The econometrics of IP: The case of patents and innovation

A guest editorial by Neil J. Wilkof

Will this soon be required reading for
the IP fraternity?

IP scholars have not traditionally been known for investigating IP matters from a statistical perspective. Cases and statutes are read and analyzed, doctrines are proposed and debated, policy is floated and vetted. However, IP scholars have largely vacated the empirical research space. It comes as no surprise, therefore, that economists have largely come to dominate this field with little input from or involvement by the IP community. Schooled in the discipline of econometrics, economists are skilled in organizing and aggregating data and then subjecting these data to various forms of statistical analysis.

Perhaps the most notable example is research seeking to measure the nexus between innovation and IP. In seeking to apply econometric techniques to this topic, the threshold challenge is to find a satisfactory metric for measurement. The answer, until now, has been to focus on and make use of the abundant sources of patent data that are available as the most reasonable proxy for measuring the quantity and quality of innovation. And so the question: should we in the IP community pay more critical attention to the use of patent data for this purpose?

Consider the following passage, taken from a much-discussed study by Shai Bernstein, “Does Going Public Affect Innovation?” As can be seen from the title of the paper, a key part of Bernstein's study involved measuring innovation. Bernstein goes about this in typical fashion by focusing on patenting activity. He writes as follows:

“While the literature acknowledges that patents are not a perfect measure [footnote—“For example, inventions may be protected by trade secrets”], their use as a measure of innovative activity is widely accepted (references omitted). Importantly for this analysis, patent information is available for both public and private firms, unlike R&D expenditures, and allows measuring firm innovative output along several dimensions, rather than merely expenditures.

The most basic measure of innovative output is a simple count of the number of patents granted. However, patent counts cannot distinguish between breakthrough innovation and incremental discoveries (reference mitted). The second metric, therefore, reflects the importance or novelty of a patent by counting the number of citations a patent receives following its approval [footnote and reference omitted) illustrate that citations are a good measure of innovative quality and economic importance.”

Bernstein goes on to add further nuances to the relationship between innovation and patents, but the contours of his approach are as stated above. As such, I have reservations about the apparent ease by which patent data are taken as a robust proxy for innovation.

First, many discussions of innovation (deriving from business management rather than from economics) have identified various forms that are far removed from patent activity. Moreover, not every form of innovation is patent-oriented. Indeed, there is something tautological about equating innovations with patent activity, whereby patents are used as a proxy for patent-focused innovation.

Secondly, the effective dismissal of trade secrets in measuring innovation is simply astonishing. The failure to address trade secrets cannot be justified on the ground that they are not material for innovation. It seems that the most salient reason why trade secrets are not included is simply the difficulty in identifying and measuring them. That may true, but any results based solely on patent data must therefore be recognized for what they are—only partial in nature.

Don't get me wrong, I am not a statistics Luddite (my Ph.D. studies included a heavy dose of applied statistics). As such, I have some idea about the strengths and weaknesses of statistical analysis. By the same token, members of the IP community have a view of patent quality and the like that can certainly augment the macro focus of econometric analysis of IP and innovation. Perhaps the time has come for economists to engage the IP community more actively devising better means to measure the nexus between innovation and IP.