Race and Gender in the USPTO: Schuster’s Hard Data for Hard Issues

[I asked some of my RAs to write guest posts this summer, lightly edited by me.  This one is by Jennifer Black, a 3L at Villanova University Charles Widger School of Law]

Intellectual property rights are just that: rights.

Much like other rights, however, they have been unequally granted to people based on factors outside of their control throughout our country’s history. Intellectual property is a means for upward mobility of individuals who, through their own ingenuity, creativity, or otherwise, contribute something of value to our society. It is this exchange of benefits that the patent system is built upon. However, when certain individuals are less likely to reap the rewards of their inventions, they are both disincentivized from creating as well as from engaging with the patent system. Although the extent of these biases is yet unknown, research regarding the subject has been conducted with the intent of identifying and remedying inequity.

The scope of this inequity is difficult to comprehend except by collecting, analyzing, and comprehending the data. Mike Schuster and his coauthors did just that in his article, An Empirical Study of Patent Grant Rates as a Function of Race and Gender (published version in the American Business Law Journal), which examines the patent granting rates as a function of inventors’ races and genders. As scientists and engineers, patent practitioners and examiners will undoubtedly appreciate the amount and quality of his data.

Schuster’s article first focuses on the patent system’s bias against women. While women have come far in their representation in the patent system—from 0.3% of patents in the first 100 years of the United States to 12% in 2016—this is a far cry from equality in a country that is 50.8% female.

Schuster’s study regarding female inventors was twofold: first, he hypothesized that female inventors would be granted patents at lower rates and second, he hypothesized that this disparity would decrease for female inventors with gender nonobvious names. The former hypothesis was supported, yielding a disconcerting result. Women were found to be 62% as likely as male inventors to have their patents granted. This gap narrowed for female inventors without gender identifying names.

Much like female inventors, certain racial minorities were also found to receive patents at lower rates than white counterparts. These numbers, however, were less thoroughly presented and discussed. There were some indications that different racial minorities have different experiences at the USPTO. For example, Asian applicants were indicated to have better outcomes than Black and Hispanic applicants.

Women and minorities’ struggles to obtain patents are a product of aggregating levels of barriers.

First, female and minority students are systematically underrated by teachers and they are discouraged from pursuing STEM and engaging in invention. This has been demonstrated in a number of studies that have teachers rate students’ academic performance generally, academic performance in math and science, and overall intelligence.

Next, women and minorities experience discrimination in employment situations. This is seen both at the forefront, where women and minorities are less likely to get jobs than white male counterparts despite equal credentials. Additionally, Schuster proposed the theory that employers are aware of the USPTO’s implicit biases against these affinity groups, therefore would avoid having these inventors being named first on patent application as a way of increasing odds that the company would receive its patents.

Then, there is the additional layer of implicit bias in the patent system. This was the step analyzed in Schuster’s article.

Minority and female inventors are not the only ones who should care about encouraging and demanding equality in the patent system. It has been proven time and time again that diversity promotes the “progress of science and the useful arts.” If inventors are less successful based on their race and gender, society will lose out on the benefit of diversity in invention. Harm has been aggregating since the founding of the United States—now that we are aware of the still remaining biases, we must focus on remedying them. There have been far too many “Lost Einsteins” for us to remain inactive in the face of bias.

Schuster offered potential solutions to promote equality in the face of systemic bias.

First, he suggested that patent examination should proceed anonymously. While the benefit of this change is clear—it is impossible to discriminate against an inventor you can’t identify—the drawbacks must be mentioned. During examination, inventors are entitled to file their own applications. Transitioning to an anonymous system would not benefit these inventors, as the examiners would be aware of both their pro se status as well as their affiliate groups. This could also result in inventors feeling pressure to seek a patent attorney or agent despite potential financial barriers. Additionally, inventors are permitted to attend examiner interviews, which would negate the benefit of an anonymous system. While this would not affect threshold discrimination (interviews are rarely granted before a rejection has issued), it would not prevent biases from marring the rest of the review of the patent application.

