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Strategic Management Journal
Strat. Mgmt. J.,32: 11281138 (2011)
Published online EarlyView in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smj.925
Received 16 July 2009;Final revision received 5 October 2010
RESEARCH NOTES AND COMMENTARIES
ESTIMATING THE PATENT PREMIUM: EVIDENCE
FROM THE AUSTRALIAN INVENTOR SURVEY
PAUL H. JENSEN,* RUSSELL THOMSON, and JONGSAY YONGMelbourne Institute of Applied Economic and Social Research, and Intellectual PropertyResearch of Australia (IPRIA), The Uniersity of Melbourne, Par!ille "ictoria, Australia
In this paper we use novel survey data on 1,790 Australian inventions to estimate the averagepatent premium, which provides an important benchmark for technology managers and IPprofessionals. Our data are drawn from the Australian Inventor Survey, which was sent to allAustralian applicants who submitted a patent application to the Australian Patent Office from1986 to 2005. Since some patent applications were unsuccessful, we have information about the
private value of both patented and unpatented inventions. Our results suggest that the presence ofa patent increases the returns to an invention by around 40 to 50 percent regardless of how wedefine value. Copyright 2011 John Wiley & Sons, Ltd.
INTRODUCTION
The introduction of new products andprocesses plays a pivotal role indriving firms productivity,profitability, and competitiveadvantage (Cecca-gnoli, 2009).However, innovators face animportant challenge in choosingamong different appropriationstrategies including patenting and
keeping ahead of the opposition, thechoice of which can have far-reaching consequences for firmprofitability. Survey evidence hassuggested
Keywords: patents; invention;commercialization; patent premium*Correspondence to: Dr. Paul H. Jensen,Melbourne Institute of Applied Economic andSocial Research, and Intellectual Property
Research Institute ofAustralia (IPRIA) Level 7,Alan Gilbert Building, The
University of Melbourne,Parkville VIC 3010,Australia. E-mail:[email protected]
that, on average,patents are considered
relatively less
important than other
appropriation
strategies, but that the
value of patenting
varies consider-ably
across technology
areas (Levin et al.,
1987; Harabi, 1995;
Cohen, Nelson, and
Walsh, 2000). In part,
this observation may
reflect the fact that not
all technologies are
patentable. In this
paper we use novel
survey data on 1,790
Australian inventions
to estimate the
average patent
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premium, which pro-vides an
important benchmark for technology
man-agers and intellectual property
(IP) professionals.
To understand our estimates of the
patent pre-mium, it is important todistinguish between the value of an
invention and thevalue of patent pro-
tection. The value ofan invention isdefined as thediscounted flow of
profits generated
over the course ofthe inventions
economic life, whilethe value of patentprotection is definedas the return
Copyright 2011 John Wiley &Sons, Ltd.
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over and above that which could havebeen gen-erated by the second bestmeans of appropriation (Schankerman,
1998; Lanjouw, 1998).1 The value ofpatent protection can be defined aseither the incremental return (i.e., indollar terms) or as the proportional
increase in value to an invention due topatent protection. The latter is referredto as the patent premium by Arora,Ceccagnoli, and Cohen (2008) and isanalogous to Schankermans (1998: 95)equivalent subsidy rate.
Existing studies of the value of patentprotection can be divided into threestreams. The first relates to surveys offirms and inventors, which show thatpatenting ranks near the bottom of allappropria-tion mechanisms (see Levin
et al., 1987; Cohen et al., 2000).Similarly, Mansfield and collabo-rators(Mansfield, Schwartz, and Wagner,1981; Mansfield, 1986) found patentprotection to be important in thecommercialization of a minor-ity ofinnovations. Arora et al. (2008)developed a model of innovation andpatenting to directly esti-mate the patentpremium and its impact on research anddevelopment (R&D) investment. Usingsurvey data, they modeled the patentpremium as con-sisting of a fixed-firmcomponent as well as an idiosyncraticcomponent and then jointly estimatedthe firms R&D productivity, patentpropensity, and patent premium. Theyshowed that the mean premium ispositive in only a few industries, butthat conditional on patenting, theaverage patent premium is 0.5.
The second stream of studies involves
imputing the value of patents from patent
renewal decisions. The seminalcontribution is Schankerman and Pakes
(1986), while more recent studies include
Sampat and Ziedonis (2004), Deng
(2007), and Gronqvist (2009). The
premise of this approach is that firms only
renew their patents if the value of patent
protection is greater than the cost of
renewal. The method involves estimating
param-eters that describe the distribution
of the initial value of patented inventions
as well as depreciation rates. It is
generally acknowledged that the highly
skewed distribution of patent values make
finite sample estimation unreliable (see
Bessen, 2009). Schankerman (1998: 95)
generated an estimate of the equivalent
subsidy rate by dividing his esti-mates of
the value of patent protection by the total
1 This implies that, in the absence of patent
protection, firms are able to generate some returnsusing alternative means of appropriation.
