Nevertheless, monetary economics can be difficult, and there is a lot of confusion out there. It seems that most of the confusion is due to two errors. The first is that Bitcoin appreciation is deflationary, and therefore, recessionary. A variant is that Bitcoin volatility will create massive booms and busts in the Bitcoin economy. I think that this point has been decisively refuted by Jerry Brito. The macroeconomic effects of a currency have to do with its unit-of-account status, not with its medium-of-exchange status. Consequently, unless people begin (foolishly) denominating their long-term contracts in Bitcoin, the cryptocurrency won’t have any macroeconomic drawbacks.

As Bitcoin skeptics have come to terms with Jerry’s point, they have resorted to a second error, that Bitcoin’s long-run fixed supply would generate persistent, long-run deflation, which will cause hoarding of the currency. This would make it unsuitable as a medium of exchange, because no one would be willing to exchange it. Transactional demand for Bitcoin would be zero. Matt Yglesias and Matt O’Brien make versions of this argument.

I think that Tim Lee has done a good job of refuting this line of thinking both on Twitter and in two posts at Forbes. But his arguments haven’t satisfied everyone. O’Brien in particular seems to be doubling down on Twitter.

@binarybits I think the mistake you make in your deflation post is that it’s not a one-time deflation, even if massive. It’s *constant*.

— Matt O’Brien (@ObsoleteDogma) April 12, 2013

@binarybits Which means the incentive to hoard Bitcoins and earn a return on them is always there. Which means it’s not a good currency.

— Matt O’Brien (@ObsoleteDogma) April 12, 2013

@binarybits My point is: it’s doomed to boom-bust, which makes it useless as a currency. Which means only a subgroup of a subgroup

— Matt O’Brien (@ObsoleteDogma) April 12, 2013

The problem is that in Yglesias’s and O’Brien’s posts on Bitcoin, I have not come across the word “arbitrage.” This is a pretty good sign that their claims about the long-run equilibrium are not rigorous. The long-run equilibrium must be defined by a “no arbitrage” condition—if arbitrage between currencies is possible, then we are not in equilibrium.

Let’s try to write down an equation that describes a first approximation of this condition:

At a high level, this equation says that the expected return to holding dollars has to equal the risk- and liquidity-adjusted expected return to holding bitcoins. On the left side of the equation is the return to holding dollars, which is given by the nominal interest rate on dollars, . On the right side of the equation, represents the expected appreciation in bitcoins from time t to time t + k, while is the risk premium and  is the liquidity premium. I am assuming for now that it is not possible to have a bitcoin-denominated loan, and therefore no interest rate on bitcoins, although I could imagine that there might be an overnight rate of some sort. But for now, assume that the equalization of returns has to happen via appreciation.

What this equation makes clear is that there is no free lunch from hoarding bitcoins. Bitcoin hoarders will be compensated for the risk they are bearing, for the illiquidity of the Bitcoin market, and for the opportunity cost of holding bitcoins, but for nothing else.

The fact that bitcoins are expected to appreciate in value does not increase the incentive to hoard bitcoins at the margin. Instead, all of the change in the value of bitcoins happens in the spot rate, . The price of bitcoins adjusts now to accommodate any future expected increase in the value of bitcoins, and there are no further gains from hoarding bitcoins. There is therefore no disincentive to transactional use of bitcoins.

I expect further that in the future, forward contracts on the Bitcoin-dollar exchange rate will reduce or eliminate the risk premium, and more sophisticated entrants (read: hedge funds) into the Bitcoin market will supply additional liquidity, making even the nominal return to holding bitcoins about the same as that of holding other currencies. The model above is not meant to be a complete account of the market for bitcoins. But I think it serves as a good baseline for thinking about what claims about an incentive to hoard entail.

Finally, I’ll note that even if almost all of the eventual 21 million bitcoins are “hoarded,” a mere 1000 bitcoins would be more than adequate to supply the transactional needs of an economy as large as the United States. Each bitcoin is divisible into 10^8 “satoshis,” and there are only around 10^9 dollars, or 10^11 cents, in circulation. One thousand bitcoins would be 10^11 satoshis. If each satoshi equalled one cent, the market capitalization of bitcoin would have to rise to 2.1 quadrillion dollars. When the market capitalization exceeds that figure, I will concede that bitcoins have been over-hoarded.

— The air pollution impacts of modern electrical power generation, industrial activity, and transportation can’t be efficiently bargained away because the transaction costs are way too high.

— So-called “public goods” like basic scientific research or musical recordings will be underproduced absent some combination of state subsidy and state-created intellectual property monopolies.

— Basic infrastructure (roads, electrical lines, sewers) won’t be provided properly without some eminent domain and they won’t be priced correctly due to the monopolistic nature of the market.

— Absent deposit insurance and regulation, banks will be subject to runs and economically destructive panics.

— Without a central bank minding the store properly, the entire macroeconomy will fall into periodic recessions lasting months or years.

