic growth and

sustain the competitive edge of the U.S. economy. e last century recorded unprecedented

improvements in the health, economic well-being, and overall quality of life for the entire U.S.

population.

As the world leader in innovation, U.S. companies have relied on intellectual prop-

erty (IP) as one of the leading tools with which such advances were promoted and realized. Pat-

ents, trademarks, and copyrights are the principal means for establishing ownership rights to the

creations, inventions, and brands that can be used to generate tangible economic benets to their

owner.

In 2012, the Department of Commerce issued a report titled Intellectual Property and the U.S.

Economy: Industries in Focus (hereaer, the 2012 report). e report identied the industries

that rely most heavily on patents, trademarks, or copyrights as IP-intensive and estimated their

contribution to the U.S. economy. It generated considerable interest and energized other agencies

and organizations to produce similar studies investigating the use and impact of IP across coun-

tries, industries, and rms.

is report builds on the 2012 version by providing an update on the impact of IP on our econo-

my and a fresh look at the approach used to measure those results. e update continues to focus

on measuring the intensity of IP use, and its persistent relationship to economic indicators such

as employment, wages, and value added. While our methodology does not permit us to attribute

those dierences to IP alone, the results provide a useful benchmark. Furthermore, this and other

studies together make clear that IP is a major part of a robust and growing economy.

Accordingly, in an eort to provide a more comprehensive analysis, this report also incorporates

ndings from other studies that target similar research questions but apply dierent methodol-

ogies. Overall, we nd that IP-intensive industries continue to be an important and integral part

of the U.S. economy and account for more jobs and a larger share of U.S. gross domestic product

(GDP) in 2014 compared to what we observed for 2010, the latest gure available for the 2012

report. We discuss these and other results in more detail below.

1 Gordon 2016.

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Principal indings

• IP-intensive industries continue to be a major, integral and growing part of the

U.S. economy.

• is report identies 81 industries (from among 313 total) as IP-intensive. ese IP-inten-

sive industries directly accounted for 27.9 million jobs in 2014, up 0.8 million from 2010.

• Trademark-intensive industries are the largest in number and contribute the most employ-

ment with 23.7 million jobs in 2014 (up from 22.6 million in 2010). Copyright-intensive

industries supplied 5.6 million jobs (compared to 5.1 million in 2010) followed by pat-

ent-intensive industries with 3.9 million jobs (3.8 million in 2010).

• While jobs in IP-intensive industries increased between 2010 and 2014, non-IP-intensive

jobs grew at a slightly faster pace. Consequently, the proportion of total employment in

IP-intensive industries declined slightly to 18.2 percent (from 18.8 percent in 2010).

• In contrast, the value added by IP-intensive industries increased substantially in both total

amount and GDP share between 2010 and 2014. IP-intensive industries accounted for

$6.6 trillion in value added in 2014, up more than $1.5 trillion (30 percent) from $5.06

trillion in 2010. Accordingly, the share of total U.S. GDP attributable to IP-intensive in-

dustries increased from 34.8 percent in 2010 to 38.2 percent in 2014.

• While IP-intensive industries directly accounted for 27.9 million jobs either on their pay-

rolls or under contract in 2014, they also indirectly supported 17.6 million more supply

chain jobs throughout the economy. In total, IP-intensive industries directly and indirectly

supported 45.5 million jobs, about 30 percent of all employment.

• Private wage and salary workers in IP-intensive industries continue to earn signicantly

more than those in non-IP-intensive industries. In 2014, workers in IP-intensive indus-

tries earned an average weekly wage of $1,312, 46 percent higher than the $896 average

weekly wages in non-IP-intensive industries in the private sector. is wage premium has

largely grown over time from 22 percent in 1990 to 42 percent in 2010 and 46 percent in

2014. Patent- and copyright-intensive industries have seen particularly fast wage growth

in recent years, with the wage premium reaching 74 percent and 90 percent, respectively,

in 2014.

• e educational gap between workers in IP-intensive and other industries observed in

2010 virtually disappeared by 2015. e share of workers in IP-intensive industries with a

bachelor’s degree or higher fell from 42.4 percent in 2010 to 39.8 percent in 2015, whereas

that percentage increased from 34.2 percent to 38.9 percent for workers in non-IP-inten-

sive industries.

• Revenue specic to the licensing of IP rights totaled $115.2 billion in 2012, with 28 indus-

tries deriving revenues from licensing.

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• Total merchandise exports of IP-intensive industries increased to $842 billion in 2014

from $775 billion in 2010. However, because non-IP-intensive industries’ exports in-

creased at a faster pace, the share of total merchandise exports from IP-intensive indus-

tries declined to 52 percent in 2014 from 60 percent in 2010.

• Exports of service-providing IP-intensive industries totaled about $81 billion in 2012 and

accounted for approximately 12.3 percent of total U.S. private services exported in 2012.

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able O Conens

ecuie Summar ..................................................................i

I. Inroducion ......................................................................1

II. he 01 epor and elaed Sudies ...............................................

III. Ideniing IP-Inensie indusries ..................................................

Paens ......................................................................................... 

rademars .....................................................................................8

Coprighs ......................................................................................9

I. IP-Inensie Indusries in he conom ............................................10

mplomen ................................................................................... 10

oal mplomen Suppored b IP-inensie Indusries .............................................1

IP-Inensie Paroll Jobs b Sae ................................................................ 14

erage ages ................................................................................. 19

ducaion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

alue added ...................................................................................

IP eenue .....................................................................................

oreign rade ................................................................................... 

. Conclusion ......................................................................0

ppendi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Paens .........................................................................................1

racional s. hole Paens Couns ..............................................................1

Mehodolog ..................................................................................

rademars ....................................................................................4

rademar Inensi ............................................................................

op 0 rademar egisering Companies .......................................................8

andom Sample o ll rademar egisraions ...................................................9

Coprighs .....................................................................................46

Combined is o IP-inensie indusries ..........................................................4

NCS ......................................................................

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I. Inroducion

“Whether through the music or movies that inspire us, the literature that moves

us, or the technologies we rely on each day, ingenuity and innovation serve as the

foundation upon which we will continue to grow our economies and bridge our

cultural identities.”

— President Barack Obama, April 26, 2016

Innovation and creative endeavors are indispensable elements that drive economic growth and

sustain the competitive edge of the U.S. economy. e last century recorded unprecedented im-

provements in the health, economic well-being, and overall quality of life for the entire U.S. pop-

ulation as technological innovation in medicine and groundbreaking scientic advances in many

elds were realized.

Tremendous advances in worker productivity boosted individuals’ earning

capacity. is allowed consumers to purchase and enjoy the abundant supply of new products

and increasingly diverse creative works of art. As goods and services became more accessible,

they were distinctively marked so buyers could readily select products that meet their individual

preferences.

Intellectual property (IP) has been a vital instrument for achieving such advances throughout our

nation’s history. A growing number of U.S. and international studies demonstrate the important

role of IP in economic activity. is report shows that IP-intensive industries continue to be a

major, integral and growing part of the U.S. economy. We nd that the 81 industries designated

as IP-intensive directly accounted for 27.9 million jobs and indirectly supported an additional

17.6 million jobs in 2014. Together, this represented 29.8 percent of all jobs in the U.S. e total

value added by IP-intensive industries amounted to 38.2 percent of U.S. GDP and IP-intensive

industries paid 47 percent higher weekly wages compared to other industries. Further, at $842

billion the merchandise exports of IP-intensive industries made up 52 percent of total U.S. mer-

chandise exports. Exports of service-providing IP-intensive industries totaled about $81 billion

in 2012, accounting for 12.3 percent of total U.S. private exports in services.

IP incentivizes the creation of new goods and services by conferring exclusive rights to their

creators. While inventions typically are a product of ingenious endeavors that require long, per-

sistent, and meticulous eort, subsequent duplication and use of such innovations are oen less

costly. Patents add to the incentive that inventors have to invest in costly research and develop-

ment (R&D) by providing the opportunity to reap the rewards of their innovations. In the words

of Abraham Lincoln, the patent system “added the fuel of interest to the re of genius in the

discovery and production of new and useful things.”

Similarly, copyrights provide the frame-

work that incentivizes authors to create literary, artistic, musical, dramatic, cinematic, and other

works by granting them the exclusive right to engage in the activities that derive economic bene-

2 Gordon 2016.

3 Nicolay and Hay 1905, 113.

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ts from their work. us, patents and copyrights serve as tools to stimulate individual, rm, and

industry level entrepreneurial ventures that feed into economic activities nationwide.

To further exploit the potential of their competitive advantage, producers need eective ways

to indicate to consumers the reliability of their products’ source. A trademark “makes eective

competition possible in a complex, impersonal marketplace by providing a means through which

the consumer can identify products which please him and reward the producer with continued

patronage.”

Patents, trademarks, and copyrights are the principal means for establishing ownership rights

to the creations, inventions, and brands that can be used to generate tangible economic benets

to their owner. In 2012, the Department of Commerce issued a report titled Intellectual Proper-

ty and the U.S. Economy: Industries in Focus. Produced jointly by the Economics and Statistics

Administration (ESA) and the United States Patent and Trademark Oce (USPTO), the report

aimed to identify the industries that rely most heavily on patents, trademarks, or copyrights as

IP-intensive and estimate the contribution of those industries to the U.S. economy. It generated a

substantial amount of interest in the IP community, both domestically and abroad, and motivat-

ed other agencies and organizations to produce similar studies investigating the use and impact

of IP across countries, industries, and rms.

is update of the 2012 report has two purposes. First, we duplicate the methodology of the 2012

report to examine how the economic contribution of U.S. IP-intensive industries has evolved.

Second, we review related studies that have been completed since 2012, and discuss the contribu-

tions of the dierent methods. e latest results bolster the 2012 ndings, conrming — across a

range of methodologies — the importance of IP in the economy. In fact, the relative contribution

of IP-intensive industries generally increased in the last several years. We describe these and oth-

er results in more detail in Section IV below.

is report attempts to understand the ways in which IP is used across dierent industries. Our

methodology aims to measure the intensity of IP use, but does not directly measure the extent to

which IP incentivizes the creation of new goods and services. We nd dierences in employment,

wages, value added, and other outcomes that are correlated with IP use, although our method-

ology does not permit us to attribute those dierences to IP alone. As in any area of research, no

single study will yield the complete picture.

is is why it is important for policy-makers and researchers to consider multiple methodologies

for understanding how IP functions in the economy. We are encouraged that other organizations,

agencies, and governments have been energized to replicate, extend, or supplement the work

done in the 2012 report. Taken together, these contributions signicantly advance our knowledge.

Persistent research with a solid empirical foundation will continue to provide the evidence upon

which good policy can rest. e evidence to date demonstrates that IP is an important part of a

robust and growing economy.

4 Smith v. Chanel, Inc. 402 F.2d 562, 566 (9

Cir. 1968).

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II. he 01 epor and elaed Sudies

It is instructive to evaluate the methodology and results of the 2012 report in the context of the

related research completed since the rst report’s release. e 2012 report identied IP-intensive

industries, and compared those industries to other industries across a number of dierent di-

mensions. e methodology consisted of identifying IP-intensive industries based on the use of

IP. According to that report, intellectual property protection aects commerce throughout the

economy by:

• Providing incentives to invent and create;

• Protecting innovators from unauthorized copying;

• Facilitating vertical specialization in technology markets;

• Creating a platform for nancial investments in innovation;

• Supporting entrepreneurial liquidity through mergers, acquisitions, and IPOs;

• Supporting licensing-based technology business models; and

• Enabling a more ecient market for trading in technology and know-how.

All of these mechanisms combine to determine the value of IP to individuals and rms and the

contribution of IP to the economy. Analyzing and measuring all the ways in which IP impacts

the economy is beyond the scope of any individual report. However, a number of studies quanti-

fying the economic impact of IP-intensive rms have emerged since the publication of the 2012

report. We are encouraged to see continued interest in research that builds upon, challenges, and

provides alternative methodologies to the 2012 report.

is section reviews a selected group of studies that targeted similar research questions to the

2012 report and which were published aer that time. e European Patent Oce and the Oce

for Harmonization in the Internal Market (OHIM) published a comparable report in 2013 using

European Union (EU) data.