Copyright 2011 John Wiley & Sons, Ltd.
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Research Notes and Commentaries
R&D expenditure used to producethose patents (in practice this ismeasured by aggregate R&Dexpenditure in the previous year) givingan esti-mated effective subsidy rate of
0.25.2
The third stream of research attempts
to infer the value of patent protectionfrom its effect on the market value offirms (typically Tobins Q). Exam-plesof this approach include Griliches(1981); Hall, Jaffe, and Trajtenberg(2005); Hall and Mac-Garvie (2006);Bosworth and Rogers (2001); and,Ceccagnoli (2009). Bessen (2009)argued that, in principle, theincremental value of patents can beisolated if we can control for the firmstotal quality-adjusted technology stock.
However, this approach relies on theefficient markets hypothe-sis, which isnot universally considered to be arobust assumption.
In this paper, we adopt a new approach
to this issue based on analysis using data
drawn from the Australian Inventor
Survey 2007 (AIS-07),3which was sent to
all Australian applicants who submitted a
patent application to the Australian Patent
Office from 1986 to 2005. A major
difference between the AIS-07 and other
inventor surveys (see Harhoff et al., 1999;Giuri et al., 2005; and Gambardella,
Harhoff, and Verspagen, 2008) is that we
sur-vey patent applicants rather than
patentees. Since some patent applications
were unsuccessful, we have information
about the private value of both patented
and unpatented inventions. Moreover,
there is considerable variation in the
commercial-ization outcomes across
patented and unpatented inventions. This
variation is the key to our empir-ical
identification of the patent premium. We
also attempt to separate the patent
premium from observable quality
characteristics of the invention.4
Our paper makes a number of
contributions. First, we present new
estimates of the aver-age patent premium
based on a novel empirical approach. All
of the inventions in our counterfac-tual
sample are potentially patentable, as
indicated by the decision of the applicants
to apply for a patent.5Second, we present
estimates of the private
2 See similar analysis by Lanjouw (1998)for West German patents during the period 19531988.3 For more details of the AIS-07, see Webster andJensen (2009).
4Ideally, we might use independent evaluations ofinvention quality (e.g., Moser, 2007) to achieve this.However, such data are not available for our sampleof inventions.
5 Moreover, note that since our estimated
patent premium is conditional on a patent
application being made, inventions for which it is
optimal to appropriate returns via secrecy are not
included.
Strat. Mgmt. J.,32:11281138 (2011)
DOI:10.1002/sm
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1130 P. H. Jensen, R. Thomson, and J. Yong
value of
Australian
inventions.
Finally, our paper
provides estimates
of the
heterogeneity ofthe patent
premium across
technology areas.
In this light, our
results have
important
implications for
the strategic
management of
inventive activity.
Estimating the
patent premium
also has important
public policy
implications.
Governments
around the world
employ an array
of policies
designed to
stimulate
innovative
activities. Forexample, across
the Organisation
for Economic Co-
operation and
Development
(OECD),
governments
typically fund
between 10 and
20 percent of total
business invest-
ment in R&D.6
Estimates of the
patent premium
enable policy
makers to
consider the size
of the implicit
subsidy provided
to inventors via
the patent system
vis-a`-vis other
subsidies.
SUR
VEY
DAT
A
AND
EMPI
RICA
L
APP
ROA
CH
The AIS-07involvedsending aquestionnaire
to everyAustralianinventor whosubmitted apatentapplication tothe AustralianPatent Officebetween 1986
and 2005.7Therelationshipbetween inven-
tor andinvention ismany to many.To deal withthis, we sentthe survey toeach listedinventor on apatent
application.8
Where aninventor hadmultipleinventions, thesurvey askedquestionsregarding amaximum offive inventions.We con-ductedtwo separatemailings of thesurvey in Julyand Decemberof 2007.
In total,
there were43,200inventor-applicationpairs in thepopulation thatrelated to
31,313 uniquepatentapplications(i.e.,inventions). Onthe basis of the number of surveys returnedto us unopened (and a post-enumeration sur-vey ofnonrespondents), we estimatethat therewere 5,446 inventions with valid addresses at
the time of the mailing.9 In total, we received6
Figures for 2005or nearest availableyear, calculatedfrom OECD (2008a,2008b).