Second, he suggested education as a way to mitigate implicit bias. These biases have been identified in health care, criminal justice, academia, employment, and the judicial as well as the patent system. Each of these systems have proven to benefit from education aimed at the identification, acknowledgment, and mitigation of these biases. However, these trainings must be used in conjunction with real, concerted efforts aimed at preventing such biases from seeping into the patent review process.

Therefore, I believe that the education of patent examiners should be bolstered by two additional factors: maintaining records of inventors’ information and monitoring examiners’ grant rate in light of this information. Much like employment demographic data, applicants maintain the right to refuse to share these details, however, the presence of use of these data would be invaluable. Rather than commentators such as Schuster having to extrapolate the race and gender of various inventors, having this information readily available for internal use and monitoring would allow the Patent Office to prevent such issues from continuing.

While it may cause discomfort among the examiners to know that their grant rates are being monitored, that discomfort is necessary in light of the data. When weighing examiner discomfort against rights granted to all people in the Constitution, the latter more than tips the scale. Growth does not come without difficulty and our system is in dire need of change. I do believe that the increasing depth and regularity of data-based studies such as Schuster’s provide some much-needed accountability in the system and for that, I cannot recommend reading this study enough.

Lucy Xiaolu Wang on the Medicines Patent Pool

Patent pools are agreements by multiple patent owners to license related patents for a fixed price. The net welfare effect of patent pools is theoretically ambiguous: they can reduce numerous transaction costs, but they also can impose anti-competitive costs (due to collusive price-fixing) and costs to future innovation (due to terms requiring pool members to license future technologies back to the pool). In prior posts, I've described work by Ryan Lampe and Petra Moser suggesting that the first U.S. patent pool—on sewing machine technologies—deterred innovation, and work by Rob Merges and Mike Mattioli suggesting that the savings from two high tech pools are enormous, and that those concerned with pools thus have a high burden to show that the costs outweigh these benefits. More recently, Mattioli has reviewed the complex empirical literature on patent pools.

Economics Ph.D. student Lucy Xiaolu Wang has a very interesting new paper to add to this literature, which I believe is the first empirical study of a biomedical patent pool: Global Drug Diffusion and Innovation with a Patent Pool: The Case of HIV Drug Cocktails. Wang examines the Medicines Patent Pool (MPP), a UN-backed nonprofit that bundles patents for HIV drugs and other medicines and licenses these patents for generic sales in developing countries, with rates that are typically no more than 5% of revenues. For many diseases, including HIV/AIDS, the standard treatment requires daily consumption of multiple compounds owned by different firms with numerous patents. Such situations can benefit from a patent pool for the diffusion of drugs and the creation of single-pill once-daily drug cocktails. She uses a difference-in-differences method to study the effect of the MPP on both static and dynamic welfare and finds enormous social benefits.

On static welfare, she concludes that the MPP increases generic drug purchases in developing countries. She uses "the arguably exogenous variation in the timing of when a drug is included in the pool"—which "is not determined by demand side factors such as HIV prevalence and death rates"—to conclude that adding a drug to the MPP for a given country "increases generic drug share by about seven percentage points in that country." She reports that the results are stronger in countries where drugs are patented (with patent thickets) and are robust to alternative specifications or definitions of counterfactual groups.

On dynamic welfare, Wang concludes that the MPP increases follow-on innovation. "Once a compound enters the pool, new clinical trials increase for drugs that include the compound and more firms participate in these trials," resulting in more new drug product approvals, particularly generic versions of single-pill drug cocktails. And this increase in R&D comes from both pool insiders and outsiders. She finds that outsiders primarily increase innovation for new and better uses of existing compounds, and insiders reallocate resources for pre-market trials and new compound development.

Under these estimations, the net social benefit is substantial. Wang uses a simple structural model and estimates that the MPP for licensing HIV drug patents increased consumer surplus by $700–1400 million and producer surplus by up to $181 million over the first seven years of its establishment, greatly exceeding the pool's $33 million total operating cost over the same period. Of course, estimating counterfactuals from natural experiments is always fraught with challenges. But as an initial effort to understand the net benefits and costs of the MPP, this seems like an important contribution that is worth the attention of legal scholars working in the patent pool area.

