“Patents and Cumulative Innovation: Causal Evidence from the Courts,” A. Galasso & M. Schankerman (2013)

Patents may increase or hinder cumulative invention. On the one hand, a patentholder can use his patent to ensure that downstream innovators face limited competition and thus have enough rents to make it worthwhile developing their product. On the other hand, holdup and other licensing difficulties have been shown in many theoretical models to make patents counterproductive. Galasso and Schankerman use patent invalidation trials to try and separate out the effect, and the broad strokes of the theory appear to hold up: on average, patents do limit follow-up invention, but this limitation appears to solely result from patents held by large firms, used by small firms, in technologically complex areas without concentrated power.

The authors use a clever IV to generate this result. The patent trials they look at involve three judges, selected at random. Looking at other cases the individual judges have tried, we can estimate the proclivity to strike down a patent for a given judge, and thus predict the probability a certain panel in the future will strike down a certain patent. That is, the proclivity of the judges to strike down the patent is a nice IV for whether the patent is actually struck down. In the second stage of the IV, investigate how this predicted probability of being invalidated, along with covariates and the pre-trial citation path, impact post-trial citations. And the impact is large: on average, citations increase 50% following an invalidation (and indeed, the Poisson IV estimate mentioned in a footnote, which seems more justified econometrically to me, is even larger).

There is, however, substantial heterogeneity. Estimating a marginal treatment effect (using a trick of Heckman and Vycatil’s) suggests the biggest impact of invalidation on patents whose unobservables make them less likely to be overturned. To investigate this heterogeneity further, the authors run their regressions again including measures of technology class concentration (what % of patents in a given subclass come from the top few patentees) and industry complexity (using the Levin survey). They also denote how many patents the patentee involved in the trial received in the years around the trial, as well as the number of patents received by those citing the patentee. The harmful effect of patents on future citations appears limited to technology classes with relatively low concentration, complex classes, large firms with the invalidated patent, and small firms doing the citing. These characteristics all match well with the type of technologies theory imagines to be linked to patent thickets, holdup potential or high licensing costs.

In the usual internal validity/external validity way, I don’t know how broadly these results generalize: even using the judges as an IV, we are still deriving treatment effects conditional on the patent being challenged in court and actually reaching a panel decision concerning invalidation; it seems reasonable to believe that the mere fact a patent is being challenged is evidence that licensing is problematic, and the mere fact that a settlement was not reached before trial even more so. The social welfare impact is also not clear to me: theory suggests that even when patents are socially optimal for cumulative invention, the primary patentholder will limit licensing to a small number of firms in order to protect their rents, hence using forward citations as a measure of cumulative invention allows no way to separate socially optimal from socially harmful limits. But this is at least some evidence that patents certainly don’t democratize invention, and that result fits squarely in with a growing literature on the dangers of even small restrictions on open science.

August 2013 working paper (No IDEAS version).

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