“Contractability and the Design of Research Agreements,” J. Lerner & U. Malmendier (2010)

Outside research has (as we discussed yesterday) begun to regain prominence as a firm strategy. This is particularly so in biotech: the large drug firms generally do not do the basic research that leads to new products. Rather, they contract this out to independent research firms, then handle the development, licensing and marketing in-house. But such contracts are tough. Not only can do I have trouble writing an enforceable contract that conditions on the effort exerted by the research firm, but the fact that research firms have other projects, and also like to do pure science for prestige reasons, means that they are likely to take my money and use it to fund projects which are not entirely the most preferred of the drug company.

We are in luck: economic theory has a broad array of models of contracting under multitasking worries. Consider the following model of Lerner and Malmendier. The drug firm pays some amount to set up a contract. The research firm then does some research. The drug firm observes the effort of the researcher, who either worked on exactly what the drug company prefers, or on a related project which throws off various side inventions. After the research is performed, the research firm is paid. With perfect ability to contract on effort, this is an easy problem: pay the research firm only if they exert effort on the projects the drug company prefers. When the research project is “tell me whether this compound has this effect”, it might be possible to write such a contract. When the research project is “investigate the properties of this class of compounds and how they might relate to diseases of the heart”, surely no such contract is possible. In that case, the optimal contract may be just to let the research firm work on the broader project it prefers, because at least then the fact that the research firm gets spillovers means that the drug firm can pay the researcher less money. This is clearly second-best.

Can we do better? What about “termination contracts”? After effort is observed, but before development is complete, the drug firm can terminate the contract or not. Payments in the contract can certainly condition on termination. How about the following contract: the drug firm terminates if the research firm works on the broader research project, and it takes the patent rights to the side inventions. Here, if the research firm deviates and works on its own side projects, the drug company gets to keep the patents for those side projects, hence the research firm won’t do such work. And the drug firm further prefers the research firm to work on the assigned project; since termination means that development is not completed, the drug firm won’t just falsely claim that effort was low in order to terminate and seize the side project patents (indeed, on equilibrium path, there are few side patents to seize since the research firm is actually working on the correct project!). The authors show that the contract described here is always optimal if a conditional termination contract is used at all.

Empirically, what does this mean? If I write a research contract for more general research, I should expect more termination rights to be reserved. Further, the liquidity constraint of the research firms matter; if the drug firm could make the research firm pay it back after termination, it would do so, and we could again achieve the first best. So I should expect termination rights to show up particularly for undercapitalized research firms. Lerner and Malmendier create a database from contract data collected by a biotech consulting firm, and show that both of these predictions appear to be borne out. I read these results as in the style of Maskin and Tirole; even when I can’t fully specify all the states of the world in a contract, I can still do a good bit of conditioning.

2008 Working paper (IDEAS version). Final paper in AER 2010. Malmendier will certainly be a factor in the upcoming Clark medal discussion, as she turns 40 this year. Problematically, Nick Bloom (who, says his CV, did his PhD part time?!) also turns 40, and both absolutely deserve the prize. If I were a betting man, I would wager that the just-published-in-the-QJE Does Management Matter in the Third World paper will be the one that puts Bloom over the top, as it’s really the best development paper in many years. That said, I am utterly confused that Finkelstein won last year given that Malmendier and Bloom are both up for their last shot this year. Finkelstein is a great economist, no doubt, but she works in a very similar field to Malmendier, and Malmendier trumps her by any conceivable metric (citations, top cited papers, overall impact, etc.). I thought they switched the Clark Medal to an every-year affair just to avoid such a circumstance, such as when Athey, List and Melitz were all piled up in 2007.

I’m curious what a retrospective Clark Medal would look like, taking into account only research that was done as of the voting year, but allowing us to use our knowledge of the long-run impact of that research. Since 2001, Duflo 2010 and Acemoglu 2005 are locks. I think Rabin keeps his in 2001. Guido Imbens takes Levitt’s spot in 2003. List takes 2007, with Melitz and Athey just missing out (though both are supremely deserving!). Saez keeps 2009. Malmendier takes 2011. Bloom takes 2012. Raj Chetty takes 2013 – still young, but already an obvious lock to win. What’s interesting about this list is just how dominant young folks have been in micro (especially empirical and applied theory); these are essentially the best people working in that area, whereas macro and metrics are still by and large dominated by an older generation.

