By Christopher J. Ryan, Jr. & Brian L. Frye*
Download a PDF version of this article here
Introduction
Since in the last quarter of the 20th Century, the United
States patent system has been in a state of flux, influencing not only patent
law but the incentives underlying invention and patent ownership. A series of
legislative acts and judicial decisions, beginning in 1980, have affected the
ownership, scope, and duration of patents. In 1980, the Bayh-Dole Act enabled
academic institutions to patent inventions created from federally-sponsored
research.[1] In 1994, Congress
extended the maximum duration of a United States patent from 17 to 20 years for
certain patents, increasing the monopolistic value of patent protection.[2] And in 2011, the
America Invents Act shifted the patent system from a first-to-invent standard
to a first-to-file system.[3] These changes have impacted
all inventors but especially those at academic institutions, where research is
a multi-billion dollar industry; perhaps relatedly, these changes have
coincided with historic increases in patent activity among academic
institutions.
This patent activity is not necessarily unexpected,
inefficient, or objectionable. After all, academic institutions are charitable
organizations and intended to promote the public good of innovation, among
other things. Many academic institutions, especially research universities,
rely on significant federal investment to support research that promotes the
dissemination of knowledge, disclosure of new knowledge, and importantly,
innovation. In theory, the patent system could do even more to encourage
academic institutions to invest far greater resources in innovation.
However, university patent activity has important economic
and normative implications. The patent system uses private economic incentives
to promote innovation. Accordingly, it creates an incentive for universities to
overinvest in patentable innovation and limit access to innovation, in order to
internalize private economic value. This is especially troubling because
universities may use publicly-funded research to generate patentable
innovations for private gain. Thus, concerns about transparency and efficiency arise
when considering the extent from which universities may ultimately derive private
monetary benefit from public investment, especially given that universities
lack the capacity to bring an invention to market.[4] That is, as a non-practicing entity,
in order to internalize the economic value of their research, universities must
acquire patent protection over their inventions. However, because they do not
have the capacity to bring their inventions to market, universities can and do
use public funds to produce research yielding patents that are worthless or,
worse yet, transfer their patents rights to patent assertion entities rather
than practicing entities, producing externalities and inefficiency in the
patent system.[5]
While the purposes of the patent system are manifold, these
sorts of behaviors undercut the argument that patents contribute to innovation.
Thus, there is a founded concern that academic institutions have responded to
patent incentives in ways that may actually limit access to innovation. Yet,
this concern is not the only cause for unease about inefficient responses to
patent incentives.[6] For example, most
of the patent infringement actions heard in a handful of district courts that have
been described as engaging in forum selling—being a friendly forum for cases filed
by patent assertion entities that choose the forum based on its pro-plaintiff
bias.[7] Many observers are concerned that
the concentration of patent assertion activity in certain district courts has
increased the cost of innovation.[8]
Similarly, there is legitimate concern that universities contribute
to cost and inefficiency by: (1) using public funds to support research that
results in often useless patents; or (2) providing the instrumentality for
non-practicing entities to increase the cost of innovation. That is,
universities may participate in driving up the cost of innovation by
aggregating patent protection for inventions that are likely to have little
market value or that they cannot bring to market and must transfer, even to
other non-practicing entities. This article is the first in a series of papers
to investigate the relationship between universities and the patent system. In
particular, this article addresses whether universities can be said to
aggregate patent protection for their inventions systematically or
monopolistically, which may indicate their role in increasing the cost of
innovation. The discussion and results, below, suggests that academic
institutions have responded to patent policy changes not in a manner consistent
with firm behavior, by accruing property rights when incentivized by patent policy
changes to do so, but also by strategically holding out in order to reap
greater monopolistic benefit under anticipated patent regime changes, which may
have exacerbated the problem of increasing the cost of innovation.
I. The Patent System
The purposes of the patent system are several, but the
primary purpose is to promote technological innovation, or rather, to “promote
the Progress of . . . useful Arts, by securing for limited Times to . . .
Inventors the exclusive Right to their respective . . . Discoveries.”[9] While some scholars
have questioned the efficiency of the patent system, and other scholars have
suggested that it may only provide efficient incentives in some industries,
conventional wisdom assumes that it is generally efficient, providing a net
public benefit by encouraging investment in innovation.[10] In any case, while
the patent system has always provided essentially identical incentives to
inventors in all industries, the demographics of patent applicants and owners
have changed over time. Originally, many patent applicants and owners were
individual inventors, but for quite some time, the overwhelming majority of
patent applicants and owners have been both for-profit and non-profit corporations.
An increasing number of those corporate patent applicants and owners are
academic institutions.[11]
A. Academic Patents
Academics have always pursued patents on their inventions
with varying degrees of success. But academic institutions did not meaningfully
enter the patent business until the early 20th century, and even then, they did
so only tentatively.[12] In 1925, the
University of Wisconsin at Madison created the first university patent office,
the Wisconsin Alumni Research Foundation, an independent charitable
organization created in order to commercialize inventions created by University
of Wisconsin professors. Similarly, in 1937, MIT formed an agreement with
Research Corporation, an independent charitable organization, to manage its
patents.[13] Many other schools
followed MIT’s lead, and Research Corporation soon managed the patent
portfolios of most academic institutions.[14]
Before the Second World War, academic institutions engaged
in very limited patent activity, collectively receiving less than 100 patents.
But during the war, many academic institutions adopted formal patent policies,
typically stating that faculty members must assign any patent rights to the
institution.[15] Gradually, some academic
institutions began creating their own patent or “technology transfer” offices.
But by 1980, only 25 academic institutions had created a technology transfer
office, and the Patent Office issued only about 300 patents to academic
institutions each year.[16]
Since then, patent law has increasingly encouraged patent
activity at academic institutions. Until 1968, each federal agency that
provided research funding to academic institutions had its own patent policy.
Some provided that inventions created in connection with federally funded
research belonged to the federal government, others placed them in the public domain,
and a few negotiated institutional patent agreements with academic
institutions, allowing them to own patents in those inventions. In 1968, the
Department of Health, Education, and Welfare’s introduced an Institutional
Patent Agreement, allowing for non-profit institutions to acquire assignment of
patentable inventions resulting from federal research support for which the
institution sought a patent. However, this policy was not uniformly applied. As
such, in 1980, under pressure to respond to the economic malaise of the 1970s, Congress
passed the Bayh-Dole Act, which enabled academic institutions to patent
inventions created in connection with federally-funded research.[17] Specifically, the
Act provided that, with certain exceptions and limitations, “a small business
firm or nonprofit organization&rdquo could patent such inventions, if the
organization timely notified the government of its intention to patent the
invention and gave the government the right to use the invention.[18] The Act placed
certain additional requirements on nonprofit organizations, providing that they
could only assign their patents to an organization whose primary function is to
manage inventions. Additionally, the nonprofit organizations must share any
royalties with the inventor and use the earned royalties only for research or
education. The limitation on assignment was intended to encourage academic
institutions to assign their patents to charitable organizations, like Research
Corporation, but in practice, it led many of them to compete over federal funds
only to produce patentable inventions with little value or to assign their
patents to patent aggregators or &ldquopatent assertion entities.&rdquo[19]
At about the same time, the scope and duration of patent
protection began to expand. First, the Supreme Court explicitly expanded the
scope of patentable subject matter to include certain genetically modified
organisms and computer software.[20] Then, in 1982,
Congress created the United States Court of Appeals for the Federal Circuit,
which has exclusive jurisdiction
over patent cases and has adopted consistently pro-patent positions.[21] In 1984, Congress
expanded the patentability of pharmaceuticals.[22] In 1994, Congress
ratified the Uruguay Round of negotiations which created the World Trade
Organization and extended the maximum duration of a United States patent from
17 years from the date of issue to 20 years from the filing date, marginally increasing
the value of a patent.[23] And in 2011,
Congress passed the Leahy-Smith American Invents Act, which amended the Patent
Act by, inter alia, moving from a
first-to-invent to a first-to-file patent system.[24]
All of these changes in patent protection caused an increase
in overall patent activity, across all types of inventors.
