Trading and Enforcing Patent Rights
By Alberto Galasso, Mark Schankerman, Carlos J. Serrano. 2013
144 citations recorded by the source corpus.
We study how the market for innovation affects enforcement of patent rights. Conventional wisdom associates the gains from trade with comparative advantage in manufacturing or marketing. We show that these gains imply that patent transactions should increase litigation risk. We identify a new source of gains from trade, comparative advantage in patent enforcement, and show that transactions driven by this motive should reduce litigation. Using data on trade and litigation of individually-owned patents in the U.S., we exploit variation in capital gains tax rates as an instrument to identify the causal effect of trade on litigation. We find that taxes strongly affect patent transactions, and that reallocation of patent rights reduces litigation risk, on average. The impact of trade on litigation is heterogeneous, however. Patents with larger potential gains from trade are more likely to change ownership, suggesting that the market for innovation is efficient. We also show that the impact of trade on litigation depends on characteristics of the transactions.
Subfields: Accounting, Economics and Econometrics, Management of Technology and Innovation
View Paper: https://www.semanticscholar.org/paper/a33bf60ac6497825dccd33e7f52950d7137c8281
Citations in the corpus
- Patent collateral, investor commitment, and the market for venture lending (2018, unknown): “Serrano (2010) and Galasso et al. (2013) document active trading in the modern market for patents, particularly for inventions originating from individuals and small firms.”
- Do corporate taxes hinder innovation (2017, unknown): “For example, only eight out of 27For instance, Galasso, Schankerman, and Serrano (2013) show that capital gains taxes a ect trading in patents.”
- Why are some regions more innovative than others? The role of small firms in the presence of large labs (2014, unknown): “Following Bertrand et al. (2004), we block bootstrap the standard errors at the state level to account for serially correlated unobserved state shocks.”