“Patent Alchemy: The Market for Technology in U.S. History,” N. Lamoreaux, K. Sokoloff & D. Sutthiphisall (2012)

It may appear that the world of innovation looks very different today than it used to. Large in-house R&D outfits – the Bell Labs of the past – are being replaced by small firms who sell the results of their research on to producers. Venture capital funding of research appears more and more important, both for providing capital to inventors and to linking the inventors up with potential buyers. Patent trolls hound the innocent, suing them for patent violations they weren’t even aware of. The speed with which patents are evaluated has slowed to a crawl, and the number of patents being granted continues to grow. Many patents are merely defensive, acquired solely to keep someone else from acquiring them.

Lamoreaux et al, building on earlier work by Lamoreaux and Sokoloff as well as Tom Nicholas’ interesting recent research, point out that none of the above is strange. The rise of in-house R&D is a phenomenon that doesn’t show up in great number in America until well into the twentieth century, only becoming dominant after the Second World War. Around the turn of the century, most innovation was done by small, independent inventors, or by small research firms like Edison’s outfit. A series of intermediaries, principally but not always patent lawyers, served both to file the proper paperwork and to link inventors with potential buyers; the authors provide a bunch of juicy historical stories, derived from lawyer diaries during this period, on exactly how such transactions took place. Railroads were frequently being hounded by patent trolls who tried to catch them unaware, and traveling patentbuyers crossed the Midwest and South suing farmers for using unlicensed barbed wire or milk buckets. Patents took an average of three years to be processed by the early 1900s, and the patenting rate was near an all time high. Firms regularly bought patents just so their competitors wouldn’t have them.

This is all to say that, to the extent we are worried about certain aspects of the patent system today, looking to history may be a useful place to begin. “Submarine patents”, acquired by trolls and kept unused until a particularly juicy potential violator has started to earn large profits, don’t appear to have been too prominent at the turn of the century – given how lucrative this business appears, perhaps an investigation of why they only appear in the present would be worthwhile. The role of a patent as a saleable piece of knowledge, allowing non-producers to do useful research and then sell that research to a firm who finds it useful, surely has some role, as Arrow pointed out in his famous 1962 essay. When patents instead simply add transaction costs or result in thickets, discouraging activity by true innovators, something has gone awry. And when something goes wrong in the world, it is rarely the case that history can offer us no useful guidance.

2012 working paper (No IDEAS version). Prof. Sokoloff passed away from cancer at a young age in 2007, so this may become his final published paper – it incorporates a great number of ideas he worked on throughout his career, so that would be a fitting tribute.

“Recruiting for Ideas: How Firms Exploit the Prior Inventions of New Hires,” J. Singh & A. Agrawal (2011)

Firms poach engineers and researchers from each other all the time. One important reason to do so is to gain access to the individual’s knowledge. A strain of theory going back to Becker, however, suggests that if, after the poaching, the knowledge remains embodied solely in the new employer, it will be difficult for the firm to profit: surely the new employee will have an enormous amount of bargaining power over wages if she actually possesses unique and valuable information. (As part of my own current research project, I learned recently that Charles Martin Hall, co-inventor of the Hall-Heroult process for aluminum smelting, was able to gather a fortune of around $300 million after he brought his idea to the company that would become Alcoa.)

In a resource-based view of the firm, then, you may hope to not only access a new employer’s knowledge, but also spread it to other employees at your firm. By doing this, you limit the wage bargaining power of the new hire, and hence can scrape off some rents. Singh and Agrawal break open the patent database to investigate this. First, use name and industry data to try to match patentees who have an individual patent with one firm at time t, and then another patent at a separate firm some time later; such an employee has “moved”. We can’t simply check whether the receiving firm cites this new employee’s old patents more often, as there is an obvious endogeneity problem. First, firms may recruit good scientists more aggressively. Second, they may recruit more aggressively in technology fields where they are already planning to do work in the future. This suggests that matching plus diff-in-diff may work. Match every patent to another patent held by an inventor who never switches firms, attempting to find a second patent with very similar citation behavior, inventor age, inventor experience, technology class, etc. Using our matched sample, check how much the propensity to cite the mover’s patent changes compares to the propensity to the cite the stayer’s patent. That is, let Joe move to General Electric. Joe had a patent while working at Intel. GE researchers were citing that Intel patent once per year before Joe moved. They were citing a “matched” patent 1 times per year. After the move, they cite the Intel patent 2 times per year, and the “matched” patent 1.1 times per year. The diff-in-diff then suggests that moving increases the propensity to cite the Intel patent at GE by (2-1)-(1.1-1)=.9 citations per year, where the first difference helps account for the first type of endogeneity we discussed above, and the second difference for the second type of endogeneity.