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That said, academic institutions
played a role in the growth of nationwide patent activity directly related to
the dramatic increases in patent applications and grants between 1980 and 2010.
In response to these policy changes, many universities adopted a research model
under which federal grants and other public funds were directed at the
development of patentable inventions and discoveries, enabling the universities
to obtain patents and claim a private benefit. By 1990, more than 200 academic
institutions had created technology-transfer offices, and the Patent Office was
issuing more than 1,200 patents to academic institutions each year.[30] In 1995,
universities received over $15 billion in research grants from the federal
government, a figure that would more than double—$35.5 billion—by 2013.[31]
Ironically, while some of the patents granted to academic
institutions proved extremely valuable, the overwhelming majority of them are
worthless. Most of the technology-transfer offices created by academic
institutions produce little revenue when compared with expenditures, and many
actually lose money.[32] In 2013, the
median value among universities reporting revenues from their technology
transfer offices was a mere $1.57 million; moreover, less than 1 percent of all
patent licenses for patents held by universities and their technology transfer
companies generate revenues reaching or exceeding $1 million.[33]
B. An Economic View of Patents
The prevailing theory of patents is the economic theory,
which holds that patents are justified because they solve market failures in
innovation caused by free riding. In the absence of patents, inventions are
“pure public goods,” because they are perfectly non-rivalrous and nonexcludable.[34]
Neo-classical economics predicts market failures in public goods, because free
riding will prevent marginal inventors from recovering the fixed and
opportunity costs of invention.[35] Under the economic
theory, patents solve market failures in innovation by granting inventors
certain exclusive rights in their inventions for a limited period of time,
which provide salient incentives to invest in innovation.[36]
Patents may also cause market failures by granting
inefficient rights to inventors and imposing transaction costs on future
inventions.[37] In theory, patent
law can increase net economic welfare by granting patent rights that are salient
to marginal inventors and encourage future inventions. In practice, however,
patent law may grant rights that are not salient to marginal inventors and
discourage future inventions. For example, patent law may cause market failures
by discouraging marginal inventors from investing in innovation.
The American patent regime has precipitated “arms race” and
“marketplace” paradigms, both of which elicit firm behavior.[38] In the first
instance, the benefits of patent protection incentivize innovators to aggregate
under the auspices of the firm model, thereby reducing the marginal cost to
each innovator of producing patentable technology. The marketplace paradigm
encourages innovation, or at least innovation likely to result in patent
protection. Both paradigms, however, are subject to the results of the perverse
incentives that the patent regime provides, specifically that of patent
stockpiling and the rent-seeking behaviors of non-practicing and patent
assertion entities.[39]
The right to exclude is perhaps the most important stick in
the bundle of patent protection rights and may have the effect of stifling
rather than promoting innovation.[40] As the ubiquity of non-practicing
and patent assertion entities in the patent market become commonplace, patent
holdup, patent litigation, and patent thickets are common features of the
modern patent marketplace.[41]
C. University Responses to Patent Policy Incentives
From the perspective of the theoretical
literature, innovation depends upon innovators receiving the benefits of their
innovation; the regime that allocates these benefits to the innovator and
thereby incentivizes innovation is the most efficient.[42]
For universities, a majority of which relied on federal funding to support
research and development of patentable innovation during the 20th Century, the
patent regime did not substantially encourage universities’ entry into the
patent market until the passage of the Bayh-Dole Act in 1980.[43] Descriptive research
in this area suggests that the Bayh-Dole Act—which allowed universities to
patent inventions developed in connection with federally-funded
research—increased the number of university participants in the patent market.[44] Some scholars have
also attributed university technology transfer and patent title aggregation as
being rooted in the Bayh-Dole Act.[45]
However, these developments point to the fact that
universities may be responding to policy interventions—such as the extension of
the duration of patents in 1995 and anticipation of the America Invents Act—and,
in turn, affecting the patent landscape.[46] Examples of these
responses include shifting investment in research and development toward
innovation sectors that are more likely to receive patent protection,
particularly those with high renewal rates, and because the US Patent and
Trademark Office (PTO) derives more revenue from these sectors, it has the
incentive to grant applications from high renewal rate sectors.[47] Additionally,
researchers have noted that the patent regime does not privilege economic
development through technological transfer, and may account for both the
increase in patent litigation from non-practicing entities, such as
universities, as well as rise in rent-seeking behaviors in patent licensing.[48]
University technology transfer forces academic institutions
to make uncomfortable decisions about licensing and litigation.[49] Many academic
institutions have responded to this ethical dilemma by assigning their patents
to patent assertion entities in order to obscure their relationship to those
patents and avoid the obligation to enforce them.[50] Despite
universities’ status as charitable organizations, as patent owners they have a
financial incentive to support their research and development enterprises by
competing for federal grants, even if it results in patentable inventions for
which there is little economic value and limit the use of the knowledge they
generate by securing patent rights regardless of whether these inventions have
economic value. Either of these scenarios exacerbates the cost of innovation.[51]
D. The University as a Firm
In response to the changes in the
patent law system between 1980 and 2011, especially the Bayh-Dole Act, academic
institutions increasingly adopted a research funding model under which federal
research grants and other public funds were focused on the development of
patentable inventions.[52] As previously
observed, the total number of patents granted by the Patent Office steadily
increased, and so did the percentage of those patents granted to academic
institutions.[53] Soon, participants
in the patent law system began expressing concerns about entities that
decreased the efficiency of the patent system by merely owning and asserting
patents, rather than practicing them. Of course, academic institutions that own
patents are non-practicing entities almost by definition, as they exist to
create and disseminate knowledge, not produce commercial products.[54] Even more
troubling, many academic institutions assign most or all of their patents to
patent assertion entities, the paradigmatic patent trolls. As a result, the way
that academic institutions use patents presents a risk of creating “patent thickets
that entangle rather than encourage inventors,” which is in tension with the
charitable purpose of those institutions.[55]
But how did these patent thickets sprout from the soil of
the university? The behavioral theory of the firm may help explain why academic
institutions responded to incentives created by changes in this way. Unlike
neoclassical economics, which uses individual actors as the primary unit of
analysis, the behavioral theory of the firm uses the firm itself as the primary
unit of analysis. As a consequence, the behavioral theory of the firm provides
better predictions of firm behavior with regard to
output and resource allocation decisions.