Since these five factors color all market activity, Matt says, there is no such thing as pure market activity, and therefore no distribution of wealth that would result if there were no government provision of pollution abatement, public goods, and so on.

In my view, Matt’s argument is not compelling. Take first his list of “minor exceptions” to the general rule that markets work best. Do we need state intervention to keep air pollution down to acceptable levels? There has never been a completely laissez-faire society that has had dirty air, so it is difficult to say. What we do know from the work of Elinor Ostrom is that we don’t need state intervention in all cases to solve problems associated with water usage or overfishing, which are structurally similar to that of air pollution (i.e., they have high transaction costs). It turns out that the threat of state-sanctioned violence is not the only solution to repeated prisoner’s dilemmas, even when transaction costs are high, either in theory or in practice.

What about other public goods? It is strange to me that Matt chose copyright protections for musical recordings as an example, because I might favor eliminating such protections even as a matter of marginal policy reform. If musicians could no longer make money from selling recordings, they would still produce recordings as advertisements for their live performances. Musicians would tour more, and the live music scene might become more vibrant. It’s not at all clear to me that it would be worse than the status quo. I don’t favor eliminating government funding for basic research, and indeed, at the margin, I would favor more such funding. But similarly, without government subsidies, research would still occur, philanthropists would still donate to universities, and so on. While the result may be some modest “underproduction” of basic research, it still seems unlikely that but for government funding of basic research, we would be living in caves.

I’ve never understood the argument about roads, since as best I can tell, roads have always existed, even in cases in which governments did not have transportation policy. The common law, which itself originated without the state, seems to have made adequate allowance for solving the anticommons problem via various kinds of easements and property rules. Matt also argues that private infrastructure would be monopolistically priced, but I think he fails to consider the possibility of customer-owned mutuals as an alternative to both government and for-profit firms.

Without deposit insurance, would banks face constant runs and panics? This is at best controversial among monetary historians. Modern economists tend to blame bank failures during the Great Depression more on restrictions on interstate banking and the concomitant lack of geographic diversification than on the lack of deposit insurance. New Zealand does not today have deposit insurance; it is not a financial hellscape. If deposit insurance were eliminated, banks would become more sober, prudent institutions than they are today, which may not be such a bad outcome. I favor the elimination of federal deposit insurance, and I don’t think I am very alone. Certainly, it is not one of my most out-of-the-mainstream policy views.

I confess to chortling a little at Matt’s line about central banks. Months or years of recession?! Unimaginable. With central banks in charge, the US is experiencing a years-long slump, Japan is experiencing a decades-long stagnation, and Europe is…fucked. Central banks were also at the helm during the Great Depression. My monetary policy views are conventional, but the central banking track record is not something I would try to draw attention to were I taking Matt’s side of this argument.

None of this is to say that we would all be immensely wealthy in a world without government intervention. The way Matt structures his argument, I don’t have to make that claim. All I need to show is that but for government intervention, we would not be dramatically worse off than we are now, which I think I have done. It seems worth mentioning, in addition, that government sometimes makes us worse off as well as better off. For example, government regulation of pollutants can and often does exceed anything resembling the welfare-maximizing amount. Governments produce public bads as well as goods, such as war, genocide, the new Jim Crow (to say nothing of the original), and immigration restrictions. Transport policy is often counterproductive, and infrastructure resources such as spectrum and airspace are often misallocated or otherwise mismanaged, relative to a common law approach. Financial regulation seems to do more to enrich Wall Street than protect the public. And as I said above, government policy caused the Great Depression and the Euro crisis, as well as innumerable other financial disasters. These costs are significant. Immigration restrictions alone cut global output in half. On top of all this is the deadweight loss of taxation, which is substantial.

What is most unfortunate about Matt’s list is how widely accepted it is. He says you can find it in “a really banal mainstream neoclassical economics textbook,” and he is right. Textbook economics presents a simple model of the world and draws conclusions from that model that are frequently at odds with reality. Most textbooks try to convince the reader of the benefits of economic analysis, not to educate the reader about the limits of the models they present. Real world institutional analysis is much more complicated, messy, and context-dependent than Matt’s textbook allows. We can and should use the tools in the textbook to illuminate our work, but applying them as Matt does to create a universal theory of the (non)existence of a market distribution of wealth seems misguided.

But now it’s time to look beyond the WCIT. The WCIT revealed substantial international disagreement over the future direction of Internet governance, particularly on the issues of whether the ITU is an appropriate forum to resolve Internet issues and whether Internet companies such as Google and Twitter should be subject to the provisions of ITU treaties. This disagreement led to a split in which 55 countries opted not to sign the revised ITRs, the treaty under negotiation.

Where does this divisive ITR revision leave us? It means that the next two years or so of ITU meetings have the potential to be extremely interesting. In particular, the World Telecommunication/Information and Communication Technology Policy Forum (WTPF) in May 2013 in Geneva and the ITU Plenipotentiary Conference (known as “Plenipot”) in October-November 2014 in Busan, South Korea, are worth watching closely.