What do we find? It is true that, after a move, the average patent held by a mover is cited more often at the receiving firm, especially in the first couple years after a move. Unfortunately, about half of new patents which cite the new employee’s old patent after she moves are made by the new employee herself, and another fifteen percent or so are made by previous patent collaborators of the poached employee. What’s worse, if you examine these citations by year, even five years after the move, citations to the pre-move patent are still highly likely to come from the poached employee. That is, to the extent that the poached employee had some special knowledge, the firm appears to have simply bought that knowledge embodied in the new employee, rather than gained access to useful techniques that quickly spread through the firm.

Three quick comments. First, applied econometrician friends: is there any reason these days to do diff-in-diff linearly rather than using the nonparametric “changes-in-changes” of Athey and Imbens 2006, which allows recovery of the entire distribution of effects of treatment on the treated? Second, we learn from this paper that the mean poached research employee doesn’t see her knowledge spread through the new firm, which immediately suggests the question of whether there are certain circumstances in which such knowledge spreads. Third, this same exercise could be done using all patents held by the moving employee’s old firm – I may be buying access to general techniques owned by the employee’s old firm rather than the specific knowledge represented in that employee’s own pre-move patents. I wonder if there’s any difference.

Final Management Science version (IDEAS version). Big thumbs up to Jasjit Singh for putting final published versions of his papers up on his site.

“Diffusing New Technology Without Dissipating Rents: Some Historical Case Studies of Knowledge Sharing,” J. Bessen & A. Nuvolari (2012)

The most fundamental fact in the economic history of the world is that, from the dawn on mankind until the middle of the 19th century in a small corner of Europe, the material living standards of the average human varied within a very small range: perhaps the wealthiest places, ever, were five times richer than regions on the edge of subsistence. The end of this Malthusian world is generally credited to changes following the Industrial Revolution. The Industrial Revolution is sometimes credited to changes in the nature of invention in England and Holland in the 1700s. If you believe those claims, then understanding what spurred invention from that point to the present is of singular importance.

A traditional story, going back to North and others, is that property rights were very important here. England had patents. England had well-enforced contracts for labor and capital. But, at least as far as patents are concerned, recent evidence suggests they couldn’t have been too critical. Moser showed that only 10% or so of important inventions in the mid-1800s were ever patented in the UK. Bob Allen, who we’ve met before on this site, has inspired a large literature on collective invention, or periods of open-source style sharing of information among industry leaders during critical phases of tinkering with new techniques.

Why would you share, though? Doesn’t this simply dissipate your rents? If you publicize knowledge of a productive process for which you are earning some rent, imitators can just come in and replicate that technology, competing away your profit. And yet, and yet, this doesn’t appear to happen in many historical circumstances. Bessen (he of Bessen and Maskin 2009, one of my favorite recent theoretical papers on innovation) and Nuvolari examine three nineteenth century industries, American steel, Cornish steam engines and New England power weavers. They show that periods of open sharing on invention, free transfer of technology to rivals, industry newsletters detailing new techniques, etc. can predominate for periods a decade and longer. In all three cases, patents are unimportant in this initial stage, though (at least outside of Cornwall) quite frequently used later in the development of the industry. Further, many of the important cost reducing microinventions in these industries came precisely during the period of collective invention.