It relies on similar methodologies to identify intellectual proper-

ty rights (IPR) intensive industries in Europe and quanties their contribution to the European

economy in the 2008–2010 period. e study nds that IPR-intensive industries generated €4.7

trillion worth of economic activity, which amounted to almost 39% of EU GDP. Furthermore, the

study nds that IPR-intensive industries directly employed 56.5 million Europeans, which ac-

counted for almost 26% of all jobs for the period. e similarity in the ndings serves to further

reinforce the core message of the 2012 report that IP-intensive industries are an integral part of

the economy.

While these reports quantify the contribution of IP-intensive industries in the economy, there is

justied skepticism as to how accurately the employment and value added outcomes can be at-

5 AsofMarch2016,OHIMisknownastheEuropeanUnionIntellectualPropertyOfce.

6 EPO and OHIM 2013.

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tributed to IP itself. For example, the fact that we observe signicant employment in IP-intensive

industries does not inform us about the contribution of IP to economic growth because employ-

ment in non-IP-intensive industries is a viable alternative. e reports also study the wage dier-

entials between IP-intensive and non-IP-intensive industries. Both reports show that IP-intensive

industries pay higher wages than other industries. While this wage premium is noteworthy, we

cannot conclude that the wage dierential is due to IP.

In 2015, OHIM issued a second report, relying on rm-level data to compare rms that own

IPRs to those that do not.

e report considers a representative sample of over 130,000 Euro-

pean rms and studies their economic outcomes, taking into account whether they own patents,

trademarks, or designs. e study nds that IPR-owning rms earn, on average, 29 percent more

in revenue per employee and pay, on average, 20 percent more in wages. is dierence is even

more signicant for small and medium enterprises that own IPRs as they earn 32 percent more

in revenue, on average, per employee compared to their counterparts with no IPRs. While this

study does not identify the causal impact of IPRs, it provides detailed evidence of a high correla-

tion between IPR-ownership and economic performance.

e methodology in the 2015 OHIM study addresses a limitation in the way the earlier reports

dened IP-intensive industries. e previous reports measure IP-intensity at the industry-level

based on the aggregate volume of IP relative to employment. ey then designate an industry

as IP-intensive or non-IP-intensive based on whether the IP to employment ratio falls above or

below the average for all industries. ere are reasonable, alternative measures of IP intensity;

including a ratio of IP to gross output, research and development, or value added. But data lim-

itations, such as data sensitivity and the absence of legal requirements on producers to record

and report on internal activities, preclude access to data at the level of detail needed to systemat-

ically employ such measures. e 2015 OHIM report successfully overcomes these limitations by

developing detailed IP-to-rm data necessary for conducting a disaggregated analysis comparing

IPR-owning with non-IPR-owning rms in Europe.

USPTO and U.S. Census researchers have recently constructed patent-to-rm data to enable

similar analysis for the U.S.

e authors match data on owners and inventors of U.S. patents

issued between 2000 and 2011 to U.S. Census Bureau data on rms and workers. Using this com-

prehensive database, the authors analyze patent-intensive rms and their contribution to the U.S.

economy. ey nd that patenting rms represent only 1 percent of U.S. rms (2000–2011) but

are among the largest in the economy, accounting for 33 percent of employment. Patenting rms

create more jobs than their non-patenting counterparts of the same age across all age categories

except the very youngest (rms <1 year old). e authors also nd that most patenting rms are

small businesses. But, because they patent less frequently, the majority of U.S. patents are held by

a few large, prolic patenting rms. Lastly, they nd that while the manufacturing sector is par-

7 OHIM 2015.

8 Graham et al. 2015.

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ticularly patent intensive with more than 6 percent of rms owning a patent between 2000 and

2011, the majority of patenting rms are in the services and wholesale sectors.

A handful of recent academic papers have also attempted to measure the impact of IP on rm

performance. One recent notable contribution uses detailed USPTO data to study whether pat-

ents have a causal impact on the growth potential of startups.

e authors nd that patents do in

fact “help startups create jobs, grow their sales, innovate, and eventually succeed” and that a delay

in a patent grant can retard the benet of each of these.

Another line of research uses surveys to study the role that IP plays in the economic performance

of rms as well as their innovative eorts. A recent study surveys over 6,000 American manufac-

turing and service sector rms to evaluate the extent to which rms that introduce new products

in the market outsource innovation to specialized rms. It nds that between 2007 and 2009, 16

percent of manufacturing rms introduced a new product in their industry. Of these innovators,

42 percent reported patenting their most signicant new product, though there is considerable

variation across industries and rms. More R&D-intensive industries, i.e., those with above

average share of rms investing in R&D, tend to patent new products at higher than average

rates. Roughly 63 percent of large manufacturing rms reported patenting their most signicant

new product innovation, compared to only 47 percent of medium rms and 36 percent of small

rms.

e UK Intellectual Property Oce published another survey based study in 2012 that aims to

quantify the extent to which patents increased expenditure in R&D. Using data from the UK in-

novation survey and linked data on rm performance, the authors estimate the patent prot pre-

mium, meaning the additional returns to R&D that can be attributed to patent protection.

ey

nd that patent premiums are positive and provide incentives to invest in R&D, though estimates

vary by type of rm and industry. Estimated patent premiums are lower for smaller rms and

rms outside biotech and pharmaceutical industries. However, premium and incentive eects are

comparable for young and older rms, indicating that patent protection can incentivize R&D for

new as well as established innovators.

9 Farre-Mensa et al. 2016. By employing an instrumental variables approach, the authors are able to identify a causal

relationship, as opposed to a mere correlation.

10 Ibid., 2.

11 Note that some startups may prefer a delay in patent grant because a larger share of its overall economic value may be

realized later in the patent term or during the period of time that is accrued due to patent term adjustment.

12 Arora et al. 2016.

13 Arora et al. 2012.

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Taken together, these contributions signicantly advance our knowledge about the role of IP in

the economy. An important direction of future work is exploiting even more granular data and

seeking methods to identify causal links between IP and economic performance. Survey based

studies, which can be designed to target specic research questions, will also continue to improve

our understanding about the extent to which IP contributes to the economy. And it is critical that

policy-makers consider scientic research standards when evaluating evidence with policy mak-

ing implications.

InellecualProperandheUSconomUpdae 

III. Ideniing IP-Inensie indusries

As in the 2012 report, IP-intensity for an industry is dened as the count of its intellectual prop-

erty for a given period of time relative to the industry’s total employment. An industry is desig-

nated as IP-intensive if its IP-count to employment ratio is higher than the average for all indus-

tries considered. Dividing IP-counts by employment is one approach to adjust for dierences in

industry size, which makes industries more comparable. However, there are other alternatives.

For instance, IP-counts could be normalized by capital holdings, research and development ex-

penditures, value added, or gross output. In addition, other methods are available for dierenti-

ating between IP-intensive and non-IP-intensive industries.

To maintain consistency and allow

comparisons to the 2012 report, this update follows the methodologies applied previously but

expands coverage to the 2009–2013 period.

Paens

e USPTO grants utility, plant, and design patents that give the grantee the right to exclude

“others from making, using, oering for sale, or selling the invention throughout the United

States or importing the invention into the Unites States.”

Using the U.S. Patent Classication

(USPC) scheme, patents are classied in over 450 patent “technology classes” that distinguish

their inventive content.

e USPTO maintains a general concordance between its technology

classications and 30 North American Industry Classication (NAICS) codes. e concordance

enables analysts to associate utility patents with these NAICS coded industries.

We rely on

NAICS-based patent counts for 2009 to 2013 to identify patent-intensive industries.

is ap-

proach strictly limits the patent analysis to the manufacturing sector because the concordance

only associates patents with manufacturing industries. Non-manufacturing industries, such as

construction, utilities, and information, may rely on utility patents, but these industries are not

captured by the patent-NAICS concordance. We calculate a measure of industry patent “intensity”

dened as the ratio of total patents over the ve years in a NAICS category to the average payroll

14 For example, analyzing the differences by deciles or even evaluating a continuous function are possible alternative

approaches that may prove informative.

15 Detailed description of the methodology is provided in the Appendix.

16 35 U.S.C. § 154(a)(1).

17 Utilitypatentsmaybeclassiedintomorethanonetechnologyclassbutareorganizedaccordingtotheirprimaryclas-

sication.

18 Whileitdoesnotaffectanyoftheresultsinthisreport,itisworthnotingthatofcialuseoftheUSPCwasdiscontin-

uedinJanuaryof2015.PatentsarenowclassiedusingtheCooperativePatentClassication(CPC)scheme.

19 ThisconcordancewascreatedbytheUSPTOwithnancialsupportfromtheNationalScienceFoundation.Becauseno

similar concordances to NAICS are available for plant or design patents, only utility patents are used in our analysis.

Seewww.uspto.gov/web/ofces/ac/ido/oeip/taf/all_tech.htmformoreinformationonutilitypatents.Foranoverview

of NAICS, see www.census.gov/eos/www/naics/index.html.

20 Seewww.uspto.gov/web/ofces/ac/ido/oeip/taf/data/misc/patenting_trends/info_ptrends2008.txt.

InellecualProperandheUSconomUpdae 

employment by industry.

Because employment reects the overall size of an industry, dividing

patent counts by employment normalizes patenting activity with respect to industry size.

is

approach evens the playing eld, so that the most patent-intensive industries are dened not as

the ones with the most patents, but rather as those with the most patents per worker.

Nearly all the industries identied as patent-intensive in the 2012 report are also designated as

such for the 2009–2013 period. One industry, resin, synthetic rubber, bers, and articial and

synthetic bers and laments (NAICS 3252), did not make the cuto in the current report. In

addition, some changes occurred in the rank-order of these industries. For example, semiconduc-

tor and other electronic components (NAICS 3344) was previously designated as the third most

patent-intensive industry, but dropped to h place. However, based on the close similarity in

the list and rank-order of patent-intensive industries across reports, it appears that patent-inten-

sity at the industry level is quite persistent over time.

rademars

A trademark is dened as “a word, phrase, symbol, or design, or a combination thereof, that iden-

ties and distinguishes the source of the goods of one party from those of others.”

rough ex-

clusive rights of use, trademarks confer legal protection that enables companies to communicate

to consumers the quality characteristics of their products and services and recoup investments

therein.

As in the 2012 report, this study uses three dierent approaches to identify trademark-intensive

industries.

e rst approach, as with patents, measures the trademark-intensity of an industry

based on the ratio of trademark counts to employment and designates those industries with an

above average ratio as trademark-intensive. Starting with the complete set of trademark regis-

trations, we matched publicly traded companies by their name to a separate database containing

information on the rms’ primary industry and number of employees. ese data allowed us to

calculate trademark intensity by industry for the matched rms. e second approach uses the

USPTO’s listing of top 50 trademark registering companies (which, unlike the rst approach,

include both private and public companies) from the Performance and Accountability Reports

for 2009–2013 and identies industries that appear repeatedly as trademark-intensive. To expand

coverage for privately-held companies and for smaller and younger rms, the third approach

draws a random sample of 300 registrations from the 194,326 trademark registrations in 2013.

We assign NAICS industry codes to the U.S. registrants in the sample and calculate the industry

share of total registrations, labeling those with an above average share as trademark-intensive.

21 Usingave-yearperiod(inthiscase,years2009–13)insteadofjustoneyearhelpsminimizethechancethatanoma-

lies in any given year will skew our results.

22 Value added and gross output are two alternative gauges of industry size; however, estimates at the level of detail need-

edforthisanalysisarenotavailableduetodatacondentialitylimitations.

23 A detailed discussion of the methodology and a table of results are provided in the Appendix.

24 U.S.PatentandTrademarkOfce2016.Weusethetermtrademarktoencompassbothtradeandservicemarks.

25 These methodologies are discussed in detail in the Appendix.

InellecualProperandheUSconomUpdae 

We combine the results from each approach to form the nal group of trademark-intensive in-

dustries.

e results from these exercises, which are summarized in Tables A-6, are noteworthy in at least

two ways. First, the diversity of the industries listed as trademark-intensive is indicative of both

the spread and intensity of trademark use. Second, we observe signicant consistency across the

three methodologies in the industries designated as trademark-intensive; which provides some

evidence on the validity of these approaches.