Unlike the WCIT, the WTPF is not a treaty conference. It is a meeting that produces opinions and reports. Also unlike the WCIT, at WTPF the Internet is explicitly on the table in an up-front, honest way. The opinions and reports produced at WTPF about the Internet will be used as input documents into Plenipot, which is a full treaty conference. At Plenipot, the entire Constitution and Convention of the ITU is subject to revision, so it is extremely likely that the Internet will be considered. One contact of mine has called Plenipot “WCIT 2.”

There is some good news. So far, all WTPF preparatory documents have been 100% open to the public. WCITLeaks applauds the ITU for this policy. Transparency provided directly by the ITU is better than the transparency we have provided in the past, because the ITU’s public documents are often available in multiple languages, something that WCITLeaks does not have the resources to offer. For example, here is the fourth draft of the SG’s report from the Informal Experts Group for WTPF. Note that it is available in English, Arabic, Chinese, Spanish, French, and Russian. The multilingual availability of this document ensures that an even broader array of global civil society will be able to more closely follow WTPF preparations.

The bad news is that we do not yet know if WTPF documents beyond the preparatory phase will be publicly available. When those documents appear, they will be listed here, but it is possible that users who are not affiliated with Member States or Sector Members won’t have access. In addition, we do not yet know what the policy will be toward access to documents relating to Plenipot.

We hope that the ITU will continue to take these important steps toward greater transparency. At the same time, we are ready to reprise our WCIT role if necessary. To that end, we have reoriented the WCITLeaks site to focus on WTPF and future conferences. WCIT-related documents will continue to be available at wcitleaks.org/wcit. As always, you can stay up to date by following @WCITLeaks on Twitter. Happy leaking!

The authors are basically regressing log output per worker on 10-year-lagged measures of patenting in a fixed effects model using metropolitan areas in the United States.

The model is structured in this relatively standard way to reduce endogeneity—there might be more patents filed where labor productivity is highest, rather than higher labor productivity where the most patents are filed. And if the only concern were reverse causality, then it would be a good way to study the question of patents and innovation.

The authors find positive coefficients on the patenting variables and conclude that patents drive economic growth both in local areas and in general.

This report documents how a strong national innovation system plays out across a dispersed array of U.S. metropolitan areas, contributing to economic growth in both local places and across a large and diverse country.

Clear in these pages is the continued vibrancy of the U.S. innovation as well as the general utility of the nation’s patenting system. (p. 28, emphasis added)

These conclusions are unwarranted given the model and findings expressed in the paper. To see that this is the case, assume temporarily that patents do nothing to incentivize real innovation, and that they merely transfer wealth from consumers at large to the patent holder through firm profits. If this were the case, then we would find that measured output per worker was higher in metropolitan areas with more patents—exactly what the authors found!—because they are gaining profits at the expense of consumers in metropolitan areas with fewer patents. In other words, the authors could be laboring under a fallacy of composition. Just because patents enrich the MSAs that generate them doesn’t mean that they are a source of prosperity for the nation as a whole or that they increase social welfare.

Alternatively, assume temporarily that patents do nothing to incentivize real innovation, but that firms that produce valuable innovations must defensively patent them to avoid being taken to court for using their own inventions. If this were the case, then patents would correlate with real innovation, and therefore with output per worker, but they would not cause an increase in productivity. In addition, at least some of the measured increase in output would come from an influx of highly-paid intellectual property attorneys, which by assumption does not represent real added productivity. Note that the top-patenting MSA in the study is Silicon Valley, the part of the country where people are most concerned about defensive patenting. But the word “defensive” does not appear even one time in the report, the appendix, or the working paper.

The authors have done nothing to identify the effect of patents on productivity, which is to say, nothing to rule out either of the possible assumptions above. They are simply relying on the assumption that more patents means more innovation.

This flaw in the paper makes all of their policy conclusions suspect. For example, if patents represent a mere transfer, then encouraging patent-generating institutions is socially destructive. It might nevertheless be rational for a single MSA to encourage such institutions, because residents of the MSA would enrich themselves at the expense of other MSAs. In this case, we should adopt federal policies to discourage patent-generating institutions. If patents merely correlate with innovation due to defensive patenting in some domains, then the U.S. patent system is not working as intended, which is again the opposite of what the authors conclude.

On point, the Winter 2013 Journal of Economic Perspectives is out this week, featuring a four-paper symposium on patents. The lead article is by Boldrin and Levine, entitled “The Case Against Patents.” Here is the first paragraph:

The case against patents can be summarized briefly: there is no empirical evidence that they serve to increase innovation and productivity, unless productivity is identified with the number of patents awarded—which, as evidence shows, has no correlation with measured productivity. This disconnect is at the root of what is called the “patent puzzle”: in spite of the enormous increase in the number of patents and in the strength of their legal protection, the US economy has seen neither a dramatic acceleration in the rate of technological progress nor a major increase in the levels of research and development expenditure.