The paper has no model, but very simply, here is what is going on. Consider a fast growing industry where some factors important for entry are in fixed supply; for example, the engineer Alexander Holley personally helped design eight of the first nine American mills using Bessemer’s technology. Assume all inventions are cost reducing. Holding sales price and demand constant, cost reductions increase industry profit. Sharing your invention ensures that you will not be frozen out of sharing by others. Trying to rely only on your own inventions to gain a cost advantage is not as useful as in standard Bertrand, since the fixed factors for entry in a new industry mean you can’t expand fast enough to meet market demand even if you had the cost advantage. There is little worry about free riding since the inventions are natural by-products of day-to-day problem solving rather than the result of concentrated effort: early product improvement is often an engineering problem, not a scientific one. Why would I assume sales price is roughly constant? Imagine an industry where the new technology is replacing something already being produced by a competitive industry (link steel rail ties replaced iron ties). The early Bessemer-produced ties in America were exactly this story, initially being a tiny fraction of the rail tie market, so the market price for ties was being determined by the older vintage of technology.

Open source invention is nothing unusual, nor is it something new. It has long coexisted with the type of invention for which patents may (only may!) be more suitable vectors for development. Policies that gunk up these periods of collective invention can be really damaging. I will discuss some new research in coming weeks about a common policy that appears to provide exactly this sort of gunk: the strict enforcement of non-compete agreements in certain states.

2012 Working Paper (IDEAS version)

“Should You Allow Your Agent to Be Your Competitor?,” M. Kräkel & D. Sliwka (2009)

Many industries – especially research heavy fields like high tech and biotech – are riven with “non-compete agreements”, where you sign a contract when you’re hired banning work for a competitor firm in a similar area for some amount of time after you quit. These are controversial. Indeed, California comes close to banning them altogether (more on this in a future post). This seems like a great deal for the employer. If your employee develops any industry-specific human capital, you ensure that they won’t use the knowledge against you by working for a competitor. This immediately raises another question, then: why doesn’t every employer use NCAs?

Theory comes to the rescue, in the form of an extension of Holmstrom’s (may he win his deserved Nobel!) career concerns. Think of your income as having three components: wages, bonuses and “implicit payments”. Wages are set salaries. Bonuses are payments conditional on some verifiable goal. Implicit payments are increases in your total expected lifetime wages and bonuses as a result of some action. For instance, a firm pays a young trainee very little, less than her outside option, but promises that the deal is worth it because the trainee position will develop human capital in such a way that future job offers will be at a high wage.

Kräkel and Sliwka show how this can lead firms to avoid NCAs. Consider a model where you work with a firm on an invention. With probability p, you invent it. With probability q, if you don’t invent, the firm invents anyway. Exactly who came up with invention is not contractible (a common problem with team effort!). The agent’s effort is costly. After the invention is made, if the agent stays with the firm, a big surplus results. Alternatively, if the agent was responsible for the invention, she may receive an outside offer. The initial contract is a triple: wage, bonus conditional on the invention being made, and potentially a non-compete clause which precludes the agent from taking any future outside offer. Total surplus is assumed to be highest when the firm and the agent stay together.

Intuitively, the agent knows if they work hard and are responsible for the invention, and there is an NCA in place, then after the invention is made, the firm is going to claim that it was not the agent’s doing. Hence the incentives for individual effort are fairly low-power. If, however, there is no non-compete clause, the agent gets an outside offer if she is, in fact, the inventor. For the firm to keep the agent, then, it must give her an extra bonus. This outside offer implicitly incentivizes the agent to work harder than she would if only the bonus and wage were available. Further, it is less susceptible to free-riding on the agent’s part, since the outside option only comes about if it was the agent, and not the firm, who made the invention: the bonus when an NCA is in effect has such ability to distinguish, hence the incentive to free-ride is stronger. The model shows this intuition is correct. A non-compete clause will only be imposed when there is a very-high probability that the agent can get an outside offer, and when the relative value to the firm of keeping the agent after an invention is small. Indeed, there is a large range of parameters where I don’t pay any bonuses and I don’t provide an non-compete. The “implicit bonus” that I will have to match the agent’s outside option is enough to encourage effort. A short extension shows that if I can use clawbacks or pay workers set amounts not to compete with me, I prefer to do that always over using an NCA since the incentives can be tuned even finer.