For robustness, we also compare the nal group to the industries covered by the companies in In-

terbrand’s listing of Best Global Brands in 2013.

As discussed in the Appendix, these two groups

overlapped signicantly further corroborating our ndings.

Coprighs

e 1976 Copyright Act of the U.S. states that copyright protects “original works for authorship

xed in any tangible medium of expression, now known or later developed, from which they

can be perceived, reproduced, or otherwise communicated, either directly or with the aid of a

machine or device.”

Property Organization’s (WIPO) Guide on Surveying the Economic Contribution of the Copy-

right-based industries and subsequently applied to the U.S. Economy.

As in the 2012 report,

this update uses a narrower denition of copyright-intensive industries than WIPO, focusing

on industries that produce creative works and excluding several industries associated with the

distribution of copyrighted material. We dene copyright-intensive industries as those primarily

responsible for the creation or production of copyrighted materials. is group includes nearly all

industries traditionally associated with production of creative works.

26 Interbrand 2013.

27 17 U.S.C § 102(a).

28 World Intellectual Property Organization 2003. See, for example, Siwek 2009.

29 A more detailed description of our methodology is provided in the Appendix.

InellecualProperandheUSconomUpdae 

IV. IP-Inensie Indusries in he conom

mplomen

Employment in IP-intensive industries totaled 27.9 million in 2014, representing 18.2 percent

of all jobs in the economy (See Figure 1). Since the 2012 report, employment in IP-intensive

industries has generally increased, rising from 27.1 million in 2010. However, due to employ-

ment growth in non-IP-intensive industries, IP-intensive industries account for a slightly lower

overall percentage of U.S. jobs (down from 18.8 percent in 2010). As in the 2012 report, trade-

mark-intensive industries contribute the most to employment. ese industries accounted for

23.7 million jobs in 2014 (up from 22.6 million in 2010), or 85 percent of all IP-intensive jobs (up

from 83 percent in 2010).

to 5.1 million in 2010) followed by patent-intensive industries with 3.9 million jobs (3.8 million

in 2010). Twenty-three of the 81 industries considered in this report were intensive in more than

one form of IP protection. For instance, Audio and Video Equipment Manufacturing (NAICS

3343) is both patent-intensive and trademark-intensive. ese multi-intensity industries account-

ed for 5.5 million jobs (up from 4.5 million jobs for 24 industries in 2010).

3,927

23,741

5,672

27,877

10,000

20,000

30,000

Patent-intensive Trademark-intensive Copyright-intensive IP-intensive

Jobs in thousands

Figure 1. Employment in IP-Intensive Industries, 2014

Source: ESA calculations using data from the Bureau of Labor Statistics' Industry Productivity program.

Note: Estimates include wage and salary employment, the self-employed, and unpaid family workers. Because several industries

were found to be trademark-intensive and patent- or copyright-intensive, total employment in IP-intensive industries is less

than the sum of employment in patent-, trademark-, and copyright-intensive industries.

30 The fact that 66 out of the 81 IP-intensive industries are trademark-intensive industries likely explains why these

industries continue to account for a large majority of IP-intensive industries employment.

31 Because some industries are intensive in more than one form of IP, the sum across the individual groups is larger than

thetotalforIP-intensiveindustries.The5.5milliongurecanbecalculatedbysubtractingoverallIPintensiveem-

ployment from the sum of employment of trademark, patent, and copyright intensive industries.

InellecualProperandheUSconomUpdae 

Self-employed individuals make up a signicant portion of jobs in IP-intensive sectors, partic-

ularly in copyright-intensive industries. Self-employed individuals accounted for 2.4 million

jobs in 2014 (unchanged from 2010); which amounts to 8.5 percent of IP-intensive industries

employment (compared to 8.9 percent in 2010). By contrast, the self-employed share of jobs in

non-IP-intensive industries dropped to 7.2 percent in 2014 from 8.8 percent in 2010

(See Figure 2).

At the individual IP level, the share of self-employed has exhibited relatively small changes since

2010. Trademark-intensive industries increased their share from 7.3 percent in 2010 to 7.6 per-

cent in 2014, while patent- and copyright-intensive industries dropped to 2.0 percent (from 2.2

percent) and 15.4 percent (from 16.5 percent), respectively. e fact that copyright-intensive

industries continue to have the highest self-employment share is not surprising as many jobs

in the creative and performing arts are contract rather than payroll jobs, usually related to the

completion or performance of a specic authored work. However, it should also be noted that

trademark-intensive industries continue to have the largest number of self-employed persons at

1.8 million.

2.0%

7.6%

15.4%

8.5%

7.2%

12%

16%

20%

Patent-intensive Trademark-intensive Copyright-intensive IP-intensive Non-IP-intensive

Figure 2. Self-Employed Share of All Jobs in IP-Intensive Industries, 2014

Source: ESA calculations using data from the Bureau of Labor Statistics' Industry Productivity program.

Note: Estimates show the self-employed and unpaid family workers as a share of all jobs. However, unpaid family workers account for

only about one percent of the combined total of the self-employed and unpaid family workers outside of agriculture.

The IP-intensive bar on the right represents all IP-intensive (patent-, trademark- and copyright-intensive) industries.

InellecualProperandheUSconomUpdae 

Figure 3 shows the trends in employment growth across IP and non-IP-intensive industries over

the past twenty-ve years. As noted in the 2010 report, employment in IP-intensive industries

was nearly the same in 2010 as in 1990 because considerable growth in employment during the

1990s was largely reversed in the 2000s. Since 2010, however, jobs in these industries rebounded.

From 2010 to 2014, IP-intensive industry employment grew 6 percent, driven by trademark and

ing the Financial Crisis, but this may reect the fact that patent-intensive industries are restricted

to manufacturing. Since 2010, employment in non-IP-intensive industries outpaced that of IP-in-

tensive industries by 2 percentage points. As a result, the share of total employment in IP-inten-

sive industries edged down over the past two and half decades from 21.0 percent in 1990 to 20.6

percent in 2000 and 18.2 percent in 2014.

100

120

140

160

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

1990 = 100

Figure 3. Indexed Employment in IP-Intensive Industries, 1990-2014

Non-IP-intensive

IP-intensive

Trademark-intensive

Patent-intensive

Source: ESA calculations using data from the Bureau of Labor Statistics' Industry Productivity program.

oal mplomen Suppored b IP-inensie Indusries

While IP-intensive industries directly accounted for 27.9 million jobs either on their payrolls

or under contract in 2014, they also helped to support an additional 17.6 million jobs in other

(non-IP-intensive) industries that supply them goods and services (i.e. the supply chain). Taken

InellecualProperandheUSconomUpdae 

together, IP-intensive industries directly and indirectly supported 45.5 million jobs, about thirty

percent of all employment.

Figure 4 shows direct employment in IP-intensive industries (medium blue bar) along with in-

direct employment in the supply chain (the rectangle below the blue bar). Indirect employment

increased for all IP-intensive industries with trademark-intensive industries growing the most

since 2010. Trademark-intensive industries indirectly employed 17.3 million jobs in 2014, up

from 13.1 million in 2010. Copyright-intensive industries supported an additional 2.8 million

jobs indirectly in 2014, compared to 2.5 million in 2010. Patent-intensive industries indirectly

supported 3.5 million jobs, up slightly from 3.3 million in 2010.

3,507

17,307

2,809

17,602

3,988

23,741

5,733

27,877

7,495

41,048

8,542

45,478

10,000

20,000

30,000

40,000

50,000

Patent-intensive Trademark-intensive Copyright-intensive IP-intensive

Jobs in Thousands

Figure 4. Total Employment Supported by IP-Intensive Industries, 2014

Total employment

supported by the

IP-intensive industries

Jobs in patent,

trademark, copyright, or

IP-intensive industries

Supply-chain jobs

in other industries

Source: ESA calculations using data from the Bureau of Economic Analysis' Industry Accounts office and the Bureau of

Labor Statistics' Industry Productivity program.

Note: Estimates include wage and salary employment, the self-employed, and unpaid family workers. Because several industries

were found to be trademark-intensive and patent- or copyright-intensive, total employment in IP-intensive industries is less than

the sum of employment in patent-, trademark-, and copyright-intensive industries.

32 These estimates are derived from unpublished input/output tables computed and analyzed by staff from the Bureau

ofEconomicAnalysis’IndustryAccountsofce.DataareconsistentwiththeDecember2010annualrevisiontothe

annualInput-Outputtablesandarebasedonthe2014after-redenitiondomesticmakeandusetablesandestimatesof

theshareof2014employmentattributabletonaldemandinIP-intensiveindustries.Totaloutputrequirementtables

were calculated based on the make and use table following the methodology published in the mathIO.doc, which are

available at www.bea.gov/industry/zip/cxctr2002detail.zip. In the previous report, non-IP employment was calculated

using employment data from BEA. In this update employment measures come from the Bureau of Labor Statistics’

IndustryProductivityprogram:http://www.bls.gov/lpc/lpc_hours_and_employment.xlsx.NAICScodesareconverted

toindustrycodesusing:http://www.bea.gov/industry/xls/GDPbyInd_VA_NAICS_1997–2012.xlsx.

InellecualProperandheUSconomUpdae 

As in the 2012 report, patent-intensive industries rely more heavily on the supply chain as evi-

denced by a larger share of total jobs in indirect employment (47 percent) compared to trade-

mark- and copyright-intensive industries.

In addition to the indirect employment supported through the supply chain, IP-intensive indus-

tries also help support downstream businesses that facilitate the distribution and trade of goods

and services. If one were to include indirect employment in these businesses, total employment

supported by IP-intensive industries would be greater than the 45.5 million jobs mentioned

above.

InellecualProperandheUSconomUpdae 

IP-Inensie Paroll Jobs b Sae

Employment in IP-intensive industries is not evenly distributed across states. Map 1 highlights

those U.S. states that are above the national average in terms of the share of covered employment

in IP-intensive industries.

Eighteen states (up from 16 in 2010) exceeded the national average

of 18.9 percent, which was 19.1 percent in 2010. With a few exceptions, IP-intensive states cluster

in New England, the upper Midwest, and West Coast. is is broadly similar to the distribution

reported in the 2012 report. e top ve states are also similar. In 2014, they were New Hamp-

shire (23.1 percent), Connecticut (23.0 percent), Wisconsin (22.5 percent), Massachusetts (21.9

percent), and Minnesota (21.2 percent). Vermont, which was part of the top ve in 2010, was

replaced by Minnesota.

33 The data used to examine state employment are from the Bureau of Labor Statistics’ Quarterly Census of Employment

and Wages (QCEW) and measure covered employment. Covered employment refers to jobs covered by state and fed-

eral unemployment insurance law, which represent practically all of civilian wage and salary employment. These data

do not include the self-employed or unpaid family workers. For more information on QCEW, see www.bls.gov/cew.

InellecualProperandheUSconomUpdae 

As seen in Map 2, the state distribution for trademark-intensive industries looks like what is ob-

served in Map 1 for all IP-intensive industries. Sixteen of the 18 states with above-average shares

of IP-intensive jobs also had above-average shares of trademark-intensive jobs. is reects the

contribution of trademark-intensive industries to IP-intensive jobs and the fact that 66 of the 81

IP-intensive industries were designated as trademark-intensive. Only Virginia and Oregon do not

show up as trademark-intensive employment states.

InellecualProperandheUSconomUpdae 

In 2014, 23 states had above-average shares of employment in patent-intensive industries, up

from 21 states in 2010 (See Map 3). Texas, Oklahoma, and Kansas were added in 2014 while Ver-

mont was removed. States in New England and the upper Midwest continue to have the highest

shares.

InellecualProperandheUSconomUpdae 

For copyright-intensive industries in 2014, 14 states had above-average employment shares and

11 of these appeared on the 2010 list. Minnesota was removed from the list, while Illinois and

New Hampshire were added. As in the previous report, these states are mostly spread along the

East and West coasts. (See Map 4.)

Overall, ve out of the six states that had above-average employment shares for patent-, trade-

mark-, and copyright-intensive industries in 2010 also did in 2014. ese are California, Con-

necticut, Massachusetts, New Jersey, and Utah. Even more, Oregon and Washington became

IP-intensive states in 2014. e inclusion of Oregon is due to the increased share of its patent-in-

tensive industries while the inclusion of Washington is due to the increased share of its trade-

mark-intensive industries. ese results suggest the use of intellectual property is expanding

geographically.