Pushback on Decreasing Patent Quality Narrative

It's been a while since I've posted, as I've taken on Vice Dean duties at my law school that have kept me busy. I hope to blog more regularly as I get my legs under me. But I did see a paper worth posting mid-summer.

Wasserman & Frakes have published several papers showing that as examiners gain more seniority, their time spent examining patents decreases and their allowances come more quickly. They (and many others) have taken this to mean a decrease in patent quality.

Charles A. W. deGrazia (University of London, USPTO), Nicholas A. Pairolero (USPTO), and Mike H. M. Teodorescu (Boston College Management, Harvard Business) have released a draft that pushes back on this narrative. The draft is available on SSRN, and the abstract is below:

Prior research argues that USPTO first-action allowance rates increase with examiner seniority and experience, suggesting lower patent quality. However, we show that the increased use of examiner's amendments account for this prior empirical finding. Further, the mechanism reduces patent pendency by up to fifty percent while having no impact on patent quality, and therefore likely benefits innovators and firms. Our analysis suggests that the policy prescriptions in the literature regarding modifying examiner time allocations should be reconsidered. In particular, rather than re-configuring time allocations for every examination promotion level, researchers and stakeholders should focus on the variation in outcomes between junior and senior examiners and on increasing training for examiner's amendment use as a solution for patent grant delay.

In short, they hypothesize (and then empirically show with 4.6 million applications) that as seniority increases, the likelihood of examiner amendments goes up, and it goes up on the first office action. They measure how different the amended claims are, and they use measures of patent scope to show that the amended applications are no broader than those that junior examiners take longer to prosecute.

Their conclusion is that to the extent seniority leads to a time crunch through heavier loads, it is handled by more efficient claim amendment through the examiner amendment procedures, and quality is not reduced.

As with all new studies like this one, it will take time to parse out the methodology and hear critiques. I, for one, am glad to hear of rising use of examiner amendments, as I long ago suggested that as a way to improve patent clarity.

The Stanford NPE Litigation Database

I've been busy with grading and end of year activities, which has limited blogging time. I did want to drop a brief note that the Stanford NPE Litigation Database appears to be live now and fully populated with 11 years of data from 2007-2017. They've been working on this database for a long while. It provides limited but important data: Case name and number, district, filing date, patent numbers, plaintiff, defendants, and plaintiff type. The database also includes a link to Lex Machina's data if you have access.

The plaintiff type, especially, is something not available anywhere else, and is the key value of the database (hence the name). There are surely some quibbles about how some are coded (I know of one where I disagree), but on the whole, the coding is much more useful than the "highly active" plaintiff designations in other databases.

I think this database is also useful as a check on other services, as it is hand coded and may correct errors in patent numbers, etc., that I've periodically found. I see the value as threefold:

1. As a supplement to other data, adding plaintiff type
2. As a quick, free guide to which patents were litigated in each case, or which cases involved a particular patent, etc.
3. As a bulk data source showing trends in location, patent counts, etc., useful in its own right.

The database is here: http://npe.law.stanford.edu/ Kudos to Shawn Miller for all his hard work on this, and to Mark Lemley for having the vision to create it and get it funded and completed.

Measuring Patent Thickets

Measuring the effect of patenting on industry R&D is an age old pursuit in innovation economics. It's hard. The latest interesting attempt comes from Greg Day (Georgia Business) and Michael Schuster (OK State, but soon to be Georgia Business). They look at more than one million patents to determine that large portfolios tend to crowd out startups. I'm totally with them on that. As I wrote extensively during troll hysteria, patent portfolios and assertion by active companies can be harmful to innovation.

The question is how much, and what to do about it. Day and Schuster argue in their paper that the issue is patent thickets, as their abstract shows. The draft article Patent Inequality, is on SSRN:

Using an original dataset of over 1,000,000 patents and empirical methods, we find that the patent system perpetuates inequalities between powerful and upstart firms. When faced with growing numbers of patents in a field, upstart inventors reduce research and development expenditures, while those already holding many patents increase their innovation efforts. This phenomenon affords entrenched firms disproportionate opportunities to innovate as well as utilize the resulting patents to create barriers to entry (e.g., licensing costs or potential litigation).