7As in the PatVal-EU survey, we sentthe survey to theinven-tor rather thanthe owner of theinvention. While itis possible that theinventor knows lessthan the ownerabout commercial-ization outcomes,Gambardella et al.(2008) comparedthe value estimatesfrom a sample ofFrench inventorsand patent ownersand found that thebias introduced wasnegligible. We haveno reason to believethat such a bias isany larger inAustralia.
8Where multiplesurveys werereturned on thesame invention,only one (randomlyselected) responsewas used.
9 The low
proportion of
inventions with
valid inventor
addresses is a result
of the fact that the
survey included
patent applica-tions
dating back to 1986.
Since the Australian
Patent Office
Copyright 2011 JohnWiley & Sons, Ltd.
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completedquestionnairesrelating to 3,736uniqueinventions.
The data sethas 2,448observations
with non-missinginvention values.Of these, 645were stillpending a patentofficeexaminationdecision at thetime the surveywasadministered.These appli-
cations wereexcluded fromthe analysisbecause ourfocus here is onthe estimation ofthe pre-miumassociated with a
patent grant.10 Afurther 13observations hadmissing
information onother explanatoryvariables andwere alsoexcluded,leaving a finalsample of 1,790observations.
Survey
responses came
from inventors in
a range of
employmentarrangements:
companies (43.7
percent), public-
sector research
organizations (5.9
percent), and
individuals (50.4
percent). The
inventions in the
sample of survey
respondents
covered a broad
cross-section of
different
technol-ogy
areas, which
were classified
using the
United
Kingdom Officeof Science and
Technology-
Inter-national
Patent
Classification
(OST-IPC)
technol-ogy
concordance.
The distribution
by technology
area suggeststhat our sample
is broadly
represen-tative
of the
population of
patent
applications.
By applying
for a patent,the inventorhas sig-naled
that his or hertechnology ispatentablesubject matter.Since the
patentapplicationpro-cessinvolves
disclosure ofthe technology,
the inventorhas foregone
the possibilityof relying on
secrecy toappropriate
returns. Thisindicates that
our sampleincludes onlyinventions forwhich
patenting was
considered tobe the bestoption (Moser,2007). It also
suggests thatour estimatesare an upperbound of the
ex ante valueof patentprotection
since it isharder toappropriatereturns without
patentprotection once
disclosure hasoccurred
(Horstmann,MacDonald,
and Slivin-ski,1985;
Schankerman,1998).
ESTIMATES
OF
INVENTION
VALUE
The privatevalue of aninvention is thediscountedflow of profitsthat accrue toits owner overthe
does not updateinventors contactdetails, we wereunable to contactinventors whosecontact address hadchanged for anyreason (e.g., jobchange, retirement,or changes inpersonalcircumstances).10
As a robustnesscheck, we alsoundertook theanalysis by
including
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applicationscategorized aspending. This did notchange the substantive
results.
Strat.
Mgmt. J.
32: 1128
1138 (2011)
DOI: 10.1002/smj
course of its economiclife. Invention value isdif-ficult to measure in
practice. Economistswould typicallyapproach such aproblem using pricesobserved in markettransactions. However,the vast majority ofpatents are not traded in
an open mar-ket.11 Anincreasingly popularalternativewhich weuse in this paperis to
ask inventors to esti-mate the value of theirinvention.
Like PatVal-EU, our
survey data include
inven-tions of different
vintages. The initial
PatVal-EU survey, which
was conducted in 2003
2004, includes a sample
of patents with a priority
date between 1993 and
1997. Both PatVal-EUand AIS-07 require
respondents to estimate a
total value including
returns already generated
as well as expected future
returns.12 PatVal-EU
asked inven-tors to report
the price they would be
willing to sell the
invention for at the time
the patent was issued.Our approach is different
in that we sep-arate
historical returns (i.e.,
returns generated up to
the time of the survey in
2007) from the future
value (i.e., the discounted
value of expected future
profits after 2007) of the
invention. This eases the
computational burden
imposed on the inventors
and enables us to
evaluate the sensitivity of
our results to different
measures of invention
value. This also means
that our forward-lookingmeasure of value is in
constant (2007) prices.
We asked inventorsthe following threeques-tions in relation toinvention value:
(1) To date, what isyour estimate ofsales rev-enuefrom products and
processes usingthis invention?
(2) If this patent hasbeen licensed,what is your bestestimate of licensing revenuesto date?
(3) If you wereselling this patentor invention today,
what price wouldyou be willing toaccept for it?