InellecualProperandheUSconomUpdae 

erage ages

Private wage and salary workers in IP-intensive industries continue to earn signicantly more

than those in non-IP-intensive industries. In 2014, the average weekly wage of $1,312 was 46

percent higher (up from 42 percent in 2010) than for workers in non-IP-intensive industries (See

Figure 5). While workers in non-IP-intensive industries earned $896 per week, those in patent-

and copyright-intensive industries earned $1,560 and $1,701 per week, respectively. At $1,236 per

week, workers in trademark-intensive industries earned less than their counterparts in patent-

and copyright-intensive industries, but still 38 percent more than non-IP-intensive workers.

$1,560

$1,236

$1,701

$1,312

$896

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

$1,800

Patent-intensive Trademark-intensive Copyright-intensive IP-intensive Non-IP-intensive

Figure 5. Average Weekly Wages of Private Wage and Salary Workers in

IP-Intensive Industries, 2014

Source: ESA calculations using data from the Bureau of Labor Statistics' Quarterly Census of Employment and Wages.

InellecualProperandheUSconomUpdae 

Figure 6 plots the trends in wage premiums for workers in IP-intensive industries.

With some

notable volatility, these premiums have generally increased. In the decade aer 1990, the premi-

um for workers in IP-intensive jobs increased from 22 to 38 percent. It lost some ground early in

the 2000s but has been rising steadily since 2002. By 2014, the IP-intensive industry wage pre-

mium stood at 46 percent. e trademark-intensive industry subgroup followed a similar path.

In 1990, trademark-intensive industries paid 19 percent more with this premium climbing to

29 percent by 2000 and 38 percent by 2014. Wages in the patent-intensive industries started at a

45 percent premium and grew through the 1990s before surging up to 69 percent by 2000. is

surge was reversed in 2001 and held fairly at in the last decade before rising again since 2008. In

2014, the average wage premium for patent-intensive workers was 74 percent.

e wage premium in copyright-intensive industries experienced a more extreme version of the

trends discussed above. In 1990, workers in these industries earned 30 percent more than non-IP

intensive industry workers, on average. is premium tripled during the following decade to 88

percent by 1999. Over the next ve years, it decreased to 63 percent before growing again to 90

percent by 2014. e wage premium for all four sets of industries was higher in 2014 than at any

point over the prior 24 years.

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Figure 6. Average Weekly Wage Premium of Workers in IP-Intensive

Industries Relative to Non-IP-Intensive Industries, 1990-2014

IP-intensive

Patent-intensive

Trademark-intensive

Source: ESA calculations using data from the Bureau of Labor Statistics' Quarterly Census of Employment and Wages.

34 The wage premium measures the percentage difference between the wages of workers in IP-intensive industries versus

those in non-IP-intensive industries. It is a premium because average weekly wages are higher in IP-intensive indus-

tries.

InellecualProperandheUSconomUpdae 

ducaion

In competitive labor markets, wages are closely correlated to worker productivity, and education-

al attainment is a common gauge of workers’ skill and expected productivity. us, we expect

employees in IP-intensive industries to have relatively high educational attainment. e 2010

data were consistent with this hypothesis as 42.4 percent of workers age 25 and older in IP-inten-

sive industries had a bachelor’s degree or higher, compared with 34.2 percent in private non-IP

intensive industries.

However, data from the 2015 Current Population Survey show this edu-

cation gap virtually disappeared (See Figure 7). e share of workers in IP-intensive industries

with a bachelor’s degree or higher fell to 39.8 percent in 2015, whereas that percentage increased

to 38.9 percent for workers in non-IP-intensive industries. Besides the increase in educational

attainment among workers in non-IP-intensive industries, trademark-intensive industries con-

tributed to the narrowing of the educational attainment gap. In 2015, the share of workers with

college education or higher in trademark-intensive industries fell to 36.6 percent (from 38.8

percent in 2010). By contrast, this share increased to 66.4 percent (from 61.2 percent in 2010) for

tries.

5.6

8.6

1.6

7.8

7.7

25.0

27.5

10.3

25.7

27.6

27.4

21.7

26.7

27.7

27.2

25.7

45.7

27.7

23.8

14.5

10.9

20.7

12.1

15.1

20%

40%

60%

80%

100%

Patent-intensive Trademark -intensive Copyright-intensive IP-intensive Non-IP-intensive

Figure 7. Distribution of Employed Persons in IP-Intensive Industries

by Educational Attainment, 2015

Graduate

degree

Bachelor's

degree

Some college or

associate

degree

High school

diploma

Less than high

school

Source: Current Population Survey, 2015, Public Use Microdata Files and ESA calculations. Estimates are for employed persons age 25 and over.

35 These estimates are calculated from 2010 and 2015 Current Population Survey public-use microdata, as accessed

through the Census Bureau’s DataFerrett tool at dataferrett.census.gov.

InellecualProperandheUSconomUpdae 

As was the case in 2010, workers in copyright-intensive industries were the most educated of the

three IP-intensive segments in 2015 with 20.7 percent having attained a graduate degree, and

only 1.6 percent having less than a high school diploma. e share of workers in patent-intensive

industries with at least a bachelor’s degree was smaller, at 41.7 percent, but still higher than the

share for non-IP-intensive industries. In trademark-intensive industries, however, the share of

workers with a college or higher degree fell below that of the non-IP-intensive industries by 2015.

alue added

While jobs in IP-intensive industries increased between 2010 and 2014, jobs in non-IP-intensive

industries grew at a slightly faster pace. Consequently, the proportion of total employment in

IP-intensive industries actually declined to 18.2 percent from18.8 percent in 2010. (See Figure

8) In contrast, the value added by IP-intensive industries increased substantially in total amount

and as a share of GDP between 2010 and 2014. IP-intensive industries accounted for $6.6 trillion

in value added in 2014, up more than $1.5 trillion (30 percent) from $5.06 trillion in 2010. Ac-

cordingly, the share of total U.S. GDP attributable to IP-intensive industries increased from 34.8

percent in 2010 to 38.2 percent in 2014.

Trademark- and copyright-intensive industries appear to be driving the recent growth in value

added. Between 2010 and 2014, the share of GDP attributed to trademark- and copyright-inten-

sive industries increased to 34.9 percent (from 30.8 percent) and 5.5 percent (from 4.4 percent),

respectively. Trademark-intensive industries alone accounted for $6.1 trillion in value added in

2014 (up from $4.5 trillion in 2010). e value added by patent-intensive industries increased

from $763 to $881 billion between 2010 and 2014. However, because this growth trailed the other

IP-intensive segments, the share of GDP attributable to patent-intensive industries declined from

5.3 percent to 5.1 by 2014.

InellecualProperandheUSconomUpdae 

5.1%

34.9%

5.5%

38.2%

61.8%

2.6%

15.5%

3.7%

18.2%

81.8%

15%

30%

45%

60%

75%

90%

Patent-intensive Trademark intensive Copyright intensive IP-intensive Non-IP-intensive

Figure 8. Value Added and Employment Shares of IP-Intensive Industries, 2014

Source: ESA calculations using data from the Bureau of Economic Analysis, National Income and Product Accounts and

the Bureau of Labor Statistics' Industry Productivity program.

Share of employment

Share of GDP

IP eenue

Up to this point, IP-intensity was dened based on the counts of patents, trademarks and copy-

rights per employee at the industry level. While this method adjusts total IP holdings for dier-

ences in industry size, it does not directly measure the revenue associated with using intellectual

property. Using revenue to dene IP-intensity is more restrictive because it requires rights hold-

ers to attribute some portion of total revenue directly to IP holdings, which is dicult due to the

intangible nature of IP assets. Ideally, information would be available on the full revenue stream

attributable to an industry’s intellectual property which would include both the measurable and

unmeasurable contributions of IP. With this information, an alternative IP-intensity metric could

be dened as total IP revenue or IP revenue as a share of total revenue, which is another way to

adjust for industry size.

Although comprehensive information of this type do not exist, the Economic Census of U.S.

business establishments does provide some data on measureable revenues associated with licens-

ing, royalties, and other forms of trade of intellectual property. e Economic Census, which is

conducted every ve years by the U.S. Census Bureau, asks companies to report sales by specic

InellecualProperandheUSconomUpdae 

product lines.

Ninety-one of these product lines were identied as related to IP.

Revenue for

each of the 91 product lines were summed and used to dene an IP-intensity metric based on the

ratio of IP revenue to total revenue at the industry level.

Table 1 shows the 29 four-digit NAICS industries that had some IP-related revenue, ranked by

the IP share of total revenue in 2012. e distribution of IP-related revenue was fairly concen-

trated. Six industries had IP revenue shares above the 11.3 percent average (among industries

for which the Economic Census collected IP-related revenue), and these industries accounted for

about 82 percent of total revenue from IP-related products. All six industries were also identied

as IP-intensive using the IP counts per employee metric.

Overall, 15 of the 29 industries with any IP revenue in 2012 were also classied as IP-intensive

using the IP counts per employee metric. Of the 14 industries that were not previously classied,

ve were in the “other services (except public administration)” sector, four were in the arts, en-

tertainment, and recreation sector, four were in the professional, scientic and technical services

sector, and one was in the information sector.

36 TheEconomicCensusistheU.S.Government’sofcialve-yearmeasureofAmericanbusinessandtheeconomy.It

isconductedbytheU.S.CensusBureauandresponseisrequiredbylaw.Thelatestcensuswascompletedin2012.In

October through December 2012, forms were sent out to nearly 4 million businesses, including large, medium and

small companies representing all U.S. locations and industries. Respondents were asked to provide a range of oper-

ational and performance data for their companies. To learn more about the Economic Census, please see http://www.

census.gov/econ/census/.

 TheindustryclassicationsforallestablishmentscoveredbytheeconomiccensusandsurveysarebasedontheNorth

AmericanIndustryClassicationSystem(NAICS).FormoreonIndustryClassicationofEstablishments:

http://www.census.gov/econ/census/help/naics_other_classication_systems/industry_classication_of_establishments.html.

37 Table A-11 in the appendix provides a complete list of these codes.

InellecualProperandheUSconomUpdae 

able 1. Indusries ih IP-elaed eenue, aned b IP eenue Inensi, 01

NICS

code

IP-

inensie

Indusr ile

IP-relaed

reenue

$millions

Cumulaie

IP-reenue

inensi

IP/oal

reenue

 

Moionpicureandideo

indusries   

 

essorsononnancialinangible

asses   

 

Independenarissriersand

perormers   

  Soundrecordingindusries   

 

Cableandohersubscripion

programming   

  Perormingarscompanies   



gensandmanagersorpublic

gures   

  Oherinormaionserices   



Promoersoperormingars

sporsandsimilareens   

 Specaorspors   

  adioandeleisionbroadcasing   



Proessionalandsimilar

organiaions   

 

Nespaperperiodicalbooand

direcorpublishers   

  Soarepublishers   



Businessschoolsandcompuer

andmanagemenraining   



Managemenocompaniesand

enerprises   

 egalserices   

 Socialadocacorganiaions   

 

Compuerssemsdesignand

relaedserices   

 

Oherproessionalscienicand

echnicalserices   

  Ciicandsocialorganiaions   

Above mean + 1 std. dev.

Above mean

InellecualProperandheUSconomUpdae 

 

derisingpublicrelaionsand

relaedserices   



Museumshisoricalsiesand

similarinsiuions   



rchiecuralengineeringand

relaedserices   

 ran-maingandgiingserices   

  Oherelecommunicaions   

 Oherpersonalserices   

 

iredelecommunicaions

carriers   

oal

ll indusries ih

IP-relaed reenue 1,684 100.0 11.

Note: Intensity measure is the percent of overall revenue generated for each four-digit NAICS industry from the licensing of

intellectual property protected assets.