This isn’t to say that noncompete agreements aren’t worrying from a social policy perspective; there are other reasons we should be concerned about them, as I’ll discuss sometime soon. But this result shows again the value of thinking through problems theoretically. In general, the answer to “why doesn’t X screw over Y?” turns out to be “because in equilibrium, it is not in X’s interest to do so”!

2006 Working Paper (IDEAS version). Final paper in 2009 Intl. Econ. Review.

“Profiting from Technological Innovation,” D. Teece (1986)

Teece’s 1986 article in Research Policy is surprisingly little known among economists given that it has been cited something like 10,000 times. I want to give an interpretation of the article similar to that of Sid Winter in his article written on the 20th anniversary of the original.

Schumpeter famously argued that “perfect” competition is, in fact, not so, as the lack of rents given no incentive for firms to spend on R&D, and since growth is so much important for welfare than static inefficiency, we ought be more forgiving of market power. Ken Arrow, in a well-known article from the 1962 NBER Invention volume, maintains that Schumpeter’s logic is incomplete, and that with patent licensing, monopolies can make things worse. Consider a good with marginal cost 2 and demand such that Q=6-p. In the competitive market, price is 2, quantity is 4, and industry profits are zero. With a monopoly, price is 4, quantity is 2, and industry profits are 4. An innovator invents a technique that lowers marginal cost for the good to 1. In the competitive market, he can license this good to all producers, accruing licensing profits of 1×4=4. In the monopoly market, the monopoly with marginal cost of 1 would optimally sell 2.5 units at 3.5 each, earning 2.5×2.5=6.25. Therefore, the invention increases monopoly profit by 6.25-4=2.25, and the inventor can earn no more than 2.25 by licensing to the monopolist. It seems, then, that whether monopoly or perfect competition leads to more invention depends, at least in part, on the ability of inventors to license without being appropriated.

Teece takes that logic a step further. As most inventions can be appropriated, either by direct imitation, or by inventing around the relevant patent, inventions will only pay off for the inventor if she owns the best complementary assets. Consider the case of EMI’s CAT scanner and Searle’s Nutrasweet. The CAT scanner was both invented and commercialized by EMI, leading to a Nobel for one of EMI’s engineers. Nonetheless, EMI would be out of business within a few years, while competitors made bundles of money from similar scanners. Nutrasweet, on the other hand, was enormously profitable for Searle. Why the difference?

The difference is access, through contracting or ownership, to complementary assets. EMI’s imitators had much better medical technology manufacturing and distribution technology than EMI itself. Searle, on the other hand, took deliberate steps to protect itself once its patent ran out, by establishing a strong brand during the patent period, by limiting outside manufacturing (since those contract manufacturers are potential future competitors), and by doing R&D on a product that is difficult to imitate without violating patent; for one, other alternative sugars would need to go through their own FDA approval, which takes years. Teece’s article also provides a second reason why large firms spend more on R&D. It’s not just that they will have market power in the product’s market, but also that they are more likely to own complementary assets.

Final Research Policy version (IDEAS version). A site note: this is the 300th article we’ve discussed on this site. I would love to see more focused research blogs. There are a few (e.g., the NEP-HIS blog with a weekly post on economic history), but that’s it. I’d be glad to share my experience from this blog with anyone interested. For one, the potential audience for discussions of new research is huge – at least half of the readers of this site are non-academics, but instead represent the curious, people working in the tech sector, undergraduate students, etc.

“Startups by Recent University Graduates and their Faculty,” T. Astebro, N. Bazzazian & S. Braguinsky (2012)

Since the Bayh-Dole Act of 1980, universities that receive federal research funding have been encourage to patent their research and license it to private industry.  The benefits of the patenting rule are still very much in dispute, but surely everyone can agree that the spread of academic research into real firms has been a net positive?  At many universities, faculty are even explicitly encouraged to commercialize their research, through start-ups and other means.

Astebro et al point out that something is missing here, though.  Google is a university spinoff, but spun off by two PhD students at Stanford.  Facebook and Microsoft are university spinoffs, but spun off by undergraduate students.  Indeed, faculty don’t seem to be very entrepreneurial at all: the median top-100 US university in any given year has zero such spinoffs.