Petra Moser’s article does a historical comparison of countries with strong and weak patent laws and concludes:

Overall, the weight of the existing historical evidence suggests that patent policies, which grant strong intellectual property rights to early generations of inventors, may discourage innovation. On the contrary, policies that encourage the diffusion of ideas and modify patent laws to facilitate entry and encourage competition may be an effective mechanism to encourage innovation. (emphasis in original)

I hope that policymakers don’t rely on Brookings’s strong reputation and infer that our patent system is the strong engine of economic growth that Rothwell et al. suggest it is.

I expect that the book will create some controversy in policy circles. In this post, I want to address what is likely to be a knee-jerk response from our critics, that copyright reform will substantially decrease the incentive to produce creative works.

Content creators anticipate that their products will generate some amount of revenue each year after they are released. The expectation is generally that the creative work will generate the highest revenue in the first year, and less revenue in each subsequent year. To model this revenue stream, I’m going to assume exponential decay. Exponential decay lets us pick a half-life, , and assume that  years after the work was released, it will generate revenue at half the initial rate. After years, it will generate revenue at one-fourth the rate, and so on.

In year , the revenue that the content creator will receive if there is copyright is times the initial revenue. Consequently, the total revenue that a copyright holder will receive over the life of a 95-year copyright term is

times the initial revenue.

However, content creators prefer revenue now to revenue 90 years from now. In order to calculate the present value of this revenue stream, we need to apply a discount rate . The ex ante value of the revenue stream generated by the 95-year copyright term is therefore

times the initial revenue.

And of course, this calculation generalizes to different copyright terms. If we returned to a 28-year term, as Tom Bell advocates in his chapter of our book, the ex ante revenue stream would be valued at

times the initial revenue.

We’re now at a point where we can start to run some numerical calculations based on plausible values for and . What is a reasonable ex ante expectation about the half-life of the revenue stream of a new creative work? I expect that for our book, the half-life will be something like 1 year or less; we will probably sell less than half as many books in the second year the book is out as in the first. But let’s not use . Let’s estimate that to be extremely conservative and generous to our critics.

What about ? Again, how about if we are conservative and give a low value, like ?

Now we can run some calculations. Using the values above, the ex ante present value of a 95-year copyright is around 11.726 times the initial revenue. The ex ante present value of a 28-year copyright is around 10.761 times the initial revenue. Consequently, shortening the copyright term from 95 years to 28 years (less than 30% of the current term!) retains about 91.8 percent of the incentive effect of the current copyright term.

It is unlikely that such a small decrease in the present-value of the revenue stream would reduce the amount of content production by much. To the extent that content producers cannot or do not substitute easily into other fields, they would simply take the 8.2 percent decline in compensation per project as a decrease in wages (not the end of the world), and there would be no decline in content production. To the extent that content producers can substitute into other fields, we would get less content, but we would also get more of other stuff—the welfare effects of less content are ambiguous, since there is a knowledge problem regarding the optimal amount of content.

If you want to do the calculation with different half-lives and interest rates, be my guest. I am confident that for all plausible values of and , you will find that shortening the copyright term will have at most a modest effect on the incentive to create.

How about the value of the public domain? This is a little harder to model, because we care about the ex post value of works, not just the ex ante expectation that content creators have. In practice, there turn out to be works with much longer half-lives than others. This fact complicates any back-of-the-envelope calculation. We also don’t know exactly by how much content creation would fall.

But let’s abstract from this and model the value of the public domain as the revenue stream for a given project that otherwise would have gone to copyright holders above. One difference for the public domain is that it no longer makes sense to discount the stream of value—future generations aren’t sitting around, waiting to be born so that they can watch Star Wars for the first time. Therefore, normalized to our original, first-year revenue stream, an estimate of the value of the public domain under a 95-year term is

.

Under a 28-year term, the value is

.

Plugging in the value we selected earlier for , 10, the former expression yields around 0.021 and the latter about 2.144. In other words, the value of the public domain would be around 100 times higher per creative work if we shortened the term to 28 years. Again, this value is highly dependent on our selection of , but the reason I am doing these calculations is so that my critics can repeat them with values they find more plausible, if they so choose.

This analysis has been highly stylized, but it is also extremely conservative. The half-life of most creative works is probably much shorter than 10 years, and when valuing an uncertain revenue stream, most artists—and even content corporations—probably discount at a rate of higher than 2 percent. The value of the public domain has been understated in this analysis, because there are many works that turn out ex post to have longer half-lives (but it is still the ex ante estimate of value that matters for investment). I have also not factored in the gains from those derivative works that are impossible under the current regime due to transaction costs, or the savings in enforcement costs from having a shorter time during which enforcement is necessary, or indeed, many of the other issues discussed in our book.