Source: ESA calculations using data from the Census Bureau’s 2012 Economic Census.

e product line codes in the Economic Census can also be grouped into those that explicitly

mention IP licensing as the source of revenue. As shown in Table 2, revenue specic to the licens-

ing of IP rights totaled $115.2 billion in 2012, with 28 industries deriving revenues from licens-

ing. Among these industries, the motion picture and video industry generated the largest reve-

nue, $41.6 billion in 2012, followed by the cable and other subscription industry and the lessors

of nonnancial intangible assets industry. Not only do these three industries account for nearly

78 percent of all reported direct revenues from IP licensing, they also have the largest shares of

licensing revenue, averaging 50.7 percent of total revenue.

able . IP-licensing eenue b Indusr, 01

NICS code

and indusr ile

IP-licensing reenue

$millions

Share o oal reenue 

oal  

-Moionpicureandideoindusries  

-Cableandohersubscripionprogramming  

-essorsononnancialinangibleasses  

-Oherinormaionserices  

-Scienicresearchanddeelopmen

serices  

-Soundrecordingindusries  

-adioandeleisionbroadcasing  

-Proessionalandsimilarorganiaions  

-Soarepublishers  

-Independenarissriersand

perormers  

InellecualProperandheUSconomUpdae 

-Nespaperperiodicalbooanddirecor

publishers  

-Compuerssemsdesignandrelaed

serices  

-Managemenocompaniesandenerprises  

-Specaorspors  

-gensandmanagersorpublicgures  

-rchiecuralengineeringandrelaed

serices  

-Perormingarscompanies  

-Promoersoperormingarssporsand

similareens  

-derisingpublicrelaionsandrelaed

serices  

-Oherproessionalscienicandechnical

serices  

-ran-maingandgiingserices  

-Businessschoolsandcompuerand

managemenraining  

-Socialadocacorganiaions  

-Ciicandsocialorganiaions  

-iredelecommunicaionscarriers  

-Museumshisoricalsiesandsimilar

insiuions  

-Oherelecommunicaions  

-Oherpersonalserices  

Source: U.S. Census Bureau, 2012 Economic Census

oreign rade

Once again using IP counts per employee to group industries, IP-intensive industries continue to

account for a signicant share of U.S. exports and imports. Total merchandise exports increased

from $775 to $842 billion between 2010 and 2014. However, because exports from non-IP-inten-

sive industries increased at a faster pace, the share of total merchandise exports from IP-intensive

industries declined to 52 percent in 2014 from 60 percent in 2010. e value of merchandise im-

ports into IP-intensive industries totaled $1,391 billion in 2014, which is largely unchanged from

2010, but fell as a percent of overall U.S. merchandise imports from 69.9 to 59.3 percent between

2010 and 2014.

e breakdown of exports by industry for 2014 is very similar to that for 2010. Manufacturing

industries accounted for 96 percent of merchandise exports from IP-intensive industries in 2014,

compared to 99 percent in 2010. Oil and gas extraction and nonmetallic minerals sectors account-

ed for the rest in both years. Within manufacturing, exports from the basic chemicals sector led

InellecualProperandheUSconomUpdae 

the way, increasing from $58.4 to $64.5 billion between 2010 and 2014. Exports from the semi-

conductors and other electronic components sector, which topped the chart at $64.0 billion in 2010,

fell to $54.8 billion in 2014. (See Figure 9)

$27.1

$29.8

$30.3

$32.6

$37.0

$39.1

$39.2

$39.8

$40.5

$49.1

$49.3

$50.8

$54.5

$54.8

$64.5

$0 $10 $20 $30 $40 $50 $60 $70

Other Electrical Equip & Components

Oil & Gas

Engines, Turbines & Power Transmsn Equip

Medical Equip & Supplies

Nonferrous (exc Alum) & Processing

Ag & Construction & Machinery

Other General Purpose Machinery

Resin, Syn Rubber, Artf & Syn Fibers/fil

Communications Equipment

Computer Equipment

Misc Manufactured Commodities

Navigational/measuring/medical Instrument

Pharmaceuticals & Medicines

Semiconductors & Electronic Components

Basic Chemicals

Figure 9. Merchandise Exports of Selected IP-Intensive Industries, 2014

Billions of current dollars

Source: ESA

calculations

using data from the Census Bureau's Foreign Trade Division.

Note: The selected industries accounted for 76.5 percent of merchandise exports of IP-intensive industries.

Data on trade in services are more limited. However, using the latest Economic Census data, we

obtained detailed accounting of service exports for 2012. We nd that exports of service-provid-

ing IP-intensive industries totaled about $81 billion in 2012 (compared to $90 billion in 2007).

is accounted for 12.3 percent (compared to 19 percent in 2007) of total U.S. private exports in

services. As shown in Figure 10, exports of soware publishers totaled $22.7 billion and continue

to be the largest group of service exports. However, export by the portfolio management indus-

try, totaling $13.6 billion in 2012, replaced the motion picture and video industry for the second

place compared to the 2007 rankings. e latter went down from $15.3 billion in exports in 2007

to $7.3 billion in 2012 and appears to account for a substantial part of the decline in exports of

service-providing IP-intensive industries. Other major services export categories in 2012 includ-

ed computer system design ($7.8 billion), motion picture and video production ($7.3 billion),

management & technical consulting ($7.1 billion), and wired telecommunications carriers ($5.2

billion).

InellecualProperandheUSconomUpdae 

$7.7

$1.4

$1.6

$2.9

$3.3

$5.2

$7.1

$7.3

$7.8

$13.6

$22.7

$0 $5 $10 $15 $20 $25

Other

Machinery and equip rental & leasing

Other telecommunications

Newspaper, book, & directory

Other information services

Wired telecommunications carriers

Manage't, scientific, & tech consult svcs

Motion picture and video production

Computer systems design & related svcs

Portfolio management

Software publishers

Figure 10. Exports of IP-Intensive Service-Providing Industries, 2012

Billions of current dollars

Source: ESA calculationsusing data from the Census Bureau's 2012 EconomicCensus.

InellecualProperandheUSconomUpdae 

V. Conclusion

e 2012 report Intellectual Property and the U.S. Economy: Industries in Focus identied IP-in-

tensive industries and quantied their contribution to the U.S. economy. It found that in 2010

IP-intensive industries supported over 40 million jobs and accounted for about $5.06 trillion in

value added; equivalent to 34.8 percent of U.S. GDP. e current report provides updated results

demonstrating that IP-intensive industries supported 45.5 million jobs and contributed $6.6

trillion in value added in 2014, equivalent to 38.2 percent of U.S. GDP. In addition, the current

report reinforces the earlier nding that IP use permeates all aspects of the economy with in-

creasing intensity and extends to all parts of the U.S.

Besides data on the prevalence of IP, policy makers are interested in learning more about how

eectively it is used to stimulate economic activity. However, understanding the eectiveness and

benets of IP use requires an understanding of the value that IP owners attribute to their assets,

and how that value translates into incentives for the creation of new goods and services. While an

expansive welfare analysis of IP is beyond the scope of this report, evidence that informs such an

analysis is an important direction for future work.

With more granular data that connects inventors and rms of various types with IP assets, we

could start to answer a variety of questions about the distinct functions of IP in the economy. In

particular, policy makers would benet from research on whether IP users seek IP protection to

facilitate nancial investment in innovation, to support entrepreneurial liquidity, or to enable

technology transfer, and the extent to which these advantages stimulate inventive activity. Under-

standing the role of IP in the performance of diversely situated rms and in the economy overall

requires the application of a variety of methodologies and persistent eorts, many of which are

already underway.

InellecualProperandheUSconomUpdae 

ppendi

In this Appendix, we provide a detailed discussion of the methodologies used to designate IP-in-

tensive industries for each of the three IP types (i.e. patents, trademarks, and copyrights). e

methodologies follow very closely what was applied in the 2012 report. We also provide a table of

the IP related product codes from the Economic Census which were discussed in the Section IV

under IP revenue.

Paens

Patents are classied in over 450 patent “technology classes” that distinguish their inventive

content.

Additionally, the USPTO maintains a general concordance between its technology

classications and 30 North America Industry Classication (NAICS) codes (26 unique codes

and 4 combinations), which enables analysts to associate patents with these industries.

We rely

on these NAICS-based patent counts for 2009 to 2013 to identify patent-intensive industries.

Just as a patent can be assigned to more than one technology class, it also may be associated with

multiple industries. Because no similar concordances to NAICS are available for plant or design

patents, only utility patents are used in our analysis.

is approach strictly limits the patent

analysis to the manufacturing sector because the concordance system only associates patents

with manufacturing industries. Service-providing industries may also rely on utility patents in

their production processes, but these industries are not captured by the patent-NAICS concor-

dance we employ.

racional s. hole Paens Couns

e USPTO reports patent data by NAICS category using two dierent counting measures. e

rst gives one full count to every industry with which a particular patent is associated. e sec-

ond divides each patent by the number of industries it is associated with, thus creating fractional

counts of patents. e sum of the fractional counts equals the total number of patents issued

in a given year, while the sum of the whole counts across industries is greater than the number

of patents issued. Patent analyses within a given industry or technology class commonly use

whole counts; however, cross-industry analyses typically use fractional counts in order to avoid

over-counting. For these same reasons, fractional counts are used in this report.

It is important

to note that the NAICS concordance maintained by the USPTO associated each patent with its

38 Utilitypatentsmaybeclassiedintomorethanonetechnologyclassbutareorganizedaccordingtotheirprimaryclas-

sication.

39 ThisconcordancewascreatedbytheUSPTOwithnancialsupportfromtheNationalScienceFoundation.Foran

overview of NAICS, see www.census.gov/eos/www/naics/index.html.

40 Seewww.uspto.gov/web/ofces/ac/ido/oeip/taf/data/misc/patenting_trends/info_ptrends2008.txt.

41 To contrast the scale of technology patents, design patents break out into 33 classes and plants have only one patent

class.Seewww.uspto.gov/web/ofces/ac/ido/oeip/taf/all_tech.htmformoreinformationonutilitypatents.

42 It should be noted that the use of fractional patent counts differs from our treatment of trademarks registrations for

which only whole counts of registrations by class are available.

InellecualProperandheUSconomUpdae 

nal use in the economy. In practice, this means that the patents are all associated with manufac-

turing NAICS codes regardless of whether the company that owns them is a manufacturer or a

company that may be classied in the services sector.

Mehodolog

Using the USPTO maintained concordance, we calculate a measure of industry patent “intensity,”

dened as the ratio of total patents over the ve years (2009–2013) in a NAICS category to the

average payroll employment by industry. Because employment is a gauge of industry size, divid-

ing patent counts by employment normalizes patenting activity with respect to industry size.

is approach helps put all industries on an even playing eld, so that the most patent-intensive

industries are dened not as the ones with the most patents, but rather those with the most pat-

ents per worker.

By using a ve-year period (in this case, years 2009–13) instead of just one year helps minimize

the chance that anomalies in any given year will skew our results. e analysis was performed

at the highest possible level of NAICS industry detail, and so results include four-digit indus-

tries as well as some individual three-digit industries and combinations of three- or four-digit

industries.

As shown in Table A-1, most patent-intensive industries in the sample fall into the

four-digit NAICS industries, which may be a product of the patent-intensive nature of these

more nely disaggregated industry sectors.

43 Forfulldetailsonthenatureandcaveatsofthepatentdataused,seewww.uspto.gov/web/ofces/ac/ido/oeip/taf/govt/

naics/explan_naics.htm.

44 Value added and gross output are two alternative gauges of industry size. However, estimates at the level of detail

neededforthisanalysisarenotavailableduetodatacondentialitylimitations.

45 IntheNAICSclassication,athree-digitcodeisalargeraggregationascomparedtoafour-digitcode.So,forinstance,

NAICS 236 “construction of buildings” is a larger aggregation of which NAICS 2361 “residential building construc-

tion”isasmallerandmorespecicsubset.