Using data from a (somewhat) longitudinal survey of university undergraduates, along with existing faculty spinoff data, the authors point out that students, within a few years of graduating, are twice as likely as faculty during that period to form their own business.  Since there are so many more students, this means that 24 times more startups come from recent university grads than from faculty.  And these are not low-quality startups or disguised unemployment: 36 percent of the businesses are still around in a follow-up survey two years later.  Earnings from these startups is particularly strong for those students who claim their business is in an area related to their studies, and for students at research universities in the NRC top 10 for doctoral research.  

There is very little in the way of identification in this paper, so read this as only a first go through the data. Nonetheless, the basic point is clear: if you are a region who wants to leverage universities for new business growth, developing better and more entrepreneurial students seems to trump encouraging faculty to run businesses. Indeed, to the extent that faculty create the human capital these students will use in their businesses, such faculty-biased policies may be counterproductive. The authors discuss a couple case studies, including the interesting E-school program at Chalmers in Gothenberg, Sweden, which perhaps provide a way forward here. 

A broader takeaway, which hopefully is well-known already: the link between urban policy and invention/entrepreneurship policy is ridiculously important.

http://www.andrew.cmu.edu/user/sbrag/ABB.pdf (Draft – final version in Research Policy 41.4 (2012). No IDEAS page available.)

“Collective Invention,” R. Allen (1983)

Who invents? Standard theories usually deal just with R&D-performing firms and individual inventors. But enormous amounts of invention come as a byproduct of everyday firm investment. This type of invention tends to be incremental, and tends to be neither patentable nor held secret by the inventor. Robert Allen, in this famous paper from the early 1980s, refers to such invention as “collective invention.”

Consider the British blast furnace industry in the mid 1800s. There was certainly no meaningful corporate R&D at the time, as the world’s first corporate R&D labs were only just appearing then (in the German chemical industry). Yet the blast furnace industry in Cleveland changed enormously over a couple decades, nearly doubling the height of blast furnaces, and more than doubling temperatures. Such changes were greatly beneficial for reducing fuel consumption.

No single firm made these drastic changes overnight. Rather, furnace heights were increased incrementally by some firms when they built a new factory. Benefits in terms of lower fuel use were then made publicly available through personal correspondence, industry gatherings, and journal publications. Two factors were critical in this shift. First, the industry was rapidly adding capital. If a new plant is being built, experimentation has low costs: the cost of adding a foot to the chimney is that efficiency might be harmed slightly, and the benefit is that efficiency may be helped slightly. When an industry is not accumulating capital, this sort of minor experimentation is much more costly, since the only experimentation involves building an entirely new, not-yet-necessary factory. The second critical factor is some reason to avoid secrecy. In the blast furnaces, secrecy was more or less impossible. Builders and workers were frequently moving from plant to plant, and could simply tell their new employer what they learned. Since information is leaking out anyway, it may be an equilibrium to share information in the hopes that others will have useful information to share with me: work by von Hippel, previously discussed here models this sort of sharing in more detail.

The reason we tend to ignore this type of public, incremental innovation is because of a bias, in popular culture and in policy, toward big technological advances. A paper of mine, which I hope to have ready to share here soon, argues that the patent bias toward technological achievement and away from incentivizing the nexus of inventions which lead to a commercially viable product can be seriously harmful. The importance of minor inventions is more than the importance of the famous ones, they shout from the rooftops!

An interesting update of Allen would be in the context of China. To the extent that industries accumulating capital quickly throw off, as a byproduct, incremental inventions, there can be rapidly increasing cost efficiency in even developed industries when some shock causes the industry to switch to a new region with little capital. Peter Hessler, National Geographic’s man in China and a great chronicler of that nation, tells a great story about technology transfer and incremental growth in his book Country Driving. I’m also curious to see how one would distinguish learning-by-doing in aggregate statistics from learning-by-sharing at the plant level.

https://docs.google.com….collinvent.pdf (Final JEBO copy. The only nongated version I can find is this Google cached article.)