In each case, thesurvey respondent hadto select one of sixpossible value ranges(in Australian dollars):below $100,000,$100,001 $500,000,$500,001$1million,
$1$2 million,11
The few that are subject toobservable trades are highlyselected. Serrano (2006) andSneed and Johnson (2009) haveexamined some such patenttransfers (via auctions) in orderto understand the market forpatents.
12 This is quite
different to Harhoff et al.
(1999), who surveyed one
cohort of patented inventions,
namely all patent applications
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in Germany in 1977. Thus, the
Harhoff et al. (1999) survey
covered revenues actually
generated by the invention.
Copyright 2011 John Wiley &
Sons, Ltd.
Research Notes and Commentaries 1131
$2$10 million, above$10 million. To convertthe responses tonumerical values, wetook the mid-point ofeach interval. Since the
highest value category(above $10 million) isunbounded, we imposedan upper bound of $50
million.13
Questions (i) and (ii)focus on returns thathave already beengenerated, capturingsales revenue
generated14 andlicensing revenues,
respectively. Question(iii) reflects the netpresent value of expected future returns.To estimate inventionvalue, we useinformation fromresponses to all threequestions. SinceQuestion (i) is revenue-rather than profit-based,we set the gross marginat 30 percent for goods
and services producedusing an invention.15
We then added the threecompo-nents of valuetogether to construct theprivate invention value,which we denote
InvVal.16
We argue that it is
important to include both
past profits and expected
future revenue in our
mea-sure of inventionvalue. Since we have a
mix of inventions of
different ages, simply
using data on total
revenue to date will
underestimate the value
of newer inventions. The
value of inventions with
faster rates of
depreciation may also be
system-atically
overestimated. As
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depreciation of inven-
tion value is in part a
function of diffusion, it is
likely to be related to
patent grant status.
However, we
acknowledge that survey
questions relating to
expected future revenuesare perhaps noisier and
less reliable than
questions based on actual
rev-enues. Accordingly,
we also present results
from regressions using
the answer to Question
(i) as the dependent
variable (with controls
for priority year)which
we refer to as SalesRev.17
The distribution ofestimated private inven-tion value (InvVal ) ishighly skewed: themean and medianinvention values in oursample are A$6.6million and A$800,000respectively, which isbroadly consistent withother inventor surveys(see Gambardella et al.,
2008). The difference in13
We also computed all resultsusing values of $100m and$200m as the upper bounds,which did not change theresults.
14It may, however, be a weak
measure of process inventionvalue since processes are morelikely than product inventionsto be used in-house, andtherefore do not typicallygenerate sales revenue.
15We have also checked ourresults by taking the value of aninvention at 100 percent of therevenue of all goods andservices sold. This variationproduces essentially the sameresults.
16With regard to licensingrevenue, we set the value tozero if the respondent did notanswer the question or wasunsure of the amount. Thus, weprobably understate the actuallicensing revenue.
17 We thank an
anonymous referee for
making this suggestion.
S
t
r
a
t.
M
g
m
t.
J.,
3
2
:
1
1
2
8
1
1
3
8
(
2
0
11
)
DOI: 10.1002/smj
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1132 P. H. Jensen, R. Thomson, and J. Yong
Figure 1. Distribution of private invention value, by patent grant status
invention value by patent grant statusis pre-sented in Figure 1. From this,we can see that there areproportionately more valuable inven-tions (above A$1 million) amonginventions pro-tected by a patent.However, many inventions that arenot protected by a patent are highlyvaluable. The difference between themean value of the patented and non-
patented inventions is 9.4 percent.18
Thus, patented inventions are morevaluable on average, but unpatentedinventions are far from worthless.
We also undertook a range ofanalyses to probe the robustness ofour value measure. First, it isreassuring that responses to Question(i) and Ques-tion (iii) are positively
correlated.19We also con-sidered thedistribution of invention values by
commercialization stage.20 As onewould expect, private value was
found to be increasing in the stage ofcommercialization attempted.21
18The mean values are A$6.7 million and A$6.1million for patented and unpatented inventionsrespectively. The difference in median inventionsvalues for the two groups, however, is muchlarger.
19 The raw correlation is 0.33. In a log-on-log regression model controlling for year ofapplication (and therefore obsolescence), thecoefficient on the response to Question (iii) is 0.5,with a t-value above 25.20 Webster and Jensen (2009) consider the impactof patent grant on attempts to commercializeinnovations using data from the AIS-07. Theyshow that, on average, patents play a small butimportant role in shaping attempts tocommercialize inventions.
21 Ideally, we
would also test the validity
of our measure of invention
value by comparing them
with other indicators of
patent value, such as the
number of forward
citations. However, this is
not possible in this instance
because disclosure of prior
art is voluntary at the
Australian Patent Office.
