[%TAGS (074db819ec% %074db819ec) %]
(074db819ec% IF user.email && action == 'arc' %074db819ec)
(074db819ec% END %074db819ec)
- From: Gregory Aharonian srctran@world.std.com
- Subject: [Patents] PATNEWS: A critique of Bessen/Maskin's innovation and patents paper
- Date: Fri, 2 Feb 2001 00:19:15 -0500 (EST)
!20010131 A critique of Bessen/Maskin's innovation and patents paper
There is a debate going on over in Europe on the patenting of software.
Some of those fighting software patents in Europe (and wanting to keep the
current minimalist prohibition, 52.2.c in the law) are trying to raise the
issue of the inherent evilness and utter reprehensibility of software
patents. One weapon they use is to cite a paper published a year ago by
two economists in the Boston area, Eric Maskin of MIT's Economics Dept.,
and James Bessen, a consultant in the Boston area. I feel that it is wrong
to use this paper in a policy argument because a) the paper's models are
unrealistic, and b) their use of correlating data is questionable. What
follows are comments on these two concerns.
They propose a simple economic model to argue that in sequential
innovation industries like software, semiconductors and computers, that
patent protection may reduce overall innovation and social welfare. The
paper is titled "Sequential Innovation, Patents and Imitation", January
2000 (it's on the Web). Here is the abstract:
How could such industries as software, semiconductors, and
computers have been so innovative despite historically weak
patent protection? We argue that if innovation is both
sequential and complementary - as it certainly has been in
those industries - competition can increase firms' future
profits thus offsetting short-term dissipation of rents.
A simple model also shows that in such a dynamic industry,
patent protection may reduce overall innovation and social
welfare. The natural experiment that occurred when patent
protection was extended to software in the 1980's provides
a test of this model. Standard arguments would predict
that R&D intensity and productivity should have increased
among patenting firms. Consistent with our model, however,
these increases did not occur. Other evidence supporting
our model includes a distinctive pattern of cross-licensing
in these industries and a positive relationship between
rates of innovation and firm entry.
The problem is that these models are too simplistic to represent the
complicated dynamics of the software world, and the economic data they
use represents only part of the software industry. To then use this
paper to argue against software patents is intellectually dishonest.
For example, consider the introduction to the static version of their
model:
We consider an industry consisting of two (ex ante symmetric)
firms. Each firm can undertake R&D to discover and develop
an innovation with expected (social) value V. The cost of
R&D is C, and if a single firm incurs that cost, the
possibility of successful innovation is P. We assume that
if a firm is not copied, it can capture the social value of
its innovation. However, the other firm, unless prevented by
patent protection, can costlessly develop an imitation. And
if it does so, the innovating firm obtains only a fraction S
(S < 1/2) of the value of V (to simplify matters, we assume
that the imitating firm captures this same faction s).
and a dynamic version
Let us now enrich the model to accommodate a sequence of
potential innovations, each of which builds on its immediate
predecessor. More specifically, we will suppose that, for a
firm to have a realistic chance of developing the innovation
of the next generation, it must have market experience with
that of the current generation.
Anyone recognize the US software R&D community (companies, universities,
government labs, individuals communicating over networks) in these models?
Additionally, marketing plays a big role in driving R&D (not only for
software, but pharmaceuticals as well). Finally, while patent protection
is a useful tool, I don't think it is a strategic tool that shapes R&D
along the lines of these two models. In short, they propose two models
fun to explore mathematically, but that's it. Thus, as a message to the
Europeans, one has to be really careful in applying conclusions from the
analysis of such models to the real world for policy purposes.
What is of additional concern to me is one such application of their
models to understand the US software patenting scene. They create an
either-or explanation for a situation which has many potential
explanations. Arguing about software, they write:
A series of court decisions in the early 1980's had the effect
of extending patent protection to many software ideas.
Consequently the number of patents issued annually covering
software grew exponentially from the mid-80's to about 7,000
in 1995. Within the software industry, this has sometimes
been described as a case of "fixing what ain't broke".