“Catching Up and Falling Behind: Knowledge Spillover from American to German Toolmakers,” R. Richter and J. Streb (2011)

The Chinese, all manufacturers agree, love to “steal” machines. Not the actual machine, of course, but the idea of a given machine. Reverse engineering can often be fairly straightforward. Many nations, especially Germany with its enviable machine tool industry, are pushing the WTO to press the Chinese and other developing nations on this margin. But we know from theory that convergence across nations in income can often rely greatly on “learning by imitating” – as any teacher knows, building simple existing devices creates the knowledge base on which novel ideas can grow. But what of history? Is such learning by imitation historically important, as claimed by people like David Landes?

Richter and Streb consider the German machine tool industry in its own early days: 1877 to the 1930s. A quick case study of J.E. Reinecker, a major tool producer, show that firm buying machines from more advanced US firms from 1873 onward, first replicating parts then replicating whole machines. German law at the time did not give patent protection within Germany to foreign inventions not manufactured in Germany. By the late 1800s, Reinecker was creating many novel inventions on its own, applying for patents in both Europe and the US. During World War I, nonmilitary R&D essentially came to a halt in Germany, and the German firms fell behind once again, leading to a decade where imitation of foreign machines once again predominated. When German firms were innovative, the German government assisted them in getting protection overseas: for instance, after 1909, American toolmakers were exempt from the rule that they had to manufacture in Germany, a rule that presumably would lead to more favorable treatment of German patents by US authorities. Further, the extra delay incurred by patent applicants from overseas versus German firms waxed and waned depending on the innovativeness of German firms; at times of imitation, there were long delays for foreign applicants, while in times of novel invention, foreign firms were not treated so harshly.

Using a custom dataset of German tool patents that are “valuable” (renewal fees were paid for at least 10 years), Richter and Streb show a similar pattern across toolmakers as a whole in Germany: imitation early on, then a series of valuable novel patents, then a collapse in WW1 followed by imitation for another few years. Firm level data is not specific enough, except at the level of a case study, to know how important imitation was to the growth of future successful German tool firms, but the evidence presented is at least suggestive of the fact that German firms who imitated (as listed in a complaint by a US industry lobby) produced many of the future valuable patents in their industry.

This paper is just historical evidence, but it does provide a great example of a more general rule: intellectual property rarely follows the same logic as traditional Ricardian trade. There is no particular reason in standard trade theory why IP rules need be harmonized. Indeed, were I (or essentially any economist who has looked at IP) were to advise a third world government, I would absolutely tell them to enforce much weaker IP than that in Europe or the US. Learning by doing matters.

http://eh.net/eha/system/files/Richter.pdf (Aug 2010 Working Paper – final version in most recent issue of the Journal of Economic History)

The Oncomouse Papers, F. Murray and coauthors (2007, 2009, 2010)

Fiona Murray has a rare background for an economist: she did her PhD at Harvard in Applied Science. Her work generally revolves around the intersection of commercial science, with its secrecy and licenses, and “open science” following the usual academia playbook. In particular, the three present papers all involve a genetic technique which helps researchers make mice ultra-susceptible to cancer, among other diseases: the Oncomice. A Supreme Court case in 1980, in coordination with the Bayh-Dole Act that encouraged university-private sector partnerships, led the Oncomouse method to be patented with exclusive licensing rights held by DuPont. The company insisted on fairly extensive restrictions if you wanted to use mice whose genes had been altered with the DuPont method: you had to buy the mice at high cost, you could not breed them freely, you had to accept oversight of your scientific studies, etc. Of course, there are many other genetic modification techniques, many other animals related to humans, and many other scientific questions that scientists could choose to work on if the Oncomouse license was too strict. How did this restriction on open science affect science further on down the road?

Let me briefly give the headlines from three papers on this question. First is “Do formal intellectual property rights hinder the free flow of scientific knowledge?” by Murray and Stern, published in 2007 in JEBO. Second, “Of Mice and Academics: Examining the Effect of Openness on Innovation” by Murray, Aghion, Dewatripont, Kolev and Stern, a 2009 working paper. Third, “The Oncomouse that Roared,” sole-authored by Murray, in a 2010 issue of the American Journal of Sociology; I, for one, appreciate the good Peter Sellers pun in the paper’s title.