InellecualProperandheUSconomUpdae 

able -1. Paen Inensi, 009–1

NICS code Indusr ile

Paens

number

mplomen

1000 jobs

Paen

Inensi

paens/1000

jobs

 Compuerandperipheralequipmen   

 Communicaionsequipmen   

-

Ohercompuerandelecronic

producs   



Naigaionalmeasuring

elecromedicalandconrol

Insrumens   



Semiconducorsandoher

elecroniccomponens   

 Basicchemicals   

 Ohermiscellaneous   



lecricalequipmenappliances

andcomponens   

 Medicalequipmenandsupplies   

 Pharmaceuicalandmedicines   

---

Oherchemicalproducand

preparaion   

 Machiner    Above Mean



esinsnheicrubberandaricial

andsnheicbersandlamens   

 Plasicsandrubberproducs   

 abricaedmealproducs   

-- Oherransporaionequipmen   

-- Moorehiclesrailersandpars   

 Nonmeallicmineralproducs   

--- eilesapparelandleaher   

 erospaceproducandpars   

 urniureandrelaedproducs   

 Primarmeal   

 oodproducs   

-

Paperpriningandsuppor

aciiies   

 Beerageandobaccoproducs   

 ood   

oal  488 10.0 46.0

Source: USPTO calculations using the agency’s patent data and the Bureau of Labor Statistics’ Industry Productivity program.

Note: Patent intensity is dened as the ratio of patents to employment and is measured in patents/thousand jobs.

InellecualProperandheUSconomUpdae 

rademars

Unlike patents, there is little academic research examining industry use of trademarks. e 2012

report oered what may be the rst comprehensive analysis of trademark use by U.S. industries

that is grounded in original research, data, and measurement theory. e methodology applied

in the current report and detailed below is derived from what was designed in the 2012 report.

As a preliminary matter, we recognized that each trademark registration has a description of the

type of good or service with which the protected mark is used in commerce. e USPTO classi-

es goods and services for administrative convenience, and applicants for trademark registration

must provide a separate description — and pay separate application and maintenance fees — for

each “class” in which the goods or services associated with the trademark is classied.

is

makes working with trademark registration data dierent from working with patent grant data.

Trademark application and maintenance fees are assessed on a per-class basis, and registration

holders may elect to renew their registrations with respect to some but not all classes.

As a

result, holding a “multi-class” registration is practically equivalent to holding multiple registra-

tions, one for each class. Accordingly, in the foregoing analysis each class listed on a registration

was considered as the unit of analysis, creating a class-registration count. For example, if one

mark (or logo) is registered in three classes,

then our input measure in the analysis reects three

trademark registration counts, one for each class.

e approach that we adopted for measuring trademark-intensive industries parallels, but diers

from, the approach employed when analyzing patents. For patents, each patent was counted only

once overall; for trademark measurements, each mark is counted once for each class in which

it belongs, potentially counting it more than once overall according to the number of classes in

which it is registered. Since it is not easy to ascertain which trademarks are relatively more im-

portant, we use the best measure available, based on the economic realities of the fee system.

Because each trademark registration-class involves some xed ling fee paid to the USPTO, the

more classes in which a trademark is registered indicate more times that a fee has been paid to

the USPTO. Using these fee-payments is an eective method to base an IP-intensity measure and

this approach was followed consistently for both trademarks and patents.

46 For a list of classes, see Trademark Manual of Examining Procedure (TMEP) chapter 1400 (April 2016 edition). Fees

also are a function of the type of application form used. For more information on the trademarking process, see Trade-

mark Basicsatwww.uspto.gov/trademarks/basics/BasicFacts_with_correct_links.pdf.

47 Each class used to group the goods or services in a registration for purposes of administrative fee payments may cover

a wide variety of goods or services. A trademark right exists as to each good or service on or in connection with which

themarkisused.Theclassicationofthegoodsandservicesdoesnotdeterminethescopeoftheprotectiongiventoa

mark.

48 Anexampleisthemark“Nike”beingregisteredinclassesassociatedwith(a)software,(b)golfequipment,and(c)

eyewear. See U.S. trademark registration numbers 3406594, 3389746, and 3081688, each by Nike, Inc.

49 Wecouldweightcompaniesbynumberofemployees,butitismoredifculttodecidewhetheragiventrademark

taken by itself should be weighted heavily or lightly.

InellecualProperandheUSconomUpdae 

Because trademark registrations can be segmented by class but not by industry, there is no

USPTO NAICS concordance for these data. Due to this methodological limitation, there is no

single, straightforward way to tabulate registrations and measure trademark intensity by indus-

try. Accordingly, and because the measurement of trademark use is a new science, we opted for

over-inclusiveness and developed a three-pronged approach to identifying trademark-intensive

industries.

We relied on three related but distinct approaches, using dierent samples of companies that have

registered USPTO trademarks. e rst approach is the closest approximation to the methodolo-

gy used to identify patent-intensive industries. Starting with the complete set of trademark regis-

trations, we matched publicly traded companies by their name to a separate database containing

information on the rms’ primary industry and number of employees. ese data allowed us

to calculate trademark intensity by industry for the matched rms. In the second approach, we

reviewed lists of the top 50 corporate trademark registrants published by the USPTO (which, un-

like the rst approach, include both private and public companies) and identied industries that

appear repeatedly. To help moderate the tendency of the rst two approaches to under-represent

smaller and younger rms, our third approach took a representative and random sample of rms

drawn from the complete database of U.S. corporate trademark registrations from 2009 to 2013.

rademar Inensi

Mehodolog 1

Like our method for dening patent intensity, we dene trademark intensity as the ratio of trade-

mark registrations to employment in a given industry. us, we are measuring the number of

trademark registrations per employee. e USPTO applied a rm-name standardization rou-

tine developed originally for patent analysis in order to match companies with new trademark

registrations to companies in Compustat’s database of nancial statements of publicly traded

companies.

is matching identied 507,008 distinct standardized rm names in the 2009–13

trademark registration and trademark renewal records. ese were rms that either registered

or renewed at least one trademark from 2009 to 2013. We merged these records with 9531 stan-

dardized parent-company records drawn from the Compustat database. Successful matches were

made for 3094 rms. Since Compustat records also include NAICS codes, we were able to sum

trademark registrations and employment by four-digit NAICS industry and then estimate indus-

try trademark intensity as the number of matched rm trademarks per worker in each industry.

Because Compustat does not record the relationships between parent and subsidiary companies,

the identities of trademark registrants were only matched to the name of the publicly traded

50 This methodology has previously been applied in studies of patents, particularly as detailed in Hall, Jaffe, and Trajten-

berg 2001. This paper and other supporting documentation are available at www.nber.org/patents/.

51 TotheextentthatmatchedrmsdifferintheirFederaltrademarkregistrationbehaviorrelativetounmatchedrms,

these trademark intensities are biased. However, what really matters for our analysis is not whether the estimates are

individually biased but rather if any bias varies across industries.

InellecualProperandheUSconomUpdae 

parent company reporting nancial statements to the U.S. government. Accordingly, trademarks

registered in the name of subsidiaries that have dierent names than the parent company were

not matched by our method.

Table A-3 provides the designation of trademark-intensive industries for years 2009–2013 us-

ing the rst of the three methodologies. While there are notable dierences, there is signicant

overlap between the industries in this list compared to the one in the 2012 report covering

years 2004–2008. ere are two main sources of dierences. First, while the methodology is the

same in both cases, a more exhaustive data cleaning process in the current report led to a more

comprehensive coverage of rms with trademark registration that were assigned to an industry.

Secondly, an industry is added to the data as trademark-intensive only if there are at least ve

rms identied that belong to it. us, a single additional rm can determine whether an indus-

try is designated as trademark-intensive. Although unlikely, this could signicantly impact the

rank-order of some industries. For example, while land subdivision (NAICS 2372) did not make

it in the list of trademark-intensive industries in the previous report, it is on the top of the cur-

rent list as presented in Table A-3 below. Despite these dierences, we again nd signicant con-

sistency across the two periods as over 65 percent of the industries designated as trademark-in-

tensive in the 2012 report are also included in the current list.

able -. Indusries ih boe-erage rademar Inensi, 009–1

Naics

Code Indusr ile

rademar

Inensi

rademars/1000

orers 

Naics

Code Indusr ile

rademar

Inensi

rademars/1000

orers

 andsubdiision   

Householdand

insiuionalurniure

andichencabines 



Oherinesmen

poolsandunds   

Oupaiencare

ceners 



Ohermiscellaneous

manuacuring   

Commercial

equipmen 



udioandideo

equipmen

manuacuring   

ooear

manuacuring 



lecriclighing

equipmen   

Nonmeallicmineral

miningandquarring 

 Oheroodproducs    essorsorealesae 



Oherinormaion

serices    Oilandgaseracion 

52 For this reason, this method not only tends to overweight large, publicly traded companies, but also those companies

that have a particular trademark-registration approach. Which is consistent with patent scholarship suggesting that IP

ownershipmayshowsystematicdifferencesalongthesedimensions.SeeAroraetal.2011,29–30.

InellecualProperandheUSconomUpdae 



lecronicshopping

andmail-order

houses    Basicchemicals 



Securiiesand

commodi

echanges   

Priningandrelaed

supporaciiies 



Nespaper

periodicalbooand

direcorpublishers   

Managemenand

echnicalconsuling

serices 



Oherambulaor

healhcareserices   

Nonerrousmeal

ecepaluminum

producionand

processing 



Ohernonmeallic

mineralproducs    Dairproducs 



essorso

nonnancial

inangibleasses

ecepcoprighed

ors    Insurancecarriers 



ciiiesrelaedo

crediinermediaion   

ired

elecommunicaions

carriers 

 Soarepublishers   

Nauralgas

disribuion 

 Indusrialmachiner   

Ohersuppor

serices 

 amblingindusries   

lecricaland

elecronicgoods 



adioandeleision

broadcasing   

Commercialand

sericeindusr

machiner 



Medicalequipmen

andsupplies   

lecronic

insrumens 



Oherelecrical

equipmenand

componens   

esinsnheic

rubberandaricial

snheicbersand

lamens 



Pharmaceuicalsand

medicine    Plasicsproducs 



Soapscleaning

compoundsand

oilepreparaions   

ruiandegeable

preseringand

specialood 

InellecualProperandheUSconomUpdae 



reighransporaion

arrangemen   

Oherproessional

andechnical

serices 



Pesicideseriliers

andoheragriculural

chemicals   

esidenialbuilding

consrucion 



derisingand

relaedserices   

Ohergeneral

purposemachiner 



rocerandrelaed

producs   

Moionpicureand

ideoindusries 



Oherransporaion

equipmen   

Cableandoher

subscripion

programming 



Oher

elecommunicaions   

Medicaland

diagnosic

laboraories 



Ohernancial

inesmenaciiies    Beerages 



Machinerand

equipmenrenaland

leasing   

ngineurbineand

poerransmission

equipmen 



Communicaions

equipmen   

Poergeneraionand

suppl 

Source: USPTO calculations using the agency’s trademark registration data and company employment data from Compustat.

op 0 rademar egisering Companies

Mehodolog 

Since 2006, the USPTO’s annual Fiscal Year Performance and Accountability Reports have iden-

tied the 50 companies that obtained the largest number of trademark registrations during the

Federal scal year (FY) pertaining to that report.

Because these reports do not provide the pri-

mary NAICS code of the companies in question, we used Avention and Manta to determine the

relevant NAICS industry classication for each of the companies listed for FY 2009–13.

On the

theory that these large companies operate in industries with large numbers of trademark registra-

tions relative to the size of the industry, those industries were dened as trademark-intensive.

53 See www.uspto.gov/about/stratplan/ar/index.jsp to access the annual “Performance and Accountability Reports.” In

each report, the Top 50 Trademark Registrants tables are Table 29B or 30B within the USPTO Workload Tables in

Section 5, “Other Accompanying Information.” The most recent list of Top 50 trademark registrants is for FY2015.

54 WeusedbothAventionandMantaNAICSclassicationofindividualrms.IfonlyoneofthesesourcesprovideaNA-

ICScodefortherm,werecordthatNAICSastheappropriateclassication.Ifthereisamismatchbetweenthetwo

sources,weresearchedtherm’slineofbusinessusingInternetsearchesandidentiedwhichofthetwogaveamore

appropriateclassication.Ifneitherhaveappropriateclassication,thermisnotincludedinthesample.