A hallmark of this type of behavior is securing large patent holdings to create competitive advantages associated with the size of the portfolio, regardless of the value of the underlying patents. Indeed, this strategy relies on quantity, not quality. Using a variety of models, we first find evidence that this strategy is commonplace in innovative markets. Our analysis then determines that innovation suffers when firms amass many low-value patents to exclude upstart inventors. From these results, we not only provide answers to a contentious debate about the effects of strategic patenting, but also suggest remedial policies to foster competition and innovation.

The article uses portfolio sizes and maintenance renewals to find correlations with investment. They find, unsurprisingly, that the more patents there are in portfolios in an industry, the lower the R&D investment. However, the causal takeaways from this seem to me to be ambiguous. It could be the patent thickets that cause that limitation, or it could simply be that industries dominated by large players are less competitive and drive out startups. There are plenty of (non-patent) theorists that would predict such outcomes.

They also find that firms with large portfolios are more likely to renew their patents, holding other indicia of patent quality (and firm assets) equal. Even if we assume that their indicia of patent quality are complete (they use forward cites, number of inventors, and number of claims), the effect they find is really, really small. For the one reported industry - biology, the effect is something like a -0.00000982 percent likelihood of lapse for each additional patent. This is statistically significant, I assume, because of the very large sample size and a relatively small variation. But it seems barely economically significant. If you multiply it out, it means that each patent is 1% more likely to lapse for every 1,000 patents in the portfolio (that is, from 50% chance of lapse, to 49% chance of lapse. For IBM - the largest patentee of the time with about 25,000 patents during the relative time period, it's still only a 25% change. Most patentees, even with portfolios, would be nowhere near that. I'm just not sure what we can read into those numbers - certainly not the broad policy prescriptions suggested in the paper, in my view.

That said, this paper provides a lot of useful information about what drives portfolio patenting, as well as a comprehensive look at what drives maintenance rates. I would have liked to see litigation data mixed in, as that will certainly affect renewals one way or the other, but even as is, this paper is an interesting read.

How Does Patent Eligibility Affect Investment?

David Taylor (SMU) was interested in how patent eligibility decisions at the Supreme Court affected venture investment decisions, so he thought he would ask. He put together an ambitious survey of 14,000 investors at 3000 firms, and obtained some grant money to provide incentives. As a result, he got responses from 475 people at 422 firms. The response rate by individual is really low, but by firm it's 12% - not too bad. He performs some analysis of non-responders, and while there's a bit of an oversample on IT and on early funding, it appears to be somewhat representative.

The result is a draft on SSRN and forthcoming in Cardozo L. Rev. called Patent Eligibility and Investment. Here is the abstract:

Have the Supreme Court’s recent patent eligibility cases changed the behavior of venture capital and private equity investment firms, and if so how? This Article provides empirical data about investors’ answers to those important questions. Analyzing responses to a survey of 475 investors at firms investing in various industries and at various stages of funding, this Article explores how the Court’s recent cases have influenced these firms’ decisions to invest in companies developing technology. The survey results reveal investors’ overwhelming belief that patent eligibility is an important consideration in investment decisionmaking, and that reduced patent eligibility makes it less likely their firms will invest in companies developing technology. According to investors, however, the impact differs between industries. For example, investors predominantly indicated no impact or only slightly decreased investments in the software and Internet industry, but somewhat or strongly decreased investments in the biotechnology, medical device, and pharmaceutical industries. The data and these findings (as well as others described in the Article) provide critical insight, enabling evidence-based evaluation of competing arguments in the ongoing debate about the need for congressional intervention in the law of patent eligibility. And, in particular, they indicate reform is most crucial to ensure continued robust investment in the development of life science technologies.

The survey has some interesting results. Most interesting to me was that fewer than 40% of respondents were aware of any of the key eligibility decisions, though they may have been vaguely aware of reduced ability to patent. More on this in a minute.

There are several findings on the importance of patents, and these are consistent with the rest of the literature - that patents are important for investment decisions, but not first on the list (or second or third). Further, the survey finds that firms would invest less in areas where there are fewer patents - but this is much more pronounced for biotech and pharma than it is for IT. This, too, seems to comport with anecdotal evidence.