Advocates counter, arguing along the lines of the static
model, that increased patent protection should increase
software innovativeness.
If the static model is correct, then the extension of patent
protection should have produced a sharp increase in R&D
spending among those firms and industries applying for
patents. This should have subsequently been followed by an
increase in productivity growth. The changes should be
measurable and large after controlling for other, possibly
offsetting charges.
[.....]
To summarize, if the state model holds, relative R&D spending
should have increased sharply, followed by productivity. If
the dynamic model applies, relative R&D spending and productivity
would not have increased and might exhibit a mild decrease.
First, the court decisions favoring software patenting only partially
explains the rise in software patent applications. The authors ignore
the parallel set of court decisions that weakened copyright protection
for software, which drove many to the patenting side. The investment
climate also became very favorable to the software industry in the 1990s,
which also partially drove the increase in software patent applications.
Next, they analyze these models in light of NSD and NBER R&D economic
data. They conclude
In summary, the initial high level of innovation in software,
mixed industry support for patents, and an apparent gradual
slowdown of R&D intensity all suggest that the applicability
of the dynamic model. This conclusion is also supported by
the distinctive pattern of cross-licensing in the semiconductor
and computer industries and by the more general positive
relationship between innovation and firm entry. All of this
is difficult to reconcile with the traditional static model
of intellectual property.
So using a simplistic two firm semi-dynamic model, and a subset of all
of the economic data relating to these industries, they make some
conclusions. Interesting, but how relevant? For example, consider
the phrase in their abstract:
A simple model also shows that in such a dynamic industry,
patent protection may reduce overall innovation and social
welfare.
They measure innovation and social welfare for the software industry
using the NSF and NBER data from the 1974 to 1994 time period, and
conclude "... in a dynamic world, firms may have plenty of incentive
to innovate without patents and patents may constrict complementary
innovation." Constrict?
Whoopee. Given all of these simplifications and "may" qualifiers, it is
dubious to bad logic for anyone to then argue that the Bessen/Maskin
article is grounds to ban software patents because they are bad.
In the real world, is there any evidence that the explosion in (bad)
software patents has stifled innovation and social welfare? I offer
some data to show that you can't answer this question YES or NO. The
data I offer is the new number of papers in the INSPEC engineering
abstracts database that have a keyword entry "SOFTWARE". INSPEC has
abstracts to most of the journals and conferences where new refereed
papers are published, papers that come out of the many corporate,
academic and government R&D environments where software plays a role.
YEAR NEW "SOFTWARE" PAPERS IN INSPEC
1999 19,480
1998 20,143
1997 20,187
1996 19,743
1995 17,181
1994 17,632
1993 14,450
1992 13,336
1991 13,088
1989 14,797
1988 17,159
1987 15,538
1986 13,295
1985 12,139
1984 13,615
1983 10,615
1982 6,799
1981 6,615
1980 4,943
1979 4,382
1978 3,960
1977 2,764
1976 2,370
What we see is a gradually increasing amount of new materials published
about software over a time period when the number of issued software
patents went from a few hundred a year to a few tens of thousands a year.
During the 1990s, each year saw about a 8% growth in the number of new
software publications.
Hard to argue then that innovation and the public's desire for publication
of new ideas, has suffered at all. Heck, as someone who has to keep
track of all of these materials for prior art searching purposes, I wish
software patents were stifling things so I would have less to track :-)
Looking at all sorts of data, it is hard for me to argue anything but that
software is just another technology with patenting problems no different
than other technologies (though I do think the quality of software patents
is lower). While the Bessen/Maskin article is suggestive, it is too
simplistic to use as a jsutification for any policy decision.
Greg Aharonian
- [Patents] PATNEWS: A critique of Bessen/Maskin's innovation and patents paper, Gregory Aharonian srctran
(074db819ec%|loc%074db819ec)Archive powered by(074db819ec%END%074db819ec) MhonArc 2.6.16.
(074db819ec%TAGS [% %]%074db819ec)