Copyright 2011 John Wiley &Sons, Ltd.
EMPIRICAL
MODEL
Let Vij denote the totalprivate value of invention i in technologyarea j , i = 1, . . ., njand j=1,. . ., J. We specify alinear model wherethe value of aninvention depends onwhether a patent hasbeen granted(conditional on apatent applicationbeing made).
ln Vij=Gij+X+j+ij, (1
where Gij is a binary variable taking the valuof unity if a patent hasbeen granted and zerootherwise,22 X is avector of additionalexplana-toryvariables, j is atechnology-specificterm, and ij is theresidual error term.We model thetechnology-specific
term, j, using atechnology-specificdummy variable,which takes the valueof unity if theinvention is intechnology areaj, andzero otherwise.23
One of the mostdifficult aspects ofour study relates toseparating the valueof patent protec-tionfrom the underlyingvalue of thetechnology. If
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inventions that are granted a patentgenerally have higher commercialvalue, our estimates of
22Although we treat this variable as a simplebinary variable, we acknowledge that the claimsin a granted patent may be different from those inthe original patent application. Unfortunately,changes in the claims as a result of interactionbetween the applicant and the patent examiner areunobserved. We thank an anonymous referee forpointing out this issue.
23 We also attempted a second
specification, the random-intercept model, in which
jis assumed to be a random variable and follows an
identical and independent
normal distribution with
mean zero and variance 2.
The results are similar and are
omitted for the sake of
brevity.
Str
at.
Mg
mt.
J.,
32:
11
28
11
38
(20
11)
DOI: 10.1002/smj
the patent premium would be biased.However, it is not clear that commercialvalue and the patent examinationdecision are necessarily corre-lated. Inexamining a patent application, thepatent office considers whether theinvention is useful, novel andnonobvious. Thus, the patent exam-inerevaluates the inventions technologicalmerit, not its expected economic value.Evidence sug-gests that a largeproportion of patented inventions havevery low (or zero) commercial value(see Harhoff et al., 1999; Gambardellaet al., 2008). Conversely, there aremany examples of inventions withsubstantial commercial value that arenot cov-ered by a patent. However, it
remains a possibility that there are othercharacteristics of the under-lyingtechnology that determine the value ofthe invention and are associated with the
patentability requirements.24
Taking these factors into account, weproceed using a reduced-form approachthat includes addi-tional variables tocontrol for characteristics of thetechnology that may be correlated with
invention value.25 First, we include adummy variable, radi-cal invention,which relates to whether the inventorrated his or her invention as radical orincre-mental. Second, we construct avariable related to the number ofproducts and processes for which theinvention was used (denoted as no. ofuses). This variable is expected to bepositively correlated with value.Although the relationship is proba-blynoisy (since there are many single-useinven-tions that have high commercialvalue), it seems reasonable to expectthat value is an increasing function of
the generality of the invention, ceterisparibus.
Third, we include a variable, other
inventions used, to proxy for the
complexity of the technology area. This
variable is based on the survey question
that asked the inventor how many other
patents were used to develop the product.
The expected sign of this variable is
unclear since it could be the case that
complex technologies are more valu-able
(i.e., there is a positive association with
value) or it could be that transaction costs
associated
24One important feature of our empirical approach isthat our data only include inventions that, in the viewof the applicant, involve patentable subject matterand have the potential of passing the criteria ofnovelty and nonobviousness.
25 To investigate the possibility of a
selection effect, we also used a two-stage sample
selection model. We failed to reject the null
hypothesis of no sample selection (results are
available from the authors upon request).
Copyright 2011 John Wiley & Sons, Ltd.
Research Notes and Commentaries 1133
with negotiating with other patentowners erode the value of the invention(i.e., there is a nega-tive association
with value). The net effect of these twoforces depends on who owns the otherpatents required to develop the product,which is unob-served in our dataset. Wealso include a dummy variable, PCTapplication, indicating whether theapplication was made through the PatentCooper-ation Treaty (PCT) to accountfor the fact that the invention may havepatent protection in other legal
jurisdictions, even if the patent was notgranted in Australia.