The 2007 paper takes the Oncomouse as anecdote and examines whether patents, in general, on academic techniques lead to less development of further research in that line. In particular, the authors look at publications in a well-known applied science journal Applied Biotechnology. More than half of the papers published in this journal are later associated with a patent by their authors, and nearly everything in the journal plausibly discusses something that could be patented; research in this intersection of basic and applied technology is what Stokes famously called “Pasteur’s Quadrant.” What is great about this paper is the identification: until 2001, patent applications in the US were secret, and patents averaged three years of lag between application and grant. The speed of research in biotech is much faster than in economics, so within three years of publication of an academic article, there is already significant followup research. If patents are an “anti-commons” and the surprise grant of a patent makes researchers wary of following up the associated academic article, then the grant of a patent should lead to a collapse in citations for its associated article. The empirical results suggest that patenting causes between 10 and 15 percent of future expected citations to never occur. The effect is only seen with papers that have at least one public sector or university author, which makes sense given the lack of “surprise” when a private sector firm patents tech that it develops. Though there is no general welfare calculation, I interpret these results are hugely worrying for supporters of Bayh-Dole style policies.

The 2009 paper stresses that, in the authors’ words, “an increase in openness does not simply lead to a temporary increase in follow-on research but instead has an increasing impact over time.” The methodology is very similar to the recent AER on Biological Resource Centers by Furman and Stern which I discussed recently on this site. Essentially, in the late 1990s, the new head of the NIH negotiated simpler, more open, more standard licenses that researchers could use if they wanted to do research using Oncomouse methods (along with one other similar genetic technique). There are also genetic techniques for mice whose patents were never really enforced, such as the University of Utah’s Knock-Out method. The authors gather citations over time for each independent article using mice modified with these technologies. They then look for a change in the (nicely semiparametric) functions of lifetime citations after the NIH negotiations. The increase in openness as a result of the NIH negotiations led to a 20 to 40 percent increase in lifetime citations for treated mouse-articles, an effect that grew over time (science is cumulative!). The effect was mostly seen by new institutions and new researchers using the now “more open” mice. These mouse-articles have mean citations in the hundreds, so the 20 to 40 percent increase is, at first glance, hugely important economically.

Finally, the 2010 AJS provides the extremely interesting anthro- and sociological backstory of the Oncomouse. These types of studies are fun to read as well; phrases like “retired school teacher, turned fancy-mouse breeder, Miss Abbie Lathrop” rarely appear in Econometrica! Murray describes the extremely tight-knit community of mouse genetics laboratories going back to the early 20th century, with traditions of exchange in new strains of mice that, while fairly open, still relied to some extent on non-financial currencies like coauthorship or “gift exchange” in later collaborations. The patenting and harsh license restrictions on the Oncomouse caused a near-riot in the community, and led the NIH to negotiate in the late 90s for more “academic” licensing terms. What is interesting, though, is that this pushback did not lead to a rejection of patenting by other mouse geneticists: indeed, patenting is now common in that field. In the case of defensive patenting to protect an anti-commons, there is no blatant hypocrisy. But beyond this, even when patents are used as currency, the manner in which they are used is still determined by community norms more than it is by the law, and standards of openness and sharing are not totally determined by the legal strength of patents. In many cases today, patented mice are shared freely in the academic community and sold at a price to industry, with follow-on inventions, protected by the patent, more lucrative to private firms wishing to apply academic findings to new products. And indeed, this was exactly the justification of Bayh-Dole. More work needs to be done on whether Bayh-Dole is “good policy”; my guided intuition is still that it is a net negative for social welfare, but the verdict is sufficiently murky that any decent social science on welfare effects would be greatly appreciated by the innovation/science studies community.

http://www.nber.org/~marschke/mice/Papers/murraystern.pdf (2007 JEBO final version)

http://www.economics.harvard.edu/faculty/aghion/files/Of%20Mice%20and%20Academics.pdf (July 2009 Of Mice and Academics working paper)

http://fmurray.scripts.mit.edu/docs/THE_ONCOMOUSE_THAT_ROARED_FINAL.pdf (2010 AJS final working paper)

(To the extent that anyone knows of particularly interesting research in progress on the intersection of open science and the real economy, this is a current research interest of mine and I would love to discuss it – shoot me an email at the address on the “About” page to your left)