I would be interested in reading further analyses like the one above from anyone who supports the current copyright term or a longer one. How do you justify such a long term? You don’t have to use my assumptions, just make your own explicit so that people can see what they are and quarrel with them. How many fewer works do you really think would be created if we shortened the term from 95 years to 28 years? Would we really be worse off? Please show your work.

Why not? The answer is surely not because McDonald’s is the best at sourcing meat. It seems likely that from time to time, local operators would be able to find higher quality meat at lower prices than the company. And the answer is not that the sourcing of meat provides a profit to the company at the expense of the restaurants. Such a transfer would be capitalized via the other terms of the franchise agreement, so there is no incentive to adopt these terms unless they are efficient.

The real answer is that there is a brand externality. Let’s suppose that one local McDonald’s tries to increase its profit by purchasing extremely low-grade beef. If you stop at this McDonald’s on a road trip and get sick, you might punish all McDonald’s restaurants by refusing to eat at them in the future.

This problem does not plague standalone restaurants. We don’t worry about them locally sourcing their meat—and often, we prefer it. But this is because they have only their own reputation to harm. If they shirk on quality, they bear all of the reputational costs themselves.

The brand externality would also not be a problem if everyone only ever ate at their local McDonald’s. If your local McDonald’s used rotten beef, you wouldn’t go there, and neither would anyone else. Other McDonald’s restaurants would be unaffected. But the fact is, people travel and indeed, that is often when they go to McDonald’s, so the brand externality is an important issue, and the company deals with it by standardizing quality across all McDonald’s restaurants by contract. This contractual arrangement between the central company and the individual restaurants is called a “vertical restraint.”

When I think about why the Republicans lost ground in the 2012 election, I think about beef that is well past its sell-by date. Individual Republican politicians have an incentive to cater to the values of their local electorates, but this can come at the expense of the national Republican brand. Tip O’Neill famously said that all politics is local, but this is no longer true—the advent of cable news and the Internet means that some politics is national, as does the fact that more policy is now decided at the federal level. It’s like we have gone from a situation in which everyone eats only at their local McDonald’s to one where people travel and eat at restaurants around the country: a brand externality has emerged.

Given that national media is not going away, party leaders need to be able to impose vertical restraints on its candidates. They need to be able to ensure that local races boost the national Republican brand, even at the expense of losing local races from time to time. Local politicians may be able to get a local boost in turnout by playing to the prejudices of their bases, but if such activity harms the party on a national level, that is inefficient, and the central party needs to find a way to stop it if it wishes to succeed.

The admittedly oversimplified median voter theorem says that both parties should converge on the preferences of the median voter. To the extent that one party suffers more from brand externalities, the other party will be able to take advantage by converging more rapidly to that position, or by making more effective use of the slack generated by the ineffective party. Democrats are arguably more nationally-minded, and this means that in the age of political brand externalities, they have an advantage. If Republicans want to be an effective party in the 21st century, they need to find a way to impose vertical restraints on those who would abuse their brand.

I haven’t written much publicly about the WCIT lately because I am now officially a participant—I have joined the US delegation to the conference. My role is to help prepare the US government for the conference, and to travel to Dubai to advise the government on the issues that arise during negotiations.

To help the general public better understand what we can expect to happen at WCIT, Mercatus has organized an event next week that should be informative. Ambassador Terry Kramer, the head of the US delegation, will give a keynote address and take questions from the audience. This will be followed by what should be a lively panel discussion between me, Paul Brigner from the Internet Society, Milton Mueller from Syracuse University, and Gary Fowlie from the ITU, the UN agency organizing the conference. The event will be on Wednesday, November 14, at 2 pm at the W hotel in Washington.

If you’re in the DC area and are interested in getting a preview of the WCIT, I hope to see you at the event on Wednesday. Be sure to register now since we are expecting a large turnout.

Amazon, you can solve this problem. Here’s how.

You already have a strong partnership with UPS, which you use for shipping. Make another deal with them. There are UPS Stores all around the country. If I bring a dead-tree book to any UPS Store, they should recycle the book for me and give me a credit for the Kindle version of that same book. The cost of handling or recycling the book can be split between me and Amazon.

This is a win-win-win-win proposition.

I win because I have fewer physical books cluttering up my house, while retaining access to my library.

Amazon wins because more consumers will have large Kindle libraries. This will create an incentive to make future purchases in the Kindle ecosystem.

Book publishers win because when used books are recycled, the market for used books shrinks. Physical books are durable and resalable; converting to Kindle books solves the durable goods problem and makes publisher profits higher because they would sell more copies.

UPS wins because they get a small fee-per-book that comes out of the gains to the other parties.

When I talk about this idea, I find that the main objection I get is an emotional one: “Isn’t it wasteful to destroy used books?” people ask. And the answer is not really. No information is destroyed by recycling the book, because Kindle books are a pretty good substitute. And if the book were not destroyed, then the publishers would never go for the deal, and we would be stuck in a more wasteful situation, one in which a significant fraction of real estate goes toward book storage.