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Attributes of the firm or individualwho owns the invention also affect therevenue that can be appro-priated. Firmsize is a key variable as the poten-tialprofit from an invention is directlyrelated to the resources of the firm.Teece (1986) highlights the importanceof complementary assets, such asmanufacturing capacity, in facilitatingthe appro-priation of innovation returns.Similarly, large ver-tically integratedfirms and conglomerates that operate inmultiple industrial sectors may be betterplaced to capture profits andinterindustry techno-logical spillovers(see Weder and Grubel, 1993). Werelied on information from severalsources to construct firm size dummy
variables.26 Our model includes threedummy variables reflecting large
company, small and medium enterprise(SME), and public sector researchorganization, with indi-vidual serving asthe reference group.A priori, we expectthat large firms and SMEs have greaterincentives and are better placed inappropriating returns than public sectorresearch organizations and individuals.
The dependent variable in our basemodel is the measure of invention value(denoted by InvVal ), whichincorporates information about pastsales revenue and license fees as well asthe forward-looking value (as discussedpreviously). As an alternative, weconsider historical sales revenue
26 From the patent office database, we observe
whether the patent is registered to an individual or anorganization. Public sector research organizationswere identified by searching for any organizationwith words such as institute, university, orresearch in its name. Of those not registered to anindividual or public sector research organization, wematched the name of the organization with aproprietary database maintained by IBISWorld, aprivate Australian market research and analysis firm.The IBISWorld database includes all of the largestfirms in Australia and we use this information toconstruct the firm size dummy variables. Admittedly,a better indicator of firm size would be based onturnover or employment. However, such data are notavailable and we note that this would not be possiblefor nonaffiliated individual inventors.
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11281138 (2011)
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1134 P. H. Jensen, R. Thomson, and J. Yong
Table 1. List of variables and summary statistics
Variable Explanation Mean Std. dev.
ln(InvVal) Private value of invention (in logarithms) 6.945 2.026No. of uses No. of products/processes for which invention was used 1.331 0.971Other inventions used No. of other inventions used in development 0.378 0.623No. inventors No. of inventors involved 1.549 1.127
Large company dummy, (=1 if invention owned by large company) 0.088 0.283SME dummy, (=1 if invention owned by SME) 0.351 0.478Public organization dummy, (=1 if invention owned by public organization) 0.059 0.235Individual dummy, (=1 if invention owned by nonaffiliated individual) 0.502 0.500Radical invention dummy, (=1 if invention was radical relative to state of art) 0.628 0.483PCT application dummy, (=1 if PCT application) 0.356 0.479
Granted dummy, (=1 if patent application granted) 0.727 0.446
as a dependent variable, which we denote as
SalesRev. The use of these two different
measures enables us to ascertain the
robustness of our results and the ad hoc
assumption that gross profit mar-gins are
uniformly the same (30 percent) across all
inventions. In particular, if profit margins
vary systematically with patent protection,
our use of a fixed proportion may downward
bias our estimate of the patent premium.
Each model also includes patent application
year dummies (equivalent to invention age)
to capture the effects of technol-ogy,
business cycles, and/or obsolescence. Table
1 lists the variables we used in the
estimation and some descriptive statistics.
The patent premium is captured by thecoef-ficient in Equation (1) and is
reported as the coefficient of the variablegrantedin Table 2. This dummy variableequals one for patent applica-tions thatwere granted, and zero if the applicationwas refused, withdrawn, lapsed, orrevoked. As such, the variable takes abroad definition of non-grants in that itincludes all patent applications that wereeither unsuccessful or were removed fromthe examination process by the patentoffice (or the applicant). The key point isthat all the inventions categorized asgranted have patent protection and that
all inventions categorized as non-grantsdo not. The coefficient of the variablegranted tells us whether the protectionoffered by apatent increases (and by howmuch) the inventors returns, ceteris
paribus. As the dependent vari-able is inlogarithms, reflects the proportionalincrease in invention value that isassociated with a patent grant.
We extend the base model by allowingthe effect of a patent grant to vary bytechnology area. Specifically, we
introduce interaction termsCopyright 2011 John Wiley & Sons, Ltd.
between the twovariables Gij andOST technologyarea dummy dj, sothat (1) becomes:
ln Vij=Gij+
j(Gijdj)+
X+j+ij,
j =1, . . . ,J 1
Thus the effectof a patent granton an invention intechnology area jis given by +j,which varies bytechnology area.
RESULTS
The estimationbased on Equation(1) is imple-mented using both
InvVal andSalesRev as thedependentvariable. Theresults are reportedin Table 2. Themain result using
InvValas the valuemeasure suggeststhat inventions thatare protected by apatent are 47percent morevaluable thaninventions withouta patent, ceteris
paribus.27 Incomparison, thesame regression
models imple-mented usingSalesRev as thevalue measureyield estimates ofthe patentpremium of 38percent.Interestingly, thepatent premiumestimates pro-duced using
SalesRev as the
dependent variablehave higherstandard errorsthan thecorrespond-ingestimates producedusing InvVal,suggesting that thehistorical revenue-based measure ofvalue is lessprecise.
