Lauren Cohen et al. go after "patent trolls"

The abstract for Patent Trolls... states


We provide theoretical and empirical evidence on the evolution and impact of
non-practicing entities (NPEs) in the intellectual property space. Heterogeneity in
innovation, given a cost of commercialization, results in NPEs that choose to act as
\patent trolls" that chase operating rms' innovations even if those innovations are not
clearly infringing on the NPEs' patents. We support these predictions using a novel,
large dataset of patents targeted by NPEs. We show that NPEs on average target rms
that are ush with cash (or have just had large positive cash shocks). Furthermore,
NPEs target rm pro ts arising from exogenous cash shocks unrelated to the allegedly
infringing patents. We next show that NPEs target rms irrespective of the closeness of
those rms' patents to the NPEs', and that NPEs typically target rms that are busy
with other (non-IP related) lawsuits or are likely to settle. Lastly, we show that NPE
litigation has a negative real impact on the future innovative activity of targeted rms.





The first paragraph shows that the authors are confused about what a patent right is:


Clearly defined property rights are essential for well-functioning markets. In the case of
intellectual property (IP), however, property rights are complex to define; unlike ownership
of physical assets, the space of ideas is di cult to clearly delineate. A solution employed
by the United States and many other countries is the patent, a property right allowing an
idea's owner sole commercialization rights for a period of time.



As the ancient diode/triode saga illustrates, having a patent does NOT give one a sole commercialization
right.

Yes, the first person mentioned in the acknowledgements on the first page is "Jim Bessen," and the first footnote
is --Bessen et al. (2011) estimate that from 2007 to 2010, these litigation (and settlement) losses averaged
over $83 billion per year in 2010 dollars (just summing over the losses to publicly traded rms). This is
equivalent to over 25% of annual United States industrial R&D investment --

Of the supporting data: -- Using proprietary data, we provide strong empirical evidence for the model's main
predictions. --