Amazon, you started the ebook revolution. Now take it to the next level by helping everyone complete the transition.

The tech world is filled with lots of smart people who understand math, so for this post, I am going to try to make the case with algebra and a wee bit of calculus. If you can follow along, great; if not, I’ll get you in some other post.

Let’s start with a basic, normalized linear demand function:

is quantity and is price. The results of this exercise will translate easily to any linear demand function, and they will apply broadly to all demand functions, so why not make it easy on ourselves?

Let’s assume that firms have a fixed cost and a marginal cost . Firms’ total costs are:

Total revenue for the firm is just price times quantity, so it is equal to . If we are concerned that not even one firm might serve this market, then it is useful to look at the monopoly case, where market and are equal to firm and . In this context, we can substitute for , and therefore, total revenue is equal to .

Total profit is simply total revenue minus total costs. Therefore:

What prices and quantities maximize profit? To calculate this, we can take a partial derivative of profit with respect to and set it to zero. This condition will hold where profit is maximized.

Solving for ,

Plugging this expression for into the demand function lets us solve for :

This is the profit-maximizing and for a monopolist in this market in terms of . Note that drops out. The profit-maximizing values don’t depend on .

What does depend on , however, is whether the firm is earning enough at these values of and to stay in business. In particular, profit needs to be zero or positive for the firm not to shut down.

Substituting for :

Gathering terms:

Simplifying:

So without price discrimination, this market will be served if and only if . If we want to plug in some numbers, assume that ; in this case the market will be served only if .

Want to try it with price discrimination now?

With marginal cost equal to , a monopolist would produce units. Assuming that the monopolist is able to charge each consumer the maximum they are willing to pay, then profit can be expressed like this:

Computing the integral:

This is equal to:

Since profits must be non-negative for the firm to stay in business:

or

So this market, with perfect price discrimination, will be served if . This means that the fixed cost can be twice as high (with linear demand) and the product or service will still be provided. If we want to plug in , then the market will be served as long as .

Why does this matter in the tech world? Because a lot of tech products and services have very high fixed costs. Building out wired and wireless broadband networks, for instance, is extremely costly. Marginal costs are often relatively low.

If we want to reap the benefits of new and innovative tech products, we must be prepared to accept price discrimination at least some of the time. There are products that are viable with price discrimination that are not viable without it—and if we ban price discrimination like some people thoughtlessly advocate, we won’t get them.

The question is worth considering, but in the details of his analysis, there is much that Gordon gets wrong. For example, Gordon looks at growth in the “frontier” economy, the economy that is most advanced in each period. This means the UK from 1300 to 1906 and the US from 1906 to 2007 (where he stops his story to abstract from the financial crisis). When looking at a single wealthy economy, global factor-price equalization that results in lower middle-class wages seems like a bad thing. But of course, these lower wages are the result of higher wages elsewhere—they are wages for poor people who can increasingly contribute to the frontier of innovation as they get wealthier. Limiting the analysis to a frontier national economy seems inappropriate when one of the major global trends is a reduction in the discreteness of national economies.

I have a lot of other complaints—for instance, I wanted to refer Gordon to Noah Smith on global warming—but for the rest of this post, I am going to focus only on one particular issue. Gordon divides our progress over the past 250 years into not one, but three Industrial Revolutions. IR #1 was from 1750 to 1830 and gave us steam power and railroads. IR #2 ran from 1870 to 1900 and yielded electricity, internal combustion, running water, indoor toilets, communications, entertainment, chemicals, and petroleum. IR #3 started in 1960 and gave us computers, the Internet, and mobile phones.

Gordon takes the view—entirely defensible—that IR #2 is the one that is the most important, and that it took about 100 years for its “full effects to percolate through the economy.” But both in his definition and discussion, he gives short shrift to IR #3.

The computer and Internet revolution (IR #3) began around 1960 and reached its climax in the dot.com era of the late 1990s, but its main impact on productivity has withered away in the past eight years. Many of the inventions that replaced tedious and repetitive clerical labor by computers happened a long time ago, in the 1970s and 1980s. Invention since 2000 has centered on entertainment and communication devices that are smaller, smarter, and more capable, but do not fundamentally change labor productivity or the standard of living in the way that electric light, motor cars, or indoor plumbing changed it.

Later in the paper, he writes,

Attention in the past decade has focused not on labor-saving innovation, but rather on a succession of entertainment and communication devices that do the same things as we could do before, but now in smaller and more convenient packages. The iPod replaced the CD Walkman; the smartphone replaced the garden-variety “dumb” cellphone with functions that in part replaced desktop and laptop computers; and the iPad provided further competition with traditional personal computers. These innovations were enthusiastically adopted, but they provided new opportunities for consumption on the job and in leisure hours rather than a continuation of the historical tradition of replacing human labor with machines.