But I've always been skeptical of surveys that ask what people would do - stated preferences are different than revealed preferences. The best way to measure revealed preferences would be through some sort of empirical look at the numbers, for example a differences-in-differences approach before and after these cases (though having 60% of the people say they haven't heard of them would certainly affect whether the case constitutes a "shock" - a requirement of such a study).

Another way, which this survey attempts, is to ask not what investors would do but rather ask what they have done. This amounts to the most interesting part of the survey - investors who know about the key court opinions say they have moved out of biotech and pharma, and into IT. So much for Alice destroying IT investment, as some claim (though we might still see a shift in the type of projects and/or the type of protection - such as trade secrets). But more interesting to me was that there was also a similar shift among those folks who claimed not to know much about patent eligibility or think it had anything to do with their investment. In other words, even for that group who didn't actively blame the Supreme Court, they were shifting investments out of biotech and pharma and into IT.

You can, of course, come up with other explanations - perhaps biotech is just less valuable now for other reasons. But this survey is an important first step in teasing out those issues.

There are a lot more questions on the survey and some interesting answers. It's a relatively quick and useful read.

Making Sense of Unequal Returns to Copyright

Typically, describing an article as polarizing refers to two different groups having very different views of an article. But I read an article this week that had a polarizing effect within myself. Indeed, it took me so long to get my thoughts together, I couldn't even get a post up last week. That article is Glynn Lunney's draft Copyright's L Curve Problem, which is now on SSRN. The article is a study of user distribution on the video game platform Steam, and the results are really interesting.

The part that has me torn is the takeaway. I agree with Prof. Lunney's view that copyright need not be extended, and that current protection (especially duration) is overkill for what is needed in the industry. I disagree with his view that you could probably dial back copyright protection all the way with little welfare loss. And I'm scratching my head over whether the data in his paper actually supports one argument or the other. Here's the abstract:

No one ever argues for copyright on the grounds that superstar artists and authors need more money, but what if that is all, or mostly all, that copyright does? This article presents newly available data on the distribution of players across the PC videogame market. This data reveals an L-shaped distribution of demand. A relative handful of games are extremely popular. The vast majority are not. In the face of an L curve, copyright overpays superstars, but does very little for the average author and for works at the margins of profitability. This makes copyright difficult to justify on either efficiency or fairness grounds. To remedy this, I propose two approaches. First, we should incorporate cost recoupment into the fourth fair use factor. Once a work has recouped its costs, any further use, whether for follow-on creativity or mere duplication, would be fair and non-infringing. Through such an interpretation of fair use, copyright would ensure every socially valuable work a reasonable opportunity to recoup its costs without lavishing socially costly excess incentives on the most popular. Second and alternatively, Congress can make copyright short, narrow, and relatively ineffective at preventing unauthorized copying. If we refuse to use fair use or other doctrines to tailor copyright’s protection on a work-by-work basis and insist that copyright provide generally uniform protection, then efficiency and fairness both require that that uniform protection be far shorter, much narrower, and generally less effective than it presently is.

The paper is really an extension of Prof. Lunney's book, Copyright's Excess, which is a good read even if you disagree with it. As Chris Sprigman's JOTWELL review noted, you either buy in to his methodology or you don't. I discuss below why I'm a bit troubled.

Lunney exploits a brief data delivery by Steam that allowed simple algebra to calculate the number of users for each game. There are a few problems with the calculations (assumptions, potential errors, etc), but not so many that I'm going to spend time quibbling with them. So, let's start with the L-Curve, which forms the basis for the article. Here is the graph of user count:


It looks like an L, alright, but the scale bothered me.  So, I looked at the 1000th most popular game, which appears to be about 0 on this chart. But the game (called Cities in Motion) had at the time of the dump (about June 2018) 237,970 users.  At the 70% takehome rate on $19.99, that's revenues of $3.3 million. And that doesn't count the 9 add-ons that range from $2 to $5 each. Nor does it include the followup, Cities in Motion 2, which sits in position 626 with 451,407 users ($6.3 million revenues plus another several add-ons). Cities in Motion 2 also looks to be nearly zero on this curve.

