Category Archives: Technology Transfer

“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 Eff ect 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)

“Patent Laws, Product Lifecycle Lengths, and the Global Sourcing Decisions of U.S. Multinationals,” L. K. Bilir (2011)

It’s something of a mystery in the IP literature why small, developing countries would ever enforce intellectual property rules. The standard tradeoff is higher prices in exchange for more innovation. But the innovation is useful no matter where it comes from. So unless you are a relatively large, prosperous country, it’s unlikely to be worthwhile trading off higher prices within your country due to the limited monopoly of IP for a tiny increase in inventive activity. Indeed, the US did not enforce foreign copyrights, for example, until the 20th century, much to the consternation of Charles Dickens. Of course, in practice many nations strengthen IP laws because they are coerced into doing so in exchange for other beneficial trade liberalization – see the TRIPS agreement. But outside of trades of this type, might there be another reason for strengthening IP in the developing world?

L. Kamran Bilir argues that there might be in a new working paper which she presented here earlier this week. Multinationals make up the bulk of international trade (and international technology transfer) and have many options of where to place their new plants. But they are worried that if they locate in a region with weak IP, there is a strong incentive for some local company in that region to rip off their product. Assume that such imitation can only happen if a plant or affiliate plant of the MNC is located in the foreign country. Assume also that figuring out how to imitate involves some stochastic investment by a would-be imitator. A simple model gives the following predictions. First, products whose commercial usefulness is very short don’t worry about imitators: by the time the iPhone is knocked off, Apple has a new model ready to go. These industries will always produce overseas in order to access cheap labor, regardless of formal IP laws. Second, products whose commercial usefulness is of moderate length might be coerced to locate overseas earlier in the product lifecycle if, at the margin, IP laws strengthen. The idea is that, with relatively stronger IP, the incentive to imitate will be weaker because stronger IP lessens the expected profits the imitator can expect to make; you might imagine “stronger IP” as “higher probability that the government will shut you down for selling products that violate a foreign patent.” Third, products with long commercial lifecycles spend less of the product lifecycle producing overseas after an IP strengthening than the marginal intermediate-length products. The response of MNC offshoring to IP changes, then, is nonmonotonic in the product lifecycle length.


Bilir then uses data, in a number of different specifications, from dozens of countries and over 30 years. She finds precisely this nonmonotonic effect. The measure of “average product lifecycle” (or, in another specification, 90th percentile product lifecycle) is constructed from forward citations in the US patent database by industry, and of course you might question this portion of the methodology, but it’s not ridiculous on face; you might also not like the measure of IP strength used, though it is pretty standard in this literature for better or worse. The nonmonotonic effect of stronger third world patents is seen not just in affiliate sales, but also in affiliate size and in the number of affiliates employed. A sensible interpretation is that third world countries can use stronger IP protection to attract MNC investment, but that policies will be unsuccessful for firms like software with short lifecycles and will be relatively unsuccessful with products like machine tools that have long lifecycles. What’s nice here is that the impact of IP on MNC location is identified in and of itself: IP changes often happen concurrently with other liberalizations in a nation’s economy. The identifying power here is that year and country fixed effects will pick up those other liberalizations while the differential impact of the IP strengthening across sectors with different product lifecycles (presumably affected in similar ways by non-IP reforms) let us isolate IP.

Two more things I would like to see. First, the formal tradeoff between reliance on secrecy and reliance on patents seems important here. This is related both to the ease of knocking off a product (drugs, for example, are easy to reverse engineer) and the importance of local legal systems in maintaining non-patent contracts like “do not disclose” policies. Perhaps this should enter the model? Second, I have an idiosyncratic preference for welfare estimates in policy-related papers, even if such estimates are only back-of-the-envelope. In this case, assuming standard learning-by-doing and technology transfer to affiliates, is it worth it for, say, China or Nigeria to increase their enforcement of IP (raising domestic prices) in exchange for some new jobs and tech transfer for the new MNC affiliates? A rigorous discussion here would lengthen the paper too much – it is already quite a monster – but a two page rough-and-dirty estimate would be useful indeed.

http://www.stanford.edu/~kbilir/Bilir_IP_and_MNCs.pdf (July 2011 Working Paper)

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