InellecualProperandheUSconomUpdae 

Aer assigning each company to a four-digit NAICS industry, we tabulated the number of times

companies within each industry appeared in the top 50 during the FY 2009–13 period. We des-

ignated industries with counts of ve or larger as trademark-intensive. At the extremes, counts

of ve or higher occurred if a given company was among the top 50 registrants in each of the ve

years studied, or if ve dierent companies in an industry had reached the top 50 in a single year

during the period.

e results are provided in Table A-4. Only three industries are missing from the list of trade-

mark-intensive industries listed in Table A-3. ese are grocery stores (NAICS 4451), sugar con-

fectionery product manufacturing (NAICS 3113), and department Stores (NAICS 4521).

able -4. Indusries ih ie or More ppearances in he isings o

op 0 rademar egisering Companies, 009–1

NICS

Code Indusr ile

Number o op 0

ppearances

 Ohermiscellaneousmanuacuring 

 Pharmaceuicalandmedicinemanuacuring 

 Soapcleaningcompoundandoilepreparaionmanuacuring 

 Moionpicureandideoindusries 

 adioandeleisionbroadcasing 

 udioandideoequipmenmanuacuring 

 amblingindusries 

 rocersores 

 Insurancecarriers 

 Sugarandconecionerproducmanuacuring 

 Deparmensores 

Source: USPTO calculations using data from the USPTO’s Annual Performance and Accountability Report, Avention, Manta,

and Internet searches.

andom Sample o ll rademar egisraions

Mehodolog 

One shortcoming of identifying industries based on the trademark intensity or top 50 appear-

ances is that these approaches tend to bias selection toward larger companies that register a

greater number of trademarks.

Moreover, these approaches can fail to account for the critical

importance that single trademarks may hold for large entities (for instance, Coca-Cola so drink

or Apple personal computer) or of dierences in industry composition and concentration. Ac-

cordingly, those methods will miss industries composed of smaller companies that may account

for many trademarks as a group but do not otherwise fall in the USPTO top 50 listing. To help

55 Note that many small companies use trademarks but, for various reasons, do not seek Federal registration. Yet they still

have rights in those marks under common law.

InellecualProperandheUSconomUpdae 

overcome this shortcoming, we supplemented our analyses with a random sample of registrants

drawn from the universe of all 194,326 trademarks registered in 2013. ese data were generated

by the USPTO using publicly available source data.

To measure the industry share of total regis-

tered trademarks, a random sample of 300 registrations was drawn from this dataset. U.S. com-

panies were listed as the registrant on 247 of these 300 trademark registrations.

We assigned

four-digit NAICS industry codes to these U.S. rms using the same procedure employed for the

top 50 corporate registrants.

Table A-5 lists those industries that were two standard deviations

above the mean in the number of companies that were associated with them. e only addition-

al industry that was identied as trademark-intensive using this methodology is civic and social

organizations (NAICS 8134).

able -. Percen Disribuion o rademar egisraions o Seleced Indusries rom

Sample o U.S.-Oned, rademar-egisran Companies, aned b Percen, 01

NICS code Indusr ile Percen

 Ohermiscellaneousmanuacuring 

 derisingandrelaedserices 

 Nespaperperiodicalbooanddirecorpublishers 

 Ciicandsocialorganiaions 

 Medicalequipmenandsupplies 

 Commercialequipmen 

Source: USPTO calculations using the agency’s trademark registration data.

One limitation of this approach is that the sample was drawn from records that pertain to only a

single year. is may result in the under-identication of industries that generally register fre-

quently in an average year, but, for some reason, were less active in 2013 (which may not be a

representative year). e sample size is another important limitation. e sample we used was

small because assigning NAICS codes to each company requires the use of many resources. In an

ideal data world, the USPTO trademark registry would include each corporate registrant’s NA-

ICS code; however, such information is not provided in trademark applications and therefore is

not included in the USPTO database. e process of assigning NAICS codes to companies was

especially cumbersome because many of the rms drawn from the sample were small businesses

56 See USPTO’s electronic bulk data products available at https://www.uspto.gov/learning-and-resources/electron-

ic-bulk-data-products. For bulk research datasets, see http://www.uspto.gov/learning-and-resources/electronic-da-

ta-products/data.

57 ThisanalysiswasrestrictedtoU.S.-ownedrmsbecauseofthegreatdifcultyinassigningNAICScodesforsmall,

foreign-ownedrms.

58 Because the sample was drawn by registrations as opposed to registrants, a single individual or company could be

drawn more than once. However, based on the review of the registrant names, it does not appear to be the case that we

have multiple draws of the same entity in our sample.

InellecualProperandheUSconomUpdae 

with few employees and had little publicly available information from which to nd or infer a

NAICS classication.

Table A-6 provides a complete list of all 68 industries designated as trademark-intensive and

better illustrates their signicant overlap as identied by the three methodologies. All but four of

the industries listed in Table A-6 were selected based on their above-average trademark intensity.

ese four additional industries were selected based on either their top 50 registrations or the

trademark registration sample; but none of these industries was agged by both methods. Only

one industry, other miscellaneous manufacturing (NAICS 3399), was selected through all three

methods.

able -6. rademar-Inensie Indusries and Selecion Crieria

NICS

Code

Indusr ile

Selecion Crierion

rademar

Inensi op 0 Sample

 Oilandgaseracion  

 Nonmeallicmineralminingandquarring  

 Poergeneraionandsuppl  

 Nauralgasdisribuion  

 esidenialbuildingconsrucion  

 andsubdiision  

 SugarandConecionarProducManuacuring  

 ruiandegeablepreseringandspecialood  

 Dairproducs  

 Beerages  

 ooearmanuacuring  

 Oheroodproducs  

 Priningandrelaedsupporaciiies  

 Basicchemicals  



esinsnheicrubberandaricialsnheicbersand

lamens  

 Pesicideseriliersandoheragriculuralchemicals  

 Pharmaceuicalsandmedicine  

 Soapscleaningcompoundsandoilepreparaions  

 Plasicsproducs  

 Ohernonmeallicmineralproducs  



Nonerrousmealecepaluminumproducionand

processing  

 Indusrialmachiner  

 Commercialandsericeindusrmachiner 

InellecualProperandheUSconomUpdae 

 ngineurbineandpoerransmissionequipmen  

 Ohergeneralpurposemachiner  

 Communicaionsequipmen  

 udioandideoequipmenmanuacuring  

 lecronicinsrumens  

 lecriclighingequipmen  

 Oherelecricalequipmenandcomponens  

 Oherransporaionequipmen  

 Householdandinsiuionalurniureandichencabines  

 Medicalequipmenandsupplies   

 Ohermiscellaneousmanuacuring   

 Commercialequipmen   

 lecricalandelecronicgoods  

 rocerandrelaedproducs  

 rocerSores  

 DeparmenSores  

 lecronicshoppingandmail-orderhouses  

 reighransporaionarrangemen  

 Nespaperperiodicalbooanddirecorpublishers   

 Soarepublishers  

 Moionpicureandideoindusries  

 adioandeleisionbroadcasing  

 Cableandohersubscripionprogramming  

 iredelecommunicaionscarriers  

 Oherelecommunicaions 

 Oherinormaionserices  

 ciiiesrelaedocrediinermediaion  

 Securiiesandcommodiechanges  

 Ohernancialinesmenaciiies  

 Insurancecarriers  

 Oherinesmenpoolsandunds  

 essorsorealesae  

 Machinerandequipmenrenalandleasing  



essorsononnancialinangibleassesecep

coprighedors  

 Managemenandechnicalconsulingserices  

 derisingandrelaedserices   

 Oherproessionalandechnicalserices  

InellecualProperandheUSconomUpdae 

 Ohersupporserices  

 Oupaiencareceners  

 Medicalanddiagnosiclaboraories  

 Oherambulaorhealhcareserices  

 amblingindusries  

 CiicandSocialOrganiaions   

Source: USPTO calculations.

As an additional way of checking the robustness of our methodologies, we use the listing of the

top hundred global brands in 2013 as identied by Interbrand’s report of Best Global Brands.

We nd that 52 out of the 100 top global brands have a NAICS code that corresponds to that of

25 out of the 68 industries that we designated as trademark-intensive. While we were still able

to capture more than half of these brands, it is a signicantly lower rate than the 70 percent

achieved in the 2012 report.

able -. rademar-Inensie Indusries ih op 100 lobal Brands in 01

Naics

Code

Indusr ile Brand

 Oilandgaseracion Shell

 Dairproducs DanoneNesle

 Beerages

Coca-ColaPepsiBudeiser

NescaeSprieCoronaHeineen

JacDanielsJohnniealer

SmirnoMoeChandron

 ooearmanuacuring Niedidas

 Pharmaceuicalsandmedicine JohnsonandJohnson

 Soapscleaningcompoundsandoilepreparaions illee’OrealColgaeon

 Ohernonmeallicmineralproducs M

 ngineurbineandpoerransmissionequipmen enerallecric

 Communicaionsequipmen CiscoNoia

 udioandideoequipmenmanuacuring SamsungPhillipsSonPanasonic

 lecronicinsrumens Siemens

 Oherelecricalequipmenandcomponens Duracell

 Oherransporaionequipmen HarleDaidson

 Ohermiscellaneousmanuacuring CarierNinendo

 lecronicshoppingandmail-orderhouses maoncomba

 Nespaperperiodicalbooanddirecorpublishers homsoneuers

 Soarepublishers MicrosoOracleSPdobe

 Moionpicureandideoindusries Discoer

 adioandeleisionbroadcasing DisneM

 Oherelecommunicaions aceboo

InellecualProperandheUSconomUpdae 

 Oherinormaionserices oogle

 ciiiesrelaedocrediinermediaion isaMasercard

 Ohernancialinesmenaciiies Cii

 Insurancecarriers llian

 Managemenandechnicalconsulingserices ccenure

Source: USPTO calculations using Interbrand’s Top 100 Global Brands and data from Avention and Manta.

As noted before, the trademark registrations are organized by class in the USPTO database. As

reected in their class title, these 49 trademark classes are divided by the function or purpose of

the good or branches of activities for services associated with a particular trademark. is diers

signicantly from the NAICS industry classication which aims to indicate the principal busi-

ness activity of an establishment. However, looking at the trademark registration rate by class can

give some insight about the products through which trademarks impact the economy the most.

Table A-8 provides a ranked list of total trademark registrations for years 2004 – 2013. e or-

der is very closely related to what was observed in the 2012 report. Furthermore, as in the 2012

report, the same top seven trademark classes accounted for more than half of all registrations in

this time period. ree of these classes are very broad and cover services ranging from wholesale

and retail trade to professional and business services, nancial services, insurance, education-

al services and the arts, entertainment, and recreation industry that consumers use on a daily

basis.

We also observe that many of the industries we designated as trademark-intensive cor-

respond to the top seven classes, and all of those designated as trademark-intensive using more

than one methodology seem to t into one of the top seven classes.

able -8. rademar egisraions b Class, aned b

Number o egisraions, 004–01

  rademar egisraions

rademar

Class

Class ile oal Percen o

oal

Cumulaie

Percen

 lecricalandscienicapparaus   

 derisingandbusiness   

 ducaionandenerainmen   

 Compuerandscienic   

 Clohing   

 Insuranceandnancial   

 Papergoodsandprinedmaer   

 Pharmaceuicals   

 Cosmeicsandcleaningpreparaions   

 osandsporinggoods   

59 These classes are advertising and business (class 35), education and entertainment (class 41), and insurance and nan-

cial (class 36).

InellecualProperandheUSconomUpdae 

 Sapleoods   

 Medicalbeauandagriculural   

 Buildingconsrucionandrepair   

 Hoelsandresaurans   

 Machiner   

 nironmenalconrolapparaus   

 Medicalapparaus   

 elecommunicaions   

 Personalandlegal   

 urniureandariclesnooheriseclassied   

 Measandprocessedoods   

 Housearesandglass   

 Chemicals   

 inesandspiris   

 ehicles   

 ransporaionandsorage   

 eahergoods   

 Jeelr   

 Mealgoods   

 reamenomaerials   

 ighbeerages   

 Non-meallicbuildingmaerials   

 Nauralagriculuralproducs   

 abrics   

 ubbergoods   

 Handools   

 Pains   

 ubricansanduels   

 Smoers’aricles   

 ancgoods   

 loorcoerings   

 Cordageandbers   

 irearms   

 Musicalinsrumens   

B Sericescericaionmar   

 arnsandhreads   

 Colleciemembership   

 oodscericaionmar   

 oal 1896 100.00 100

Source: USPTO calculations using the agency’s trademark registration data.