Indeed, the scale is so off, it reminded me of this global warming chart from the National Review:

So, I thought I would be clever and cut off the top outliers to show a more linear progression. But all I got was another L-Shaped graph like Prof. Lunney did. Indeed, no matter where I cut, it was always L-Shaped. The reason for this is that the revenue growth is exponential. Lunney notes as much as well, just to be clear. Now, people misuse that word, but it actually applies here. The number of users at each rank is some exponential power higher than the one before it. So I did what people sometimes do with an exponential curve that's difficult to graph - I took a log of it.

Here's the chart of the logged number of players:
 

The relatively straight line shows a fairly constant exponential growth, though there is a large dropoff at the bottom, and some big outliers at the top.

What to make of all this? It is here where we diverge a bit. Prof. Lunney's basic position is that we don't need super-strong copyright to protect the folks at the very top. They would have made those games for a lot less. Therefore, copyright must, if it is to exist, be there for the large middle. And the problem with the L-Curve is that the large middle isn't making any money.

There are two ways to approach his concerns. The first is the theory, and the second is the empirics.

The primary theoretical answer is that the large middle creates incentives for developers hoping to become outliers. Prof. Lunney calls this the lottery effect, and he poo-poos it as not terribly valid. Let's just say I disagree with him, but I don't want this post to be about that. I frame this question as an expected value question, which means that in a repeat and uncertain game, one must have supracompetitive returns to offset all the losses when things flop. I mathematically illustrated this in an article I wrote nearly 20 years ago, which demonstrated that cutting off copyright protection once some expected value of profits was reached yielded lower expected value than the alternative. Ironically, this proposal is exactly professor Lunney's here today, and I disagree with it as much now as I did then. If you claim that the middle isn't making money, then by cutting off outliers you're just making your average creator earn even less money, which will push incentives downward.

Now, this isn't to say that Prof. Lunney doesn't have a point. As noted above, I agree that some supra-competitive rents may be too much. Where we differ in large part is our views of the uncertainty involved and the motives for participating.

But I'll put that aside, and focus on the second question - even without the lottery effect, does the data support a theory that copyright is providing nothing to the vast middle?

It's hard to get a sense from the data, so I thought I would look at every tenth percentile (deciles):
1. Team Fortress 2, 50,191,347 users, released Oct 2007, free to play (since 2011), first person shooter, formerly $20, developer: 41 games
2. Trick and Treat - Visual Novel, 164,544 users, released Dec. 13, 2016, free to play (visual novel), developer: 3 visual novels
3. Hunahpu: way of the Warrior, 48,807 users, released April 10, 2017, $3.99, very simple graphic landscape game (like Mario Bros. or Defender), developer: 8 games
4. Caravan, 19,612 users, released Sep. 30, 2016, $9.99, low-graphic RPG, developer: only game, publisher: 50 games
5. The Fidelio Incident, 8,547 users, released May 23, 2017, $9.99, first-person adventure, developer: only game
6. Rubek, 4,163 users, released Oct. 14, 2016 , $2.99, very simple graphic strategy game, developer: 2 games
7. Soko Match, 1,904 users, released Sep. 16, 2016, $.99, extremely simple graphic strategy game, developer: 3 games
8. Q-YO Blaster, 828 users, released Jan. 15, 2018, $3.99, pixel graphic landscape game, developer: 1 game
9. EquiMagic - Galashow of Horses, 343 users, released Dec. 19, 2017, $9.99, simple graphic horseshow simulation (trotting horses), developer: 15 games
10. Over My Dead Body (For You), 119 users, released Sept. 11, 2017, $9.99, very simple graphic strategy game, developer: 1 game

Doing this exercise was interesting, and revealed a few patterns to be explored. First, price seems to matter, but Prof. Lunney's data does not take that into consideration. Free games reign supreme, but cheap games do not. This implies that a) there's a quality tradeoff, b) that in-game revenues are not being counted, and c) that perhaps some low-user games make money because they are cheap to develop.

Also, many firms appear to be repeat players. Some of the followons have more users, and some have less. A full study of repeat play and incentives to create better games would be interesting.