The field of organizational economics emerged in 1937, when
Ronald Coase observed that firms emerge when the external transaction costs
associated with markets exceed the internal transaction costs of the firm.[56] Coase’s theory of
the firm was revolutionized in 1963, when Richard Cyert
and James March provided a behavioral theory of the firm, observing that firms
consist of competing coalitions with different priorities responding to
different incentives.[57]
In the context of funded
research, university patent activity can be read as the result of strategic
firm decision-making regarding patent output and resource allocation decisions.
In fact, the way that patent policy has bent toward
rewarding university patent activity through conferral of rights is a direct
result of lobbying and decision-making efforts by these universities with
lawmakers—evidence of the bidirectional interaction between universities and
external influences.[58] The behavioral theory of the firm suggests that
academic institutions have responded to incentives created by patent law in a
manner consistent with firm behavior.[59] Though heterogeneity of university patent
activity does exist, at most intensive research
universities, where decisions are made two ways—with executive administrators
setting strategic goals for research which are then implemented at lower
management levels—intense competition exists between intensive research
universities to vie for patent rights and thus profit maximization.
Increasingly, these universities have centralized and ceded
title in patents to their foundations and technology transfer offices.[60] As non-practicing
entities, universities bear the transaction costs of developing patented
inventions, but they transfer the transaction costs of bringing the invention
to market to intermediaries—and get paid for doing so.[61] As a consequence,
the goal of a university is to satisfice rather than maximize results; firms
typically focus on producing good enough outcomes, rather than the best
possible outcomes, as a function of compromise among internal coalitions with
different priorities.
Thus, one could view increased
activity immediately after the implementation of a policy conferring greater
patent rights not as a random but as a very rational, profit-maximizing response.
However, this activity presents issues when the firm actor is a university.
Because academic institutions are necessarily non-practicing entities with
strong incentives to assign their patents to patent assertion entities in order
to extract their economic value—yet the research from which a patentable
invention derives is funded largely by public, federal investment—the gray area
which universities occupy through their patent activity makes clear that, while
they might not be “patent trolls” as Mark Lemley
argues, they certainly feed the patent trolls.[62]
This article aims to provide
evidence of that very point. As scholars, like Jacob Rooksby,
have observed: “[t]he accumulation, use, and
enforcement of intellectual property by colleges and universities reflects
choices to engage in a system that . . . takes knowledge and information that
is otherwise subject to . . . public use and restricts it, by attaching private
claims to it.”[63] The result of these restrictions produced by
universities’ firm behavior through their patent activity and transfer carries
real consequences for innovation. While the effects of these consequences are
uncertain, the inputs are fairly clear: the prospect of wealth-maximizing
motivates activity in university technology transfer.[64] Yet, the relationship between universities’
wealth-maximizing foray into patent acquisition and its connection with patent
policy changes, as well as the explanatory theoretical framework of the
behavioral theory of the firm for this very sort of activity, have not been
established heretofore. In the sections that follow, this article makes this
connection with supporting empirical analysis.
II. Empirical Analysis
A. Research Questions
While academic institutions have responded to patent
incentives in a manner consistent with firm behavior, the optimal firm response
does not necessarily produce the optimal social outcome. Organizational
economics predicts that firms will respond to external incentives by
satisficing results consistent with the consensus of internal coalitions. As a
consequence, firms may or may not respond to patent incentives in a manner
consistent with the patent system’s goal of maximizing innovation. It follows
that if academic institutions exhibit firm behavior in relation to patent incentives,
they may satisfice internal coalitions at the expense of social welfare. In the
context of university patent activity, this behavior could take the form of the
pursuit of patent acquisition not because it is a wealth-maximizing or an
economically efficient activity but simply because the regulatory conditions
are preferable to pursue patent acquisition.
This study asks whether and how changes in patent law have
affected the patent activities of academic institutions. Specifically, it asks
two questions:
To what extent do
universities change their patent acquisition strategy in response to changes in
patent law?
To what extent do
different kinds of universities respond differently to changes in patent law?
To answer these questions, this study analyzes data on the
population of academic institutions that were granted one or more patents
between 1969 and 2012 in order to determine the impact of policy changes on
university patent activity over this time.[65] Notably, while
future papers in this series may engage with such questions, this article does
not determine whether academic institutions have responded to changes in patent
law in a way that increases or decreases net social welfare. But it can help
explain how academic institutions have responded to patent incentives and
whether their responses are consistent with firm behavior, laying the
foundation for future exploration of whether and how universities may play a
role of increasing costs to innovation.
B. Data
This study relies primarily on a valuable, albeit limited,
dataset compiled by the PTO, which records the total number of patents granted
per year to each educational institution in the United States between 1969 and
2012.[66] Because of
limitations with this data—for example, the data contain only one measured
variable, the total number of patents granted to an institution in a calendar
year—this dataset had to be merged with other datasets to include more
explanatory variables for each institution observation over the same length of
time. Specifically, this study relied on the available data from the
Classifications for Institutions of Higher Education, a Carnegie Foundation
Technical Report, which was produced in 1973, 1976, 1987, 1994, 2000, 2005, and
2010.[67] Because the first
three published Carnegie Classification reports—1973, 1976, and 1987—have not
been digitized, the use of this data required the authors to hand-code the
classification for each observation utilized in the analytical sample.
From the merged dataset, consisting of the full population
of higher-education-affiliated institutions that had been granted a patent
between 1969 and 2012, an analytical sample had to be drawn from this
population to focus on the main university participants in the patent market:
research universities; doctoral-granting universities; medical, health, and
engineering specialized institutions; and to a lesser extent, comprehensive
universities; liberal arts colleges; and other specialized institutions,
including schools of art, music, and design, as well as graduate centers,
maritime academies, and military institutes.[68] Due to the paucity
of observations in the following subgroups, 31 observations from two-year
colleges, corporate entities, and spin-off research institutes were dropped
from analysis, preserving 591 university observations. Additionally, given that
the University of California system does not differentiate patent activity by
institution, choosing instead to have reported patent activity in the aggregate
in the PTO dataset, it was removed from the analytical sample.
Because the Carnegie Classifications attribute most
administrative units to the parent institution, this study took the same
approach, collapsing administrative units, foundations, other organizational
entities, and former institutions on the current parent institution. However,
each observation that received a separate classification from its parent
institution in the Carnegie Classifications was preserved as a separate
observation from the parent institution.[69] The process of
collapsing on parent institution reduced the total number of institutions
observed from 590 to 366 school observations, each with 44 year observations.
C. Limitations
It should be noted that the data are limited by two
important factors: (1) a lack of explanatory covariates; and (2) a small sample
of higher education institutions relative to the overall population of higher
education institutions. In the first instance, because the year observations
for each institution comprise a 44-year span, it is impractical to match each
institution-year observation with rich, explanatory covariates over that time.