The coefficients
of the other
explanatory vari-
ables are consistent
with a priori
expectations. The
variables radical
invention and PCT
application
27 We also estimated a
random-intercept model.
The results, availableupon request, are
remarkably consistent
with those from the
fixed-effects model andare omitted for the sake
of brevity.
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Research Notes and Commentaries 1135
Table 2. Estimation results
Dep. variable: ln(InvVal) Dep. variable: ln(SalesRev)coefficient (std. error) coefficient (std. error)
No. of uses 0.4068 0.2471
(0.0460) (0.0548)Other inventions used 0.4931 0.2054
(0.0719) (0.0857)No. inventors in application 0.0789 0.0198
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(0.0457) (0.0544)Radical invention 0.6591 0.3101
(0.0913) (0.1089)PCT application 0.5575 0.3805
(0.1075) (0.1281)Large company 0.3927 1.4052
(0.1752) (0.2088)SME 0.3818 0.9887
(0.1051) (0.1253)Public organization 0.0313 0.4597
(0.2314) (0.2758)Granted 0.4717 0.3790
(0.1047) (0.1248)Intercept 5.4650 4.5903
(0.5341) (0.6366)Adjusted R2 0.208 0.116Number observations 1,790Number tech. classes 28
Notes: (1) Included in all regression models are 19 year dummies, which denote the year in which the patent
application was lodged, and 27 OST technology classification dummies. (2) Significance levels: 10%; 5%;1%.
are both positively associated with value.In addi-tion, the results support the notion
that inventions that have many uses are
positively correlated with higher value,
and that inventions registered to pri-vate
firms (both SMEs and large firms) are
more valuable than those registered to
individuals or to public sector
organizations. It is noteworthy that the
effect of firm size (i.e., the large firm
dummy variable) becomes substantially
larger when we replace InvVal withSalesRevas the dependent variable. This
increase in the firm size effect per-haps
reflects the superior ability of large firms
in product development and
commercialization, and the tendency of
SMEs and individual inventors to rely on
licensing and outright transfer of patents
to appropriate returns.
We extend the base model by allowingthe coef-ficient of grant status to vary by
technology area. The estimation isimplemented using InvVal as thedependent variable, and the results arereported in Table 3. We perform astatistical test of whether the effect of a
patent grant varies by technol-ogy area;the joint test of all interaction terms equalzero gives an F test statistic of 1.3, which
Copyright 2011 John Wiley & Sons, Ltd.
has a p-value of
0.142.28 Thus wefind no evi-dence
to suggest that the
effect of a patent
grant is different
across technology
areas. This is
some-what
surprising given
the empirical
support in other
studies thatsuggests patents
are more valu-able
in pharmaceuticals
and chemicals than
other technology
areas. However,
we note that the
exist-ing literature
also shows some
inconsistencies in
this regard. Forinstance, analysis
by Schanker-man
(1998) finds that
the value of patent
pro-tection in
pharmaceuticals is
less than that in
other technological
fields.
Nonetheless, we
cau-tion that ourresult is likely
caused by the
small number of
observations
within each
technology area.29
28We also performed thesame regressions usingSalesRev as thedependent variable. Theresults, available uponrequest, are similar andare omitted for the sakeof brevity.
29 We alsoestimated the model
using six major OST
technology areas rather
than the 30 technology
area classifications. In
this specification, we
find strong evidence that
the value of a patent
grant varies across
technology areas.
However, this is a much
coarser (and
heterogeneous)
classification of
technology areas.
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J.,32:
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1136 P. H. Jensen, R. Thomson, and J. Yong
Table 3. Estimationresults: effect ofpatent grant, bytechnology area
Dep. variable: ln(InvVal)
No. of uses
Other inventions used
No. inventors in application
Radical invention
PCT application
Large company
SME
Public organization
Granted
G electricaldeviceselectricalengineering
G audiovisual technology
G telecommunications
G information technology
G optics
G analysis, measurement,
control
G medical engineering
G organic fine chemicals
G pharmaceuticals,
cosmetics
G biotechnology
G materials, metallurgy
G agriculture, food
G general processes
G surfaces, coatings
G material processing
G thermal techniques
G basic chemical processing,
petrol
Copyright 2011 John
Wiley & Sons, Ltd. Table 3.(Continued)
Dep. variable: ln(InvVal) Coefficient (std. error)
G environment, pollution(0.6714)0.3961
G mechanical tools(0.8517)0.8348
G engines, pumps, turbines(0.6658)0.2068
G mechanical elements(0.6094)0.8741
G handling, printing(0.6105)
1.0242
G agriculture/food(0.4668)
0.6946machinery
(0.4190)G transport 0.5291
G space technology,(0.4224)0.6602
weapons
(1.5009)G consumer goods & 0.1920
equipment(0.3736)
Intercept 5.1310
(0.5623)Adjusted R2 0.212Number observations 1,790Number technology areas 28
Notes: (1) Included
in the regression are
19 year dummies,
which denote the
year in which thepatent application
was lodged, and 27
OST technology
classification
dummies. (2) The
omitted reference
group for the
interaction terms is
G civil
engineering,
building, mining.