Another takeaway is that age seems to matter. A lot. I did a simple regression on the user count (rather the log of user count) and the steamid (which is smaller for older games), and that simple variable explains 40% of the variation in user counts. Older games have more users. Prof. Lunney might consider that for future analysis. That said, there's still remarkable inequality even in what remains after age - so the question remains whether the vast middle must be linear in order for copyright to make sense.

I'm not so sure. but before I consider some of Prof. Lunney's analysis, I should note that in large part I agree with many of the things he's arguing. For example, the existence of strong copyright won't force the unwilling to pay - they will otherwise pirate. On the flip side, content management systems, like Steam's, largely eliminate the need for pure piracy copyright, as they limit copying even in the absence of law. Copyright's added value in platforms like this is much more in avoiding knock-offs, as PUBG (No. 3 on the list) alleged when Fortnite came out with a similar battle royale system.

Now, on to some specifics:
Does the "L-Curve" mean that the average producer can't make a profit? No. I contacted a programmer right around the median, with a $3.99 game. He told me that he worked on it minutes at a time, off and on, for a couple years. He confirmed that the numbers sounded right (he actually had more sales associated with bundles, but the people didn't play), and that he made a very small profit. This was a side business, and the world got a program it wouldn't otherwise have. But he also didn't believe that copy protection helped him make that money.

That's the median creator, still making a profit. How far up or down the line do we go? Prof. Lunney says: "As soon as two games are produced without copyright or with extremely narrow copyright, the welfare losses associated with the excess incentives for these two games likely outweigh the welfare gains from enacting or expanding copyright to ensure the expected profitability of the third game." I think it may be this statement that gives me the most heartburn.

There are a few reasons I'm troubled by this. First, this seems to assume that all consumer welfware can come from owning a couple games - that there's simply nothing to be gained by having more games (that somehow isn't stifled by limiting copying, at least). But the data belies that. These user counts are not individual - if you add them all up, they add to 1.7 billion or so. And Steam had about 150 million users at that time, which means that every user played 10 games on average. So if we stop at 2 games we have a shortage - players willing to pay for games that may or may not be created.

Second, we don't know what the quality of games would look like. If firms are limited to self help protections, it may be that their games will be of lesser quality, taking less investment, and otherwise not fulfilling demand. Or maybe they won't. We certainly can't know this from the data here.

Third, as noted above, Prof. Lunney believes that there is a lot less uncertainty than there is. At one point, he notes: "But whatever the reason some profit motivated production will occur even without copyright, and under our assumptions, the most popular videogames will be produced first." While it's true that the older games have more users, they are more popular because they are older, not because they were created first. I am highly skeptical that producers know in advance which games will be highly played. Many flop. This ties to my point above about expected value - where one does not know whether a game will be successful, one cannot assume that the first one out will be the best one.

Fourth, Prof. Lunney reaches his conclusions by making assumptions about the welfare loss associated with copyright at the top as compared to the welfare gain through added incentives at the median. Those assumptions may work for patents (I don't know enough to know). They might even work for songs, to the extent that songs are limiting new creation. But I seriously question them in video games for several reasons. First, in a world where content management systems control much, it is unclear what copyright is restricting at the top end. Some copying of actual characters, I suppose, but is it really dollar for dollar? Second, in a world where much gaming is based on underlying engines, such that gameplay is already half-handled, what limitations are there? Again, it seems to be specific artwork rather than free reuse of games (which, are already free at the top end anyway). Is the restriction on artwork so great that it's causing loss of welfare? I don't know, but I doubt it. The reason people spend money on free-to-play Fortnite is for the original skins that cost money (as stupid as I think that is). If the Fortnite skins look like everyone else's then why bother? Note, of course, that the copyright incentive at the low end may also be too low. It's the upper middle range, where there's a real investment (which is less than half the games, apparently) that matters to me, not the median.