Not even the Integrated Postsecondary Education Data System (IPEDS) collected
comprehensive data on universities before 1993. As such, the Carnegie
Classifications serve as a proxy for more detailed information about each
institution during a span of years for which data is virtually impossible to
find. Given that the Carnegie Classifications categorizes schools on the basis
of its federal funding for academic research, production of doctorates,
institutional selectivity, enrollment, and degree programs, the Carnegie
Classification for each school makes an ideal proxy for a more complete set of
explanatory covariates.
As for the size of the analytical sample relative to the
population of institutions of higher education receiving a Carnegie
Classification since 1973, this population consisted of 1,387 universities—not
counting theological seminaries, bible colleges and two-year colleges—while the
analytical sample used in this study comprises 366 universities—26.39 percent
of the population. However, because this study analyzes university patent
activity relative to patent policy change, the analytical sample size is
necessarily limited to only those universities that have been granted a patent.
As such, the analytical sample used in this study can be viewed as representing
a nearly complete picture of the population of academic institutions that have
successfully engaged in patent activity between 1969 and 2012.
D. Descriptive Results
Research universities and doctoral-granting universities
dominate patenting activity and receive an overwhelming majority of patents
granted to academic institutions.
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Table_Body_2.png)
However, just under half of the analytical sample is
comprised of research universities and doctoral-granting universities, which
the Carnegie Classifications consider separate but component parts of its
doctoral-granting institution category. The average patent totals for research
universities dominate all other classification of institution and are over four
times as large as the average patent total for doctoral-granting universities.
While comprehensive universities account for the largest proportionate
classification in the sample, the average patent total for comprehensive
universities is among the smallest in the analytical sample. In fact, it is
followed only by the smallest classification in proportion and average patent
total—other specialized institutions. Medical, health, and engineering schools,
while small in number, maintain considerable average patent totals, nearly
doubling the patent totals of liberal arts colleges which account for about the
same proportion of institutions analyzed in the analytical sample. Across all
categories, universities that entered the patent market before the passage of
the Bayh-Dole Act buoy patent totals. As such, given their high level of patent
activity, the spline regression model results below will especially highlight
early entrants as well as research universities, doctoral-granting
universities, and medical, health, and engineering schools.
E. Research Method and Model
This study employs a spline regression approach to identify
how universities reacted to changes in patent policy at key points in time
between 1969 and 2012. This method is very similar to using a
difference-in-differences approach to compare the activity differences between
two series of years separated by a point, or knot, in
time, where the intercept and slope vary before and after the knot.[70] Spline regression
modeling necessitates that the location of the knots be set a priori in order to produce estimates
of the non-linear relationship between the predictor and response variables.
Doing this requires defining an indicator variable, using it as a predictor,
but also allowing an interaction between this predictor and the response
variable.[71] The analytical
model employed in this study is as follows:
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Image_Body_1.png)
Thus, the expectation of the total number of patents granted
to school i
(PATi)
in year t (yrt) is a function of:
(1) a vector of the factors attendant to school i in year t as proxied by its Carnegie
Classification (CCit);
(2) a dummy variable for whether or not the school engaged in patent activity
before 1980 (EEi);
(3) a school fixed effect (Si);
(4) the year indicator variable (yrt); (5) a dummy variable for the location of
the indicator year between the critical spline knots (kc, kc-1);
(6) the interaction of the indicator year and the dummy variable for its
location between the critical spline knots; and (7) the random error term (eit).
Spline knots were set at 1981 (k1), 1996 (k2),
and 2010 (k3) to account
for: (1) the passage of the Bayh-Dole Act in 1980, which incentivized
universities to engage in patent activity by giving them title to inventions
produced from federally-funded research; (2) the expansion of the patent
protection duration from seventeen to twenty years in 1995; and (3) the
introduction of the America Invents Act, which would pass into law in 2011 and
change the right to the grant of a patent from a first-to-invent standard to a
first-inventor-to-file standard.[72] The final spline
knot was not set at 2012 for two reasons. First, because 2012 was the final
year of observation in the data set, the spline regression model would not
tolerate a post-2012 slope prediction without post-2012 data. Additionally,
setting the knot at 2012 would not account for the possibility that
universities may have begun reacting to the policy before the effective date of
the policy change, as this particular policy change was in the offing for several
years before its eventual passage.
From a theoretical perspective, the decision to specify the
analytical model with year-after-the-intervention spline knots is defensible on
the grounds that it allows an additional calendar year for universities to
react to the policy intervention. However, to test the sensitivity of the model
and the decision to set the spline knots one year after the policy
intervention, the model was specified in multiple formats to include spline
knots on the year of the policy intervention, one year before the policy
intervention, and two years before the policy intervention. This sensitivity
test was undertaken to ensure that the differences in slopes and intercepts
throughout year observations were not evidencing a secular exponential curve.
Although the year-of-the-intervention slopes and intercepts bore marginal
similarities to the results discussed below, which are modeled on
year-after-the-intervention spline knots, there were significant differences
between the year-after-the-intervention slopes and intercepts reported below
and those for year-prior- and two-years-prior-to-the-intervention. Thus, the
year-after-the-intervention spline knot specification used in this study is
preferable to other specifications, because it rules out the potential threat
of secular trends.
F. Empirical Results
To analyze the effect of the patent
policy changes on university patent activity, the regression model provided in
the section above was used to calculate both the intercept before and after the
policy intervention as well as the slope before and after the policy
intervention. Given that the model employed a fixed effect by institution, the
regression results reported below can be interpreted as providing an estimate
of the intercepts (I) and effects, or slopes (E) pre-intervention, as well as
the marginal intercept shift and slope change after the intervention for
universities in the analytical sample. In the first regression table, Table 2,
the results compare early entrants to non-early entrants, demonstrating stark
differences between the two groups.
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Table_Body_3.png)
Notably, the early entrants engaged in patent activity at a
modest but steady rate, adding minimally to yearly patent totals and averaging
2.67 patents granted annually by 1980. In 1981, the intercept at this spline
knot jumped by an average of nearly one and a half patents in a single year,
with an accelerated slope adding to the average growth by three-quarters of a
patent every year thereafter to 1994. By 1995, the intercept spiked again, this
time by an additional 4.76 patents granted annually for early entrants, with
even further accelerated slope gains to 2010. Finally, in 2011, thought they
came close, the estimates lacked statistical significance at the p<0.05
level but indicated an added intercept bump and positive explosion in slope.
The non-early entrant estimates, though mostly consistent with the statistical
significance of the early entrant estimates for the same periods, pale by
comparison. The direction and statistical significance of the results for all
early entrants are fairly consistent with estimates for the effect of policy
changes at the 1981, 1995, and 2011 spline knots among early entrants in the
research and doctoral-granting universities classifications.
The results provided in Tables 3 and 4 describe patent
activity among early entrant research and doctoral universities, respectively.
As Table 3 indicates, research universities achieve the greatest orders of
magnitude of increased patent grants at the regression spline knots. Slope
changes among this group are statistically significant (or very closely
approaching significance in the case of the 1995 spline), illustrating the
differential response within group to the various policies while mitigating the
influence of secular trends.
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Table_Body_4.png)
Doctoral-granting institutions
maintained relatively flat—until 2011, when the slope dramatically and
significantly changed—but exhibit consistent growth in patent activity around
the spline knots.