I can see how if you’re comparing the advancements of the past few decades to the benefits of indoor plumbing you might come away a little disappointed, and I’m not trying to play IRs 2 and 3 against each other. But I think that Gordon unfairly or unwittingly understates the magnitude of IR #3, because IR #3 has only just begun.

What is IR #3 and where is it going?

Again, Gordon defines IR #3 as the arrival of computers, the Internet, mobile phones, etc. But rather than focusing on the products, let’s focus on the processes and innovations that got us here—computation, miniaturization, packet switching, and so on. These ideas feature prominently in the products that Gordon uses to define IR #3, but they also have much wider conceivable applicability than just those products.

I think we are on the cusp of an important transition within IR #3. So far, we have used these innovations to make ever faster, smaller, and more useful computers, including mobile phones. We have created, as Gordon notes, a whole lot of dot-coms and online services. But we’re already starting to see engineers and companies dabble with new kinds of products. Rather than merely accepting, transforming, relaying, and displaying information, some new computer-based products have more of a physical—really, a kinetic—effect on the world.

The most obvious example of this new kind of kinetic computing is the autonomous car. Rather than simply gathering information and displaying it to the driver, like a GPS mapping system, we are empowering an onboard computer to make decisions about driving. These decisions have consequences, and it is difficult to program a computer to get them right—much harder than, say, inventing Facebook. But despite the difficulty of the problem, we have made a lot of progress in the last decade, and most of us can look forward to one day owning a robotic car or ordering a robotic taxi to come pick us up.

The point is that computing innovation is going to shift, and is already starting to shift, from the virtual to the physical world. The products that IR #3 has brought us so far are great fun, but because they only really display information to us, they leave a lot for us to do. The main benefit of iR #3 is going to arrive when new innovations make and do things for us.

Ambient computing

Golden Krishna wrote an excellent blog post recently entitled “The best interface is no interface.” Read the whole thing. The point of the post is that we have not yet done a good job of replacing early computer interface paradigms like WIMP—window, icon, menu, pointer—with natural, unobtrusive, adaptive paradigms. Instead we slap a display on everything and call it progress.

Krishna provides some great examples of the alternative vision, what he calls “No UI,” which include the Auto Tab feature of Pay with Square and Nest. What these products and services have in common is that users empower them to make decisions without direct supervision. They require a little human interaction to set up, but from then on, unless something goes wrong, there is no need to do anything to use the product. The product adapts to you, it gets out of the way, and it feels natural.

We are only just now getting to the point where products like these are becoming possible. So far in IR #3, we have mainly trusted computers with information, not with decisions about the physical world. But as computing improves, we are going to automate more.

In What Technology Wants, Kevin Kelly writes about the “home motors” you could buy a century ago. The idea was that buy a single motor for interchangeable use in a sewing machine, a mixer, a fan, or an egg beater.

One hundred years later, the electric motor has seeped into ubiquity and invisibility. There is no longer one home motor in a household; there are dozens of them, and each is nearly invisible. No longer stand-alone devices, motors are now integral parts of many appliances. They actuate our gadgets, acting as the muscles for our artificial selves. They are everywhere. I made an informal census of all the embedded motors I could find in the room I am sitting in while I write:

[...]

That’s 20 home motors in one room of my home. A modern factory or office building has thousands. We don’t think about motors. We are unconscious of them, even though we depend on their work. They rarely fail, but they have changed our lives. We aren’t aware of roads and electricity either because they are ubiquitous and usually work. We don’t think of paper and cotton clothing as technology because their reliable presences are everywhere.

Once computer chips become as ubiquitous and invisible as motors, and we get competent enough at using them to empower them to make decisions for us without direct supervision, the result will be something like ambient intelligence. It’s hard to predict what people will use AmI for, but it certainly feels to me like a much bigger advance than Angry Birds and Facebook. We’re probably a decade or two away from high-quality ambient intelligence, but given its reliance on the innovations generated on IR #3, AmI should be counted as an IR #3 innovation when it arrives.

Transport efficiency

The audacious idea that economic growth was a one-time-only event has no better illustration than transport speed. Until 1830 the speed of passenger and freight traffic was limited by that of “the hoof and the sail” and increased steadily until the introduction of the Boeing 707 in 1958. Since then there has been no change in speed at all and in fact airplanes fly slower now than in 1958 because of the need to conserve fuel.

Gordon is right that travel speeds have not increased much in recent decades. If you had told me in that 1980s that by 2012 I would still never have traveled faster than sound (relative to the Earth), I would have been very disappointed. And while some interesting technologies are in the pipeline—scramjets, spaceplanes, and so on—it will be a while before these are commercialized.

