Do patents stifle cumulative innovation?

This important question is ask by Joshua Gans at the Digitopoly blog. The question is whatever other benefits and faults there might be with the patent system, a fault that really matters for the operation of the system and for growth prospects is how patents might stifle cumulative or follow-on innovation. Gans writes,

The standard, informal theory of harm here is that follow-on innovators, feeling that they can’t easily deal with the patent holder on the pioneer innovation, decide that the risks are too high to invest and so opt not to do so. To be sure, this ‘hold-up’ concern is not good for anyone, including possibly the patent rights holder who loses the opportunity to earn licensing fees from applications of their knowledge. Suffice it to say, this has been a big feature of the movement against the current strength and, indeed, existence of the patent system.

Now I'm not sure this really is a hold-up problem in the Goldberg sense, it looks more like a barrier (or a delay) to entry problem. Either way if innovation is affected then the cost could be high. A problem, however, with dealing with this issue was that the evidence on the impact of patents on cumulative innovation was weak. Gans continues,

At the NBER Summer Institute a new paper by Bhaven Sampat and Heidi Williams [...] actually found a way to examine the impact of patents on follow-on innovations themselves. Their setting was to look at precisely the area of the Myriad case. They utilised the human genome and the fact that genes that were sequenced could be patented. What’s great about this setting is that the gene itself has a unique identifier that the researchers can use to identify whether it is subject to a patent claim (and indeed a patent application that may be accepted or rejected by the USPTO) and then also identify whether that gene was the subject of publications and clinical trials. This is as good as it gets for the measurement of innovation.

But how do you find a way of comparing what happens if there is a patent on a gene sequence versus if there is no patent? After all, there may be no patent because no one things that gene is important which may also be the reason why there is no follow-on research. That means you have to find some relatively independent reason why a patent may exist or not. Sampat and Williams exploit imperfections at the USPTO that can be themselves identified to obtain that reason.

They use several methods that all give the same answer but let me explain the best one. Patents are examined by examiners that are essentially randomly assigned.

Examiners are also identified and thus it is possible to look at their history and work out if they are tough or lenient. Gans again,

The researchers worked out that this characterisation was unrelated to other things and so could use it to identify patents that might have otherwise been accepted but were given to a tough examiner and the reverse. That is not perfect but is a fairly convincing way to measure and incorporate randomness to assess causality.

Prior to this paper, had you asked the 200 economists in the room at the NBER what they thought the outcome would have been, it is fair to say, all of them (including myself) would have predicted that patents would have a negative impact of at least 10 percent. This probably included the authors. As it turned out, the paper showed that those magnitudes in reduction could be rejected statistically. But more to the point, the paper presents pretty convincing evidence that you cannot reject zero as the likely prediction. That is, the effect patents on follow-on research appears to be non-existent.

So the impact of patents on cumulative innovation may be zero. But is this surprising? If the patent holder and the follow-on innovators both gain from allowing innovation, a Coaseian bargain should be able to be agreed to which allows innovation and makes both parties better off.