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Table_Body_5.png)
Table 5 compares the activity among these two early entrant
groups in terms of patents granted. Before the passage of the Bayh-Dole Act in
1980, research universities engaged in steady, relatively flat rates of patent
activity, averaging about four patent grants per year. In 1981, the intercept
for research universities increased by an average of about two patent grants,
significantly adding an average of more than one patent grant per year
thereafter. In 1995, the research university intercept jumped over seven units
but had a relatively stable slope before and after this time. While the limited
data after 2011 do not tolerate statistical significance, research universities
and doctoral-granting universities may have undergone another upward intercept
shift, but more importantly, may have also undertaken a momentous slope shift,
relative to all other slope shifts observed by category, in the years since
2011.
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Table_Body_6.png)
Among early entrant comprehensive universities, only one
spline knot approaches statistical significance—the knot at 1995—but even it
represents a modest increase from preceding patent activity.
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Table_Body_7.png)
Likewise, the statistical
significance of the specialty institutions’—including primarily medical,
health, and engineering schools—spline knot estimates is only present around
the 1981 spline knot. Yet, the results clearly indicate a considerable bump at
the 2011 spline knot, despite the lack of statistical significance at that
spline or the 1995 spline.
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Table_Body_8.png)
It is likely that these two groups of
institutions—comprehensive universities and specialty institutions—demonstrate
relatively little change with the passage of new patent policy for a couple of
reasons. First, their numbers are few, especially when compared with research
and doctoral-granting universities. Second, and perhaps more important, their
missions are very different from research universities.[73] Thus, these
universities may not respond to the same incentives in the same way as research
and doctoral universities simply because research resulting in a patent may not
be an institutional priority for many of the schools in the comprehensive and
specialty institution categories.
Notwithstanding these results for the comprehensive
universities and specialized institutions, the statistically significant slope
and intercept differentials, while controlling for explanatory covariates,
indicate the strong presence of university patent activity responses among
research and doctoral universities to patent regime changes at the years
represented by the spline knots. There is considerable evidence that, among
these two categories of universities, the passage of the Bayh-Dole Act in 1980
provided considerable incentive, and elicited considerable effect, on the
engagement of major universities in patent acquisition. The shrinking but still
significant effect at the 1995 policy intervention, which extended patent
duration to 20 years in some but not all patents, may be direct evidence that,
because this policy change was not as major a shift in the conferral of rights
to universities, it did not elicit the same magnitude of response. However, the
anticipation of the passage of the America Invents Act triggered a massive
shift in university patent acquisition, perhaps because universities were
concerned that their inventions could be scooped under the new
first-inventor-to-file standard.
This behavioral pattern suggests a rational,
profit-maximizing response—the result of strategic
firm decisions regarding patent output and resource allocation decisions—to
increase patent activity immediately after the implementation of a policy
conferring greater patent rights. However, because universities do not bring
these patents to market themselves, and so many of these patents are sold to
patent assertion entities, the increase in university patent activity has the
effect of contributing substantially to the patent thicket.
Conclusion
This study asks whether universities exhibit patent activity
consistent with firm behavior. The results of the spline regression models
suggest that research universities and doctorate-granting universities increase
their patent activity in direct response to incentives created by changes in
patent law but may also strategically hold on to pursue patentable inventions
until after the policy provides them more robust patent rights or protection.
Most notably, across all university types, the Bayh-Dole Act accelerated patent
activity once universities could take title in inventions produced from
federally-funded research. As illustrated in the regression models and Figure 1
in the Appendix, this Act may have even incentivized research universities to
disengage in patent activity prior to, and scale up patent activity just after,
the passage of the act, in anticipation of the benefit that would be conferred
upon them once the act had passed into law. As the patent protection duration
expanded in the mid-1990s, the growth of patent activity at most universities
in the analytical sample increased marginally, indicating another firm response
to the patent law regime changes. Finally, preliminary results and the figures
in the Appendix indicate that the anticipation of the America Invents Act may
have had the largest impact in the rate of patent activity to date, evidence of
a university patent activity response to protect current research against a
more liberalized granting process.
These responses, evincing a move toward patent aggregation
by universities, may have lasting impact not only on the patent marketplace but
also on innovation. Yet, patent aggregation, in and of itself, is not
necessarily problematic. However, the symptoms of patent aggregation, such as
patent hold-up and rent-seeking licensing behaviors, are detrimental to the
promotion of innovation. Moreover, competition for federal funds that leads to
the production of patentable technology of little economic value could evince
another market inefficiency to which universities may substantially contribute.
This study—the first in a series investigating how
universities make decisions about their intellectual property, and whether
these decisions redound to the public good—demonstrates that research
universities, doctoral granting institutions, and specialized institutions
respond strategically to patent policy changes in ways that carry profound
consequences for innovation and the public good. It is clear that changes to
patent policy are necessary to incentivize universities to reap the benefits of
research and development of patentable technologies while promoting innovation.
* * *
Appendix
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Image_Body_3.png)
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Image_Body_4.png)
![X](/wp-content/uploads/2018/01/NYU_JIPEL_Vol-7-No-1_2_Frye_AnEmpiricalStudy_Image_Body_5.png)
Patent and Trademark Law Amendments (Bayh-Dole) Act, Pub. L. No. 96-517, 94
Stat. 3015, 3019 (1980).
See Uruguay Round Agreements Act, Pub. L. No. 103–465,
108 Stat.
4809, 4984 (1994)
(codified at 35 U.S.C. § 154(a)(2) (1994)).
See generally Stuart W. Leslie, The Cold War and American Science: The
Military-Industrial Academic Complex at MIT and Stanford (1993); Christopher P. Loss, Between Citizens and the
State: The Politics of American Higher Education in the 20th Century
224-25 (2012).
See generally David Mowery, et Al., Ivory Tower and Industrial Innovation:
University-industry Technology Transfer before and after the Bayh-Dole Act
(2015) (noting the trend of universities to transfer patent rights to patent
assertion entities in recent years); Donald S. Siegel, David Waldman &
Albert Link, Assessing the Impact of
Organizational Practices on the Relative Productivity of University Technology
Transfer Offices: An Exploratory Study, 32 Research Pol’y
27 (2003) (analyzing productivity in university technology transfer offices and
finding that many are only successful at litigating infringement, not bringing
the technology to market); Matkin, Technology Transfer and the University
(1990) (exploring university patent transfer after the Bayh-Dole Act).
For instance, the Supreme Court recently limited the scope of patent venue in
its unanimous decision in TC Heartland v.
Kraft Foods, which was motivated by flagrant “forum selling” in the
district courts. TC
Heartland vs. Kraft Foods Group Brands, 137 S. Ct. 1514 (2017). For the Federal
Circuit’s decision, which was reversed by the Supreme Court, see TC Heartland vs. Kraft Foods Group
Brands, 821 F.3d 1338 (Fed. Cir. 2016). Forum selling is an issue many scholars
have identified as increasing the costs to innovation. See, e.g., Brian L. Frye & Christopher J. Ryan Jr., Fixing Forum Selling, 25 U. Miami Bus. L. Rev. 1 (2017); Gregory
Reilly & D. Klerman, Forum Selling, 89 S. Cal L.