Note: e cumulative percent gures may not equal the sum of the percent of total gures because of rounding.

InellecualProperandheUSconomUpdae 

Coprighs

As indicated in the text, our methodology for designating copyright-intensive industries draws

heavily from denitions established by the World Intellectual Property Organization’s (WIPO)

Guide on Surveying the Economic Contribution of the Copyright-based Industries.

A series of

reports by Stephen Siwek titled Copyright Industries in the U.S. Economy have applied these

denitions to the U.S. economy.

While this established literature underlies our analysis, we used

a more narrow denition of copyright-intensive industries than WIPO, focusing on industries

that produce copyrighted work and excluding several industries associated with the distribution

of copyrighted material. is deviation from the WIPO Guide was needed in order to maintain

internal consistency with our measures of patent- and trademark-intensive industries.

Mehodolog

Because WIPO’s Guide on Surveying the Economic Contribution of the Copyright-based Industries

clearly distinguishes the type of works that can be copyrighted, the industries in which those

works are created, and the downstream (distribution) industries delivering the produced copy-

righted works, it is possible to develop a list of copyright-intensive industries that is comparable

in scope to our lists of patent- and trademark-intensive industries. We started by focusing on

“core” copyright industries, which WIPO denes as industries “wholly engaged in creation, pro-

duction and manufacturing, performance, broadcast, communication and exhibition, or distri-

bution and sales of works and other protected subject matter.”

In other words, core copyright

industries were considered ‘core’ because they either produce copyrighted materials or bring

them to market.

For this report, we are only concerned with the set of industries that are primarily responsible

for the creation or production of copyrighted materials and designate them as copyright-inten-

sive. us, to the extent possible using four-digit NAICS industry codes, we excluded industries

whose primary purpose is to distribute copyright materials to businesses, consumers or both. For

example, we did not count industries such as book, periodical, and music stores (NAICS 4512) or

consumer goods rental (NAICS 5322), which includes video rentals, as copyright-intensive even

though they are part of the “core” category in the WIPO guide.

Our denition is narrower than

WIPO’s in order to be consistent with our treatment of patent- and trademark-intensive indus-

tries, where industries most responsible for the production of protected IP are the main focus.

is approach simply reects our goal of examining the industries in the economy that are most

60 World Intellectual Property Organization 2003.

61 See, for example, Siwek 2009.

62 World Intellectual Property Organization 2003, 29. The core copyright industries represent one of four main groups of

63 ThisdiscussionshouldnotimplythatdistributionindustriesasawholecannotbyourdenitionsbeconsideredIP-in-

tensive. As discussed above, a broad range of industries seek trademark protection, including distribution industries

likeclothingstores,whichareidentiedasIP-intensive.

InellecualProperandheUSconomUpdae 

responsible for the production of protected IP and use of this approach is not a criticism of WI-

PO’s guidelines.

One conceptual distinction between the approach taken here and that selected in the patent and

trademark sections is worth noting. roughout this report, the focus was on industries that

produce protected IP, whether patents, trademarks, or copyrights. In the case of patents and

trademarks, we dened “intensive” industries as the subset of all patent or trademark producers

that had high scores in various “intensity” measures, whereas we dene as copyright-intensive

essentially all industries traditionally associated with the production of copyrighted materials.

Table A-9 lists the copyright-intensive industries. All are involved in the creation and/or record-

ing (in print, magnetically, or digitally) of protected works.

able -9. Coprigh-Inensie Indusries

NICS code Indusr ile

 Nespaperperiodicalbooanddirecorpublishers

 Soarepublishers

 Moionpicureandideoindusries

 SoundecordingIndusries

 adioandeleisionbroadcasing

 Cableandohersubscripionprogramming

 Oherinormaionsericesnessndicaesandinernesies

 Specialieddesignsericesisualandgraphicars

 Compuerssemsdesignandrelaedsericessoareanddaabases

 derisingandrelaedserices

 Oherproessionalandechnicalserices

 Perormingarscompanies

 Independenarissriersandperormers

Source: ESA selection based on World Intellectual Property Organization 2003.

Combined is o IP-inensie indusries

Table A-10 provides the total list of all eighty-one unique IP-intensive industries that we obtain

from a combination of the patent-, trademark-, and copyright-intensive industries we already

identied. In light of the considerable overlap between the patent- and trademark-intensive

industries and some between copyright- and trademark-intensive industries, the 81-industry

total is smaller than the sum of the parts. is table also indicates that 15 out of the 25 patent-in-

tensive industries are designated as both patent- and trademark-intensive while 7 out of the 13

construction, there does not exist any overlap between patent- and copyright-intensive industries.

64 We list the relevant copyrighted materials in parentheses if the title describing the industry does not clearly indicate

what protected materials are produced (e.g. other information services (NAICS 5191)).

InellecualProperandheUSconomUpdae 

is is because the USPTO developed a concordance of patent technology only to manufacturing

industries from which the patent-intensive industries are identied. ese industries do not cov-

er any of the service sectors from which the copyright-intensive industries are drawn.

Table A-10 also provides the employment count in 2013 for each of these IP-intensive industries,

totaling 27.3 million jobs for the year.

able -10. IP-Inensie and Selecion Crieria

NICS

Code

Indusr ile  Selecion crieria

mplomen

in 01

1000 jobs

Paen-

Inensie

rademar-

Inensie

Coprigh-

Inensie

 Oilandgaseracion    

 Nonmeallicmineralminingandquarring    

 Poergeneraionandsuppl    

 Nauralgasdisribuion    

 esidenialbuildingconsrucion    

 andsubdiision    



Sugarandconecionarproduc

manuacuring    



ruiandegeablepreseringand

specialood    

 Dairproducs    

 Beerages    

 ooearmanuacuring    

 Oheroodproducs    

 Priningandrelaedsupporaciiies    

 Basicchemicals    



esinsnheicrubberandaricial

snheicbersandlamens    



Pesicideseriliersandoher

agriculuralchemicals    

 Pharmaceuicalsandmedicine    



Paincoaingandadhesie

manuacuring    



Soapscleaningcompoundsandoile

preparaions    



Oherchemicalproducandpreparaion

manuacuring    

 Plasicsproducs    

65 In addition to wage and salary jobs, the employment count included self-employment; which accounts for a sizeable

portion of employment in the copyright-intensive industries.

InellecualProperandheUSconomUpdae 

 Ohernonmeallicmineralproducs    



Nonerrousmealecepaluminum

producionandprocessing    



griculureconsrucionandmining

machinermanuacuring    

 Indusrialmachiner    



Commercialandsericeindusr

machiner    



enilaionheaingair-condiioning

andcommercialrerigeraionequipmen

manuacuring    

 Mealoringmachinermanuacuring    



ngineurbineandpoerransmission

equipmen    

 Ohergeneralpurposemachiner    

 Compuerandperipheralequipmen    

 Communicaionsequipmen    

 udioandideoequipmenmanuacuring    



Semiconducorsandoherelecronic

componens    

 lecronicinsrumens    



Manuacuringandreproducingmagneic

andopicalmedia    

 lecriclighingequipmen    

 Householdappliancemanuacuring    

 lecricalequipmenmanuacuring    



Oherelecricalequipmenand

componens    

 Oherransporaionequipmen    



Householdandinsiuionalurniureand

ichencabines    

 Medicalequipmenandsupplies    

 Ohermiscellaneousmanuacuring    

 Commercialequipmen    

 lecricalandelecronicgoods    

 rocerandrelaedproducs    

 rocersores    

 Deparmensores    

 lecronicshoppingandmail-orderhouses    

 reighransporaionarrangemen    

InellecualProperandheUSconomUpdae 



Nespaperperiodicalbooanddirecor

publishers    

 Soarepublishers    

 Moionpicureandideoindusries    

 SoundrecordingIndusries    

 adioandeleisionbroadcasing    

 Cableandohersubscripionprogramming    

 iredelecommunicaionscarriers    

 Oherelecommunicaions    

 Oherinormaionserices    

 ciiiesrelaedocrediinermediaion    

 Securiiesandcommodiechanges    

 Ohernancialinesmenaciiies    

 Insurancecarriers    

 Oherinesmenpoolsandunds    

 essorsorealesae    



Machinerandequipmenrenaland

leasing    



essorsononnancialinangibleasses

ecepcoprighedors    

 Specialieddesignserices    



Compuerssemsdesignandrelaed

serices    



Managemenandechnicalconsuling

serices    

 derisingandrelaedserices    

 Oherproessionalandechnicalserices    

 Ohersupporserices    

 Oupaiencareceners    

 Medicalanddiagnosiclaboraories    

 Oherambulaorhealhcareserices    

 Perormingarscompanies    



Independenarissriersand

perormers    

 amblingindusries    

 Ciicandsocialorganiaions    

Source: USPTO calculations using data from the Bureau of Labor Statistics’ Industry Productivity program.

Note: Employment includes wage and salary jobs, the self-employed, and unpaid family workers and is measured in thousands

of jobs.

InellecualProperandheUSconomUpdae 

Table A-11. IP-Related Products and Services in the 2017

North American Product Classication System (NACPS)

NPCS code ile

 Conracproducionsericesorinellecualproper

 ieperormancesproducedunderconrac

 Conracliesporingeens

 Conracliepublicappearancesandspeeches

 Supporsericesorproducionoaudioisualorsandsudiosoundrecordings

 clusiirighs

 icensingorighsouseinellecualproperproecedbrademar

 icensingorighsouseinellecualproperproecedbcoprigh

 Ourighsaleoinellecualproperproecedbcoprigh



Conracproducionsericesorinellecualproperproecedbcoprigheclude

lieperormingars

 Conracdesignsericesorinellecualproperproecedbrademar

 icensingodomesicrighsodisribueaudioisualors

 icensingodomesicrighsoehibibroadcasorreneaurelms

 icensingodomesicrighsoehibibroadcasorrenshorlms

 icensingodomesicrighsobroadcasorreneleisionprogramming

 icensingodomesicrighsoehibibroadcasorrenoheraudioisualors

 icensingoinernaionalrighsodisribueaudioisualors

 icensingoinernaionalrighsoehibibroadcasorrenaudioisualors

 icensingoinernaionalrighsouseconcepodomesicaudioisualors

 icensingoinernaionalrighsoroherusesoaudioisualors

 Conracproducionsericesoraudioisualors

 icensingorighsousemusicalcomposiions



icensingorighsousemusicalcomposiions-orecordandreproduceor

commercialuseecepordisribuionasphonorecordsieelecricalranscripion

righs



icensingorighsousemusicalcomposiions-Inadramaicoriegrandrighs

anddramaicadopionrighs

 icensingorighsousemusicalcomposiions-Inoherors



icensingoinernaionalrighsopublishdomesicmusicalcomposiionsie

inernaionalsub-publishing

 icensingorighsousemusicalrecordings

 dminisraionocoprighsorohers

 Merchandiselicensing-Domesicandinernaional

 icensingorighsousemusic

 icensingorighsouseaudioisualors

 Conracproducionsericesororiginalmusicecludingmusicoraudioisualors

InellecualProperandheUSconomUpdae 

 icensingorighsoreproduceanddisribuecompuersoare

 icensingorighsobroadcasradioprograms

 icensingorighsodisribuespecialaudioprogrammingconen

 icensingorighsobroadcaseleisionprograms

 icensingorighsodisribuespecialeleisionprogrammingconen

 icensingorighsosndicaedmediaconen

 Paencoprighandoherinellecualproperdocumenlingandsearchserices



icensingorighsoreproduceanddisribuecompuersoareproecedb

coprigh

 icensingorighsousesocphoos

 Paenbroeringmareingserices

 Paendraingandrademarillusraionserices

 Ourighsaleooriginalorsoinellecualproper

 icensingorighsouseinellecualproper

 icensingorighsouseinellecualproperproecedasindusrialproper

 icensingorighsouseinellecualproperproecedbcoprighs

 icensingandroalagreemensoeploinauralresources

Source: U.S. Census Bureau at http://www.census.gov/eos/www/napcs/.

InellecualProperandheUSconomUpdae 

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