Another interaction
term G
macromolecularchemistry,
polymers is
omitted due to
singularity. (3)
Significance levels:
10%; 5%;
1%.
Theestimated
patent premium
implies that a
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patent increasesthe value of themedian inven-tion by about
A$256,000.30
The results alsohave important
public policy
implications.Since approx-imately 2,000
patents aregranted each yearin Australia, ourresult suggests
that in 2005 thepatent system
provided animplicitsubsidy toinnovators of
about A$4billion. This isapprox-imatelyfive times
larger than thecombined
value of theA$425 million
contributed bythe govern-
ment throughtax incentives(IA, 2007) and
the A$420million viasubsidies,grants, and
procure-ment(ABS Cat.8104.0).
30Given by 0.47/(1
+0#47) (median
patented invention
value).
Strat.
Mgmt. J.,
32: 1128
1138 (2011)
DOI: 10.1002/smj
CONCLUSIONS
This paper sheds new
light on a fundamental
question frequently
asked, but never
definitively answered:
what is the increase in
private value due to the
presence of a patent? We
tackle this question using
a novel empiricalapproach that makes use
of data from a
comprehensive survey of
inventors who applied for
a patent in Australia
between 1986 and 2005.
We use the variation in
patent examina-tion
outcomes to identify the
patent premium. The
results provide strongand robust support for the
existence of a sizeable
patent premium. The
pres-ence of a patent
increases the returns to
an inven-tion by around
40 to 50 percent on
average, regard-less of
how we define value.
While the value of patent
protection is expected to
vary according to
idiosyncratic inventor
and marketcharacteristics
surrounding an invention,
the average effectiveness
reported in this paper
provides a valuable
bench-mark to
technology managers and
IP professionals. This
result should aid firms in
their decisions on the
different appropriation
mechanisms to use as
part of their IP
management strategy.
Further, we also provide
new evidence on the
effectiveness of patenting
by technology area.
We acknowledge that
there are someimportant limitations ofour attempt to estimate
the patent premium.Foremost among theseis that invention value isdifficult to measure. Wehave relied on an
inventor survey to dothis, but we are cog-nizant of the fact thatself-reported
evaluations of inventionvalue can be
problematic. However,
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in the absence of aperfectly functioningmarket for technology(which may never
exist), we have madesome valuable inroadsinto understanding howinventor surveys can be
used to tackle theidentification of the
patent premium. Wealso note that some
recent research hasestablished a strong
statistical relationshipbetween survey-basedmea-sures of inventionvalue and other
measures of valuederived from citationand renewal analysis
(Gambardella et al.,2008). Second, it is
difficult to disentangleinvention quality from
patent value. Ratherthan relying on self-reported proxies ofinvention quality (as we
have done), it may bebetter to rely on
independent evaluationsof the inventions as in
Moser (2007), althoughsuch data are difficult tocome by. Futureresearch on this issue
might consideralternative ways inwhich the underlyingtechnological
characteristics may be
Copyright 2011 John Wiley &Sons, Ltd.
Research Notes and Commentaries 1137
measured. Third, we do
not observe firms
willing-ness to enforce
their patents, which is an
important determinant of
the private returns to
patenting (see Lanjouw1998; Lanjouw and
Schankerman 2001).
ACKNOWLEDGME
NTS
We thank AssociateEditor Tomi Laamanen,two anonymous
referees, Beth Webster,Jim Bessen, AlfonsoGambardella, Georgvon Graevenitz, DirkCzarnitzki, and GeorgLicht for thoughtfulcom-ments on thispaper. Comments andsuggestions fromseminar participants atLudwig MaximiliansUniversity (Munich),
ZEW Mannheim,MERIT (MaastrichtUniversity), and theKatholieke Uni-versityof Leuven are gratefullyacknowledged. Fundingfor this research comesfrom an AustralianResearch Council(ARC) Linkage Grantwith IP Australia(LP0667467).
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