Rev. 241 (2016); Chester S. Chuang, Offensive
Venue: The Curious Use of Declaratory Judgment to Forum Shop in Patent
Litigation, 80 Geo. Wash. L. Rev. 1065
(2011); Elizabeth P. Offen-Brown, Forum Shopping and Venue Transfer in Patent
Cases: Marshall’s Response to TS Tech
and Genentech, 25 Berkeley Tech. L.J.
61 (2010); Yan Leychkis, Of Fire Ants and Claim Construction:
An Empirical Study of the Meteoric Rise of the Eastern District of Texas as a
Preeminent Forum for Patent Litigation, 9 Yale
J.L. & Tech. 194 (2007).
[7] See, e.g., Mark Lemley, Where to File
Your Patent Case 4-27 (Stanford Public Law, Working Paper No. 1597919,
2010), http://law.stanford.edu/wp-content/uploads/sites/default/files/publication/260028/doc/slspublic/ssrn-id1597919.pdf; Li Zhu, Taking Off: Recent Changes to Venue Transfer
of Patent Litigation in the Rocket Docket, 11 Minn. J.L. Sci. & Tech. 901 (2010); Alisha Kay Taylor, What Does Forum Shopping in the Eastern
District of Texas Mean for Patent Reform, 6 Intell. Prop. L. 1 (2006).
See, e.g., Sara Jeruss,
Robin Feldman & Joshua Walker, The
America Invents Act 500: Effects of Patent Monetization Entities on US
Litigation, 11 Duke L. & Tech.
Rev. 357 (2012); Tracie L. Bryant, The
America Invents Act: Slaying Trolls, Limiting Joinder, 25 Harv. J.L. & Tech. 697 (2011).
U.S. Const. art. I, § 8, cl. 8. See also,
A Brief History of Patent Law of the
United States, Ladas & Parry,
http://ladas.com/a-brief-history-of-the-patent-law-of-the-united-states-2/
(May 7, 2014). In this article, the term “patent” is used to refer exclusively
to utility patents. While the United States Patent and Trademark Office also
issues design patents and plant patents, and the United States Code provides
for protection of vessel hull designs and mask works, both of which resemble
design patents, all of these forms of intellectual property are outside the
scope of this article.
See, e.g., James Bessen & Michael J. Meurer, Patent Failure (2008) (questioning the
efficiency of the patent system); William W. Fisher, The Growth of Intellectual Property: A History of the Ownership of
Ideas in the United States, in Eigentum im internationalen Vergleich
255-91 (1999) (decrying the antitrust implications of intellectual property
protection at the exclusion of innovation); Dan L. Burk & Mark A. Lemley, Is Patent Law
Technology-Specific?, 17 Berkeley
Tech. L.J. 1155 (2002) (observing that the patent system seems to
provide efficient incentives in some industries, but not others); but see, e.g., Robert P. Merges, Justifying Intellectual Property (2011)
(concluding that the patent system is broadly justified).
Research Corporation was formed in 1912 by Professor Frederick Cottrell of the
University of California to manage his own inventions, as well as those others
submitted by faculty members of other educational institutions. See Frederick Cottrell, The Research Corporation, an Experiment in
Public Administration of Patent Rights, 4 JIndust. & Engineering Chemistry 846
(1912).
[15] By 1952, 73 universities had
adopted a formal patent policy. By 1962, 147 of 359 universities that conducted
scientific or technological research had adopted a formal patent policy, but
596 universities reported that they conducted “little or no scientific or
technological research” and had no formal patent policy. American Association
of University Professors, American
University Patent Policies: A Brief History, https://www.aaup.org/sites/default/files/
files/ShortHistory.pdf (last visited Oct. 23, 2017).
This increase in patent activity at universities between 1968 and 1980 is
almost certainly a response to the Institutional Patent Agreement. See Rooksby, supra note 11,
at 130-35; American Association of University Professors, supra note 15.
Patent and Trademark Law Amendments (Bayh-Dole) Act, Pub. L. 96-517, 94 Stat.
3015, 3019 (1980).
35 U.S.C. § 202(c)(7) (2011).
See Mark A. Lemley,
Are Universities Patent Trolls?, 18 Fordham Intell. Prop.
Media & Ent. L.J. 611 (2008). But
see Jonathan Barnett, Has the Academy
Led Patent Law Astray? Berkeley Tech.
L.J. (forthcoming 2017), https://ssrn.com/abstract=2897728.
See Diamond v. Chakrabarty,
447 U.S. 303 (1980) (holding that patentable subject matter included
genetically modified organisms); Diamond v. Diehr,
450 U.S. 175 (1981) (holding that patentable subject matter included certain
kinds of computer software); Patent and Trademark Law Amendments Act, Pub. L.
No. 96-517, 94 Stat. 3015 (1980) (amending 35 U.S.C. § 301 and allowing
universities to take title in the patentable results of funded research).
See Federal Courts Improvement Act,
Pub. L. No. 97-164, 96 Stat. 25 (1982) (creating an appellate-level court, the
U.S. Court of Appeals for the Federal Circuit, with the jurisdiction to hear
patent cases).
See Drug Price Competition and Patent
Term Restoration Act, Pub. L. No. 98-417, 98 Stat. 1585 (1984) (enabling
generic pharmaceutical companies to develop bioequivalents
to patented innovator drugs).
See Uruguay Round Agreements Act,
Pub. L. No. 103–465, 108 Stat.
4809, 4984 (1994)
(codified at 35 U.S.C. § 154(a)(2)).
See United
States Patent and Trademark Office Patent Technology Monitoring Team, U.S.
Patent Statistics Chart, Calendar Years 1963 – 2015 (2016), https://www.uspto.gov/web/offices/ac/ido/oeip/taf/us_stat.htm.
Id.
Id.
[29] Id.
Association of University Technology
Managers (AUTM) STATT Database, www.autm.net/resources-surveys/research-reports-databases/statt-database-%281%29/.
See Rooksby, supra note 11,
at 139-50. See also Joseph Friedman
& Jonathan Silberman, University
Technology Transfer: Do Incentives, Management, and Location Matter?, 28 J. Tech. Transfer 17 (2003); Mowery,
et. Al., supra note 5,
at 24-40.
See Francis M. Bator, The Anatomy of Market Failure, 72 Q. J. Econ. 351, 377 (1958).
See, e.g., Kenneth J. Arrow, Economic Welfare and the Allocation of
Resources for Invention, in Readings
in Industrial Economics, 219-36 (1972); Francis M. Bator, The Anatomy of Market Failure, 72 Q. J. Econ. 351 (1958); Charles M. Tiebout, A Pure
Theory of Local Expenditures, 64 J.
Political Econ. 416 (1956).
Because the benefits of patent protection disincentivize
the inventor form further innovating the patented invention, patent law can be
said to discourage innovation. This is because—from the time the invention is
granted a patent—the inventor’s costs are sunk, meaning that the inventor must
incur new development costs and secure a new patent in order to innovate under
the patent law regime. See id. at
38-39.