But in the meantime, the efficiency of transporting people and goods could explode in the near future. Gordon is well aware of autonomous cars, so I won’t belabor the point, but it seems obvious to me that a morning commute during which I am able to productively get started on my day is almost like no commute at all. An evening commute during which I am able to relax and unwind is almost like no commute at all. If we calculate effective speed by dividing travel distance by wasted time, then technologies like autonomous vehicles and to a lesser extent in-flight Wi-Fi are starting to make up for some of the stagnation in proper transport speed.

I have already written about how revolutionary commercial drones are likely to be. Local deliveries will be made robotic quadrocopters instead of by humans, and FedEx will switch to blended-wing unmanned cargo freighters that will reduce the cost of long-range goods transport by a factor of five, making air transport competitive with (only about twice as expensive as) ocean transport. A key point about the quadrocopter revolution is that it needed the iPhone market to get started:

As Dan Shapiro notes, “A single high-quality gyro used to go for a thousand bucks.  Now, you can get 3 gyros, 3 accelerometers, and a nice CPU to manage the whole thing for under a sawbuck.”

Commercial drones face some regulatory hurdles, but assuming these can be overcome, they will be an important contribution of IR #3.

Matter compilers

Traditional printers have a kinetic effect on the world—they put ink to paper—but not really. We value them for the informational quality of the printed product, not for the physical structure of the object that comes out of the printer. 3D printing is not that different from traditional printing, but its impact is likely to be much larger. It is another element of IR #3 that is still in development.

When I got a chance to see a 3D printer in person earlier this year, I was underwhelmed. There is still very little that consumer 3D printers can produce that I would actually want. But future generations of printers will almost certainly be much more useful as they become able to print in a wider array of materials.

In particular, I am excited to see chemical printers. People will be able to make their own drugs—both medical and recreational. This may sound dangerous, and perhaps it will be. But with the adoption of quantum computing we will be able to simulate chemical reactions in advance, something that we still cannot do efficiently with classical computers. Such simulation will greatly improve the feasibility of moving quickly to human trials on new drugs, including self-experimentation. The combination of quantum simulation and chemical printing could lead to a golden age of pharmaceutical discovery.

Synthetic biology

Relatedly, synthetic biology is another area where we seem to be observing rapid progress. I am woefully ignorant about synthetic biology—I am ashamed of this and will remedy it soon—so I should probably not be making very strong claims. But it seems important to mention that few if any of the advances in this field would have been possible without computers or prior research that has made heavy use of computers. Consequently, these advances are attributable to IR #3.

Online education

Total educational spending in the United States is something like 7 percent of GDP (5.5% of GDP is public expenditure, I believe around 1.5% or so is private expenditure). And the quality of education for anybody but the best or richest students is not especially good—the US routinely posts middling scores in international comparisons for primary and secondary education. Even at the college level, where the US excels, a lot of students are being underserved, often because they need remedial help.

We are still using a medieval technology, the lecture, to educate our students. But increasingly entrepreneurs—both for- and non-profit—are looking for better ways of teaching. Many of the new crop of online educational institutions, such as Khan Academy, Udacity, and Marginal Revolution University, are completely free.

People are still experimenting with educational models (and business models), but education that leverages new technologies has several advantages over the old classroom model. For example, in what is known as “flipping the classroom,” students can watch lectures for homework, and do problem sets in class, where they can get help from teachers. The quality of teaching can be higher because everybody can be taught by the very best teachers. And separating the teaching component of school from the coaching and supervision component of school means lower costs and greater specialization, including jobs for people who are not good at teaching but who are nevertheless good at working with kids. At least until the robots can do that too.

Gordon argues that we got a one-time economic boost from educating more people, but now educational achievement has plateaued and we can no longer rely on more education as a source of economic growth. But this seems like a narrow perspective to me. The quality of education certainly has a lot of room for improvement, as does the cost. If we let computers help us teach, we can improve on both of these margins.

While it remains to be seen what the ultimately successful models of online education will be, it would be surprising to me if there is not a major change in the educational industry in the next couple decades. And when that change comes, I bet it will be due to IR #3.

A new phase of IR #3

I’ve tried to review a number of emerging technologies that are likely to transform our daily lives, how we transport people and goods, how we make stuff, our health, and our educational system. Obviously this is an incomplete list; see Wikipedia for more.

There is still a lot of oomph in IR #3. All of the technologies that I have described are in development, and all of them owe their existence to digital computing. Some of them may founder, and some different technologies may turn out to be more important. But it is a big mistake to think that the world of computing can remain separate from the rest of the world for long. Computing started out set apart because it is safer that way—if your browser crashed or your web server goes down, there are not very large external consequences.

Experience and practice in the safe virtual world are leading to a greater desire and capability to extend these technologies to the physical world. It has taken 50 years, but we are now on the cusp of these changes. The remaining question is whether we will welcome them or try to smother them with regulations and arguments over the transitional gains. The best way out of the Great Stagnation is to eagerly embrace and support the new technologies. But they may be coming whether we want them or not, and that is why I am a long-run growth optimist.