Fifth, the analysis relies on three assumptions that Prof. Lunney lays out: "For this to be the case, we need: (i) revenue to be correlated with demand, so that a more popular game earns more than a less popular game; (ii) for each game to have a constant cost, and thus higher demand games are more profitable per unit cost; and (iii) expected demand cannot be completely uncertain ex ante." The article admits that item (ii) is difficult for videogames, and my analysis of the ten games above shows that. Item (i) is also difficult to show in practice; the pricing varies so much that some games with 4000 users make $40,000 and some games with 4000 users make $12,000. Item (iii) probably holds - expected demand is not completely uncertain, especially given quality of investment, but it's probably a lot more uncertain than Prof. Lunney gives credit for. In any event, the assumptions of his analysis don't hold up on their own terms.

I suppose the real issue for me comes down to this passage in the article (in which Prof. Lunney suggests that revenues be capped at costs, a point that I disagreed with above):

Alternatively, some might insist that it is neither fair nor efficient that Sheeran should earn the same for Shape of You [the number highest earning song] as someone earns for a marginal song to which hardly anyone listens. But it is entirely fair and efficient. In a competitive market economy, a heart surgeon who saves your life earns the same market reward as a doctor who gives you a vaccine. Neither earns the value of their work, in the sense of the maximum reservation price a patient could be forced to pay to avoid dying. Rather, both earn the cost of the service they provided. To the extent the market prices for the surgery and the vaccine differ, that price difference should reflect an underlying difference in cost. In a competitive market economy, it is not value, but cost that dictates what you earn. If copyright intends to create a market that mimics a competitive market, it should strive to do the same. As a result, if Shape of You cost the same as a marginal song to author and distribute, then that cost is all the market return that fairness and efficiency require each to earn.

I'm troubled by this analysis and analogy in a couple of ways. Primarily, it mixes the apples of price per unit and the oranges of total demand. Sheeran and noname song both earn the same cost: Spotify pays them exactly the same per play. Sheeran makes more money not because the price of his song is higher, but because more people want it. There are no rents in his individual demand/supply curve; indeed, if he knew the popularity, he probably would have charged more (see Taylor Swift refusing to go on Spotify). Now, Lunney is saying that if too many people want the song, then it's not efficient because there are others who could copy it for free and that's a welfare loss because the gain in incentives to create music is outweighed by the joy we would all get if we could just listen to the music for free once Sheeran got enough to make the music in the first place. But if that's the argument he wants to make, he should own it, rather than claiming that somehow Sheeran is selling something at other than the cost of making it. Because if you take this argument to the extreme, it means that even though the heart surgeon has now exceeded the cost of running the practice by June (it was an unexpectedly cholesterol filled year), then the incentives for people to become heart surgeons are outweighed by the value we'd all get if we just forced the surgeon to operate for free after July 1. Maybe it's ok for copyright because of "promote the progress" in the constitution and all, but it's a pretty unsettling way to look at the world, in my view.

I'm also troubled because this treats music (and other copyrighted works) as fungible goods, as you would in a market. Sheeran and noname - either one is the same, so if they are priced similarly then they should make similar profits. But that's not how even efficient markets work. In an efficient market, a better product has a larger demand, and thus garners more revenue because more people will buy it. Even with a flat marginal cost (and it's not actually flat, even with music), if the demand curve shifts out, more people will buy the product at the same price. And so cutting off the revenues in fact distorts the market. It's a wealth transfer. It may be justified in the name of welfare maximization (though I'm not convinced), but again, Prof. Lunney should own that. He proposes taking an otherwise efficiently behaving market, in which everyone sells the similar but slightly differentiated goods for the same price, and putting a thumb on the scale to cap demand at the competitive price before it is sated, so that consumers and have all of the welfare associated with not having to pay for a product they prefer to another product they could just as easily buy for the exact same cost but do not prefer. This is not an efficient market proposal, in my view. (On a side note, it's not even clear that Spotify is the way to measure this, as customers pay a fixed price, and can consume as much of the product as they want, detaching demand analysis from pricing).

To recap this very long rant post, I agree with Prof. Lunney that we likely don't need more copyright protection to get more video games, or music, or books, or whatever. Indeed, we likely would be fine with a lot less of it. But I just cannot get to that conclusion from the data presented here, except to say that a lot of people seem to make video games on Steam without the expectation of huge profits.