See generally Colleen V. Chien, From Arms Race
to Marketplace: The Complex Patent Ecosystem and Its Implications for the
Patent System, 62 Hastings L. J.
297 (2010).
Id. See also Thomas L. Ewing, Indirect Exploitation of Intellectual
Property Rights by Corporations and Investors, 4 Hastings Sci. & Tech. L. J. 1 (2011); but see David L. Schwartz & Jay P. Kesan, Analyzing the
Role of Non-Practicing Entities in the Patent System, 99 Cornell L. Rev. 425 (2014) (arguing that
the debate over non-practicing entities should be reframed to focus on the
merits of the lawsuits they generate, including patent system changes focusing
on reducing transaction costs in patent litigation, instead of focusing solely
on whether the patent holder is a non-practicing entity); Holly Forsberg, Diminishing the Attractiveness of Trolling:
The Impacts of Recent Judicial Activity on Non-Practicing Entities, 12 Pitt. J. Tech. L. & Pol’y
1 (2011) (centering on the difficulties faced by legislators in attempting to
solve the patent troll problem and turns to the recent judicial activity
related to patent law allowing for individually-focused, closely tailored
analysis is examined with an evaluation of four recent court decisions and
resulting changes to the patent system).
See Daniel A. Crane, Intellectual Liability, 88 Tex.
L. Rev. 253 (2009). See also
James Boyle, Open Source Innovation,
Patent Injunctions and the Public Interest, 11 Duke L. & Tech. Rev.
30 (2012) (noting that open source innovation is unusually vulnerable to patent
injunctions); John R. Allison, Mark A. Lemley &
Joshua Walker, Extreme Value or Trolls on
Top? The Characteristics of the Most-Litigated Patents, 158 U. Penn. L. Rev.
1 (2009); John R. Allison, Mark A. Lemley &
Joshua Walker, Patent Quality Settlement
Among Repeat Patent Litigants, 99
Georgetown L. J. 677 (2011);
Colleen V. Chien & Mark A. Lemley,
Patent Holdup, the ITC, and the Public
Interest, 98 Cornell L. Rev. 1 (2012).
See Chien
& Lemley, supra note 40
(noting the unintended consequence of the Supreme Court’s ruling in eBay v. MercExchange, 547
U.S. 388 (2006), namely, the driving patent forces entities to a different
forum, the International Trade Commission (ITC), to secure injunctive relief
not available in the federal courts); Thomas F. Cotter, Patent Holdup, Patent Remedies, and Antitrust Responses, 98 J. Corp.
L. 1151 (2009).
[42] See Ronald Coase, The Problem of Social Cost, 3 J.
L. & Econ. 1 (1960).
See Brownwyn
H. Hall, Exploring the Patent Explosion,
30 J. Tech. Transfer 35 (2005); U.S. Patent and Technology Office, U.S. College
and University Utility Patent Grants – Calendar Years 1969 – 2012, https://www.uspto.gov/web/offices/ac/
ido/oeip/taf/univ/univ_toc.htm (last
visited Oct. 23, 2017) (examining the sources of patent growth in the United
States since 1985, and confirming that growth has taken place in all
technologies); Rosa Grimaldi, Martin Kenney, Donald
S. Siegel & Mike Wright, 30 Years
after Bayh-Dole Act: Reassessing Academic Entrepreneurship, 40 Res. Pol’y 1045
(2011) (discussing and appraising the effects of the legislative reform
relating to academic entrepreneurship); Elizabeth Popp Berman, Why Did Universities Start Patenting?
Institution-Building and the Road to the Bayh-Dole Act, 38 Soc. Studies of Sci. 835 (2008); Leslie, supra note 4;
Loss, supra note 4,
at 224-25. But see Elizabeth Popp
Berman, , 38 Soc. Studies of Sci. 835 (2008) (noting
that while observers have traditionally attributed university patenting to the
to the Bayh-Dole Act of 1980, university patenting was increasing throughout
the 1970s, and explaining the rise of university patenting as a process of
institution-building, beginning in the 1960s).
David C. Mowery, Richard R. Nelson, Bhaven N. Sampat & Arvids A. Ziedonis, The Growth
of Patenting and Licensing by US Universities: An Assessment of the Effects of
the Bayh-Dole Act of 1980, 30 Pol’y 99 (2001) (examining the effect of the
Bayh-Dole Act on patenting and licensing at three universities—Columbia,
Stanford, and California-Berkeley—and suggesting that the Bayh-Dole Act was
only one of several important factors behind the rise of university patenting
and licensing activity); see also
Harold W. Bremer, The First Two Decades of the Bayh-Dole Act, Presentation to the National
Association of State Universities and Land Grant Colleges (Nov. 11, 2001)
(attributing the proliferation of technology transfer to the Bayh-Dole Act).
See, e.g., Jennifer Carter-Johnson, Unveiling the Distinction between the
University and Its Academic Researchers: Lessons for Patent Infringement and
University Technology Transfer, 12 Vanderbilt
J. Entertainment & Tech. L. 473 (2010) (exploring the idea that a
faculty member acting in the role of an academic researcher in the scientific
disciplines should be viewed in the context of patent law as an autonomous
entity within the university rather than as an agent of the university, and
arguing that acknowledging a distinction between the university and its
academic researchers would revive the application of the experimental use
exception as a defense to patent infringement for the scientists who drive the
innovation economy and encourage academic researchers to participate in
transferring new inventions to the private sector); Martin Kenney & Donald
Patton, Reconsidering the Bayh-Dole Act
and the Current University Invention Ownership Model, 38 Res. Pol’y 1407 (2009)
(citing the problems with the Bayh-Dole Act’s assignment of intellectual
property interests, and suggesting two alternative invention commercialization
models: (1) vesting ownership with the inventor, who could choose the
commercialization path for the invention, and provide the university an
ownership stake in any returns to the invention; and (2) making all inventions
immediately publicly available through a public domain strategy or, through a
requirement that all inventions be licensed non-exclusively); Liza Vertinsky, Universities
as Guardians of Their Inventions, 4 Utah
L. Rev. 1949 (2012) (submitting that universities need more “discretion,
responsibility, and accountability over the post-discovery development paths
for their inventions,” in order to allow the public benefit of the invention to
reach society, and arguing that, because universities guard their inventions,
the law should be designed to encourage their responsible involvement in
shaping the post-discovery future of their inventions).
35 U.S.C. §154 (1994); 125 Stat. §§ 284-341 (2011).
See Kira R. Fabrizio,
Opening the Dam or Building Channels: University Patenting and the Use of
Public Science in Industrial Innovation (Jan. 30 2006) (working paper) (on file with the Goizueta
School of Business at Emory University) (investigating the relationship between
the change in university patenting and changes in firm citation of public
science, as well as changes in the pace of knowledge exploitation by firms,
measured using changes in the distribution of backward citation lags in
industrial patents); Hall, supra note 43
(confirming that growth since 1984 has taken place in all technologies, but not
in all industries, being concentrated in the electrical, electronics,
computing, and scientific instruments industries); Michael D. Frakes & Melissa F. Wasserman, Does Agency Funding Affect Decisionmaking?:
An Empirical Assessment of the PTO’s Granting Patterns, 66 Vanderbilt L. Rev.
67 (2013) (finding that the PTO is preferentially granting patents on
technologies with high renewal rates and patents filed by large entities, as
the PTO stands to earn the most revenue by granting additional patents of these
types); Tom Coupé, Science Is Golden:
Academic R&D and University Patents, 28 J.
Tech. Trans. 31 (2003) (finds that more money spent on academic research
leads to more university patents, with elasticities that are similar to those
found for commercial firms).
See Clovia
Hamilton, University Technology Transfer
and Economic Development: Proposed Cooperative Economic Development Agreements
Under the Bayh-Dole Act, 36 J.
Marshall L. Rev. 397 (2003) (proposing that Congress amend the Bayh-Dole
Act to provide guidance on how universities can enter into Cooperative Economic
Development Agreements patterned after the Stevenson-Wydler
Act’s Cooperative Research and Development Agreements); Lita
Nelsen, The Rise of Intellectual Property
Protection in the American University, 279 Science
1460, 1460-1461 (1998) (describing the inputs and outcomes of university
assertion of intellectual property rights); Nicola Baldini,
Negative Effects of University Patenting:
Myths and Grounded Evidence, 75 Scientometrics
289 (2008) (discussing how the university patenting threatens scientific
progress due to increasing disclosure restrictions, changes in the nature of
the research (declining patents’ and publications’ quality, skewing research
agendas toward commercial priorities, and crowding-out between patents and
publications), and diversion of energies from teaching activity and reducing
its quality); Lemley, supra note 7
(illustrating that universities are non-practicing entities, sharing some
characteristics with trolls but somewhat distinct from trolls, and making the
normative argument that the focus should be on the bad acts of all
non-practicing entities and the laws that make these acts possible); Jacob H. Rooksby, University
Initiation of Patent Infringement Litigation, 10 John Marshall Rev. Intell. Prop. L. 623
(2011) (revealing similarities between the litigation behavior of universities
and for-profit actors, as well as complex and varied relationships between
universities, their licensees, and research foundations closely affiliated with
universities).
See generally Mowery, et al., supra note 5;
Christopher A. Cotropia, Jay P. Kesan
& David L. Schwartz, Unpacking Patent
Assertion Entities (PAEs), 99 Minn.
L. Rev. 649 (2014); Sara Jeruss, Robin Feldman
& Joshua Walker, The America Invents
Act 500: Effects of Patent Monetization Entities on US Litigation, 11 Duke L. & Tech. Rev. 357 (2013).
See Cyert & James G. March, A Behavioral Theory of
the Firm (Herbert A. Simon ed., Prentice-Hall Inc. 1963).
See Lattuca & Joan S. Stark, Shaping
the College Curriculum: Academic Plans in Context 24 (2d ed. 2009) (modeling visually the interaction
between universities and external influences such as governments).
(2002), http://citeseerx.ist.psu.edu/viewdoc/download?
doi=10.1.1.453.1958&rep=rep1&type=pdf (noting
that such a duty transforms the academia-industry relationship from the
traditional view of disparate entities into a Congressionally-mandated
partnership, intended to advance technology and benefit the public).
See Valerie L. McDevitt et al., More than Money: The Exponential Impact of Academic Technology Transfer,
16 Technology & Innovation 75 (2014).
Id.
This study employs data from the Carnegie Classification of Institutions of
Higher Education, U.S. College and
University Utility Patent Grants – Calendar Years 1973, 1987, 1994,
2000, 2005, 2010, with years 1994, 2000, 2005, and 2010, http://carnegieclassifications.iu.edu/downloads.php
(last accessed Oct. 23, 2017). However, because the Carnegie Commission on
Higher Education changed its classification standards in 2010, the “basic”
classification standard was used to impute these values for each classification
observation from 2010 to 2012.
The “basic” Carnegie Classifications split Doctoral-Granting institutions into
four subgroups: Research Universities I and II, and Doctoral-Granting
Universities I and II. Research universities originally were considered the
leading universities in terms of federal financial support of academic
research, provided they awarded a minimum threshold of Ph.D.’s and/or M.D.’s.
Doctoral-granting universities were originally conceived of as smaller
operations, in terms of federal funding and doctoral production, but comparable
in scope to the research universities. Next, the Comprehensive Universities I
and II met minimum enrollment thresholds, offered diverse baccalaureate
programs and master’s programs, but lacked substantial doctoral study and
federal support for academic research. The Liberal Arts Colleges I and II were
selected somewhat subjectively in the first several iterations of the Carnegie
Classifications; this is particularly the case for Liberal Arts Colleges II,
which did not meet criteria for inclusion in the first liberal arts college
category but were not selected for Comprehensive University II, either. The
Liberal Arts Colleges I included colleges with the most selective baccalaureate
focused liberal arts programs. As for the specialized institutions, which are
divided into nine categories, the medical, health and engineering schools
tended to be stand-alone institutions or institutions affiliated with a parent
higher education institution but maintaining a separate campus. Last, the
“other specialized institutions” included in the analytical sample are drawn from
schools of art, music, and design, as well as graduate centers, maritime
academies, and military institutes. Id.
As an illustrative example of collapsing an administrative unit on the parent
institution, Washington University School of Medicine was collapsed on
Washington University. This also applied to foundations and boards of regents,
which were collapsed on the flagship institution, given that the vast majority
of observations in this dataset are standalone or flagship institutions; for
example, the University of Colorado Board of Regents and the University of
Colorado Foundation are collapsed on the University of Colorado, given that no
other institution from the University of Colorado system appears in the PTO
dataset. Finally, independent institutions within the same university system
were treated as different observations: the University
of Texas Southwestern Medical Center is distinctly observed from the University
of Texas at Austin or even the University of Texas at Dallas, the city in which
the University of Texas Southwestern Medical Center is located.
Stata FAQ: How Can I Run a Piecewise
Regression in Stata?, Univ. of Calif.
Los Angeles Inst. for Digital Research and Educ. (2016), https://stats.idre.ucla.edu/stata/faq/
how-can-i-run-a-piecewise-regression-in-stata/. Effectively, calculating the slope and
intercept shifts by hand using spline regression rescales the variable “year”
by centering it on the location of the spline knot. For example, the first
spline knot (k1) is
centered on 1981, with all years before it counting up to zero and all years
after—but before the next spline knot—counting up
from zero. Including the centered “year” variable in the regression equation
also requires adding an indicator variable of the intercept before and after
the spline knot. Because the model has an implied constant—the intercepts
before and after the spline knot should add up to 1—the overall test of the
model will be appropriately calculated by hand. To finish estimating the slope
and intercept differences by hand, this regression approach requires the use of
the “hascons” option, because of the implied
intercept constant. Alternatively, the “mkspline”
package in Stata 13 can be used to conduct this estimation. Both approaches
were used and yielded substantially similar results. The estimates from using
the “mkspline” command are
reported below for ease of interpretation.
James H. Steiger, An
Introduction to Splines, StatPower
(2013), http://www.statpower.net/Content/313/Lecture%20Notes/Splines.pdf.
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