Tag Archives: Innovation

Light On Dark Matter

I posted recently on the question of what makes up the “dark matter” intangible assets that today are most of firm assets. Someone pointed me to a 2009 paper of answers:

IntangibleShares

[C.I. = ] Computerized information is largely composed of the NIPA series for business investment in computer software. …

[Scientific R&D] is designed to capture innovative activity built on a scientific base of knowledge. … Non-scientific R&D includes the revenues of the non-scientific commercial R&D industry … the costs of developing new motion picture films and other forms of entertainment, investments in new designs, and a crude estimate of the spending for new product development by financial services and insurance firms. …

[Brand equity] includes spending on strategic planning, spending on redesigning or reconfiguring existing products in existing markets, investments to retain or gain market share, and investments in brand names. Expenditures for advertising are a large part of the investments in brand equity, but … we estimated that only about 60 percent of total advertising expenditures were for ads that had long-lasting effects. …

Investment in firm-specific human and structural resources … includes the costs of employer-provided worker training and an estimate of management time devoted to enhancing the productivity of the firm. … business investments in firm-specific human and structural resources through strategic planning, adaptation, reorganization, and employee-skill building. (more)

According to this paper, more firm-specific resources is the biggest story, but more product development is also important. More software is third in importance.

Added 15Apr: On reflection, this seems to suggest that the main story is our vast increase in product variety. That explains the huge increase in investments in product development and firm-specific resources, relative to more generic development and resources.

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Firms Now 5/6 Dark Matter!

Scott Sumner:

We all know that the capital-intensive businesses of yesteryear like GM and US steel are an increasingly small share of the US economy. But until I saw this post by Justin Fox I had no idea how dramatic the transformation had been since 1975:

intangibles

Wow. I had no idea as well. As someone who teaches graduate industrial organization, I can tell you this is HUGE. And I’ve been pondering it for the week since Scott posted the above.

Let me restate the key fact. The S&P 500 are five hundred big public firms listed on US exchanges. Imagine that you wanted to create a new firm to compete with one of these big established firms. So you wanted to duplicate that firm’s products, employees, buildings, machines, land, trucks, etc. You’d hire away some key employees and copy their business process, at least as much as you could see and were legally allowed to copy.

Forty years ago the cost to copy such a firm was about 5/6 of the total stock price of that firm. So 1/6 of that stock price represented the value of things you couldn’t easily copy, like patents, customer goodwill, employee goodwill, regulator favoritism, and hard to see features of company methods and culture. Today it costs only 1/6 of the stock price to copy all a firm’s visible items and features that you can legally copy. So today the other 5/6 of the stock price represents the value of all those things you can’t copy.

So in forty years we’ve gone from a world where it was easy to see most of what made the biggest public firms valuable, to a world where most of that value is invisible. From 1/6 dark matter to 5/6 dark matter. What can possibly have changed so much in less than four decades? Some possibilities:

Error – Anytime you focus on the most surprising number you’ve seen in a long time, you gotta wonder if you’ve selected for an error. Maybe they’ve really screwed up this calculation.

Selection – Maybe big firms used to own factories, trucks etc., but now they hire smaller and foreign firms that own those things. So if we looked at all the firms we’d see a much smaller change in intangibles. One check: over half of Wilshire 5000 firm value is also intangible.

Methods – Maybe firms previously used simple generic methods that were easy for outsiders to copy, but today firms are full of specialized methods and culture that outsiders can’t copy because insiders don’t even see or understand them very well. Maybe, but forty years ago firm methods sure seemed plenty varied and complex.

Innovation – Maybe firms are today far more innovative, with products and services that embody more special local insights, and that change faster, preventing others from profiting by copying. But this should increase growth rates, which we don’t see. And product cycles don’t seem to be faster. Total US R&D spending hasn’t changed much as a GDP fraction, though private spending is up by less than a factor of two, and public spending is down.

Patents – Maybe innovation isn’t up, but patent law now favors patent holders more, helping incumbents to better keep out competitors. Patents granted per year in US have risen from 77K in 1975 to 326K in 2014. But Patent law isn’t obviously so much more favorable. Some even say it has weakened a lot in the last fifteen years.

Regulation – Maybe regulation favoring incumbents is far stronger today. But 1975 wasn’t exact a low regulation nirvana. Could regulation really have changed so much?

Employees – Maybe employees used to jump easily from firm to firm, but are now stuck at firms because of health benefits, etc. So firms gain from being able to pay stuck employees due to less competition for them. But in fact average and median employee tenure is down since 1975.

Advertising – Maybe more ads have created more customer loyalty. But ad spending hasn’t changed much as fraction of GDP. Could ads really be that much more effective? And if they were, wouldn’t firms be spending more on them?

Brands – Maybe when we are richer we care more about the identity that products project, and so are willing to pay more for brands with favorable images. And maybe it takes a long time to make a new favorable brand image. But does it really take that long? And brand loyalty seems to actually be down.

Monopoly – Maybe product variety has increased so much that firm products are worse substitutes, giving firms more market power. But I’m not aware that any standard measures of market concentration (such as HHI) have increased a lot over this period.

Alas, I don’t see a clear answer here. The effect that we are trying to explain is so big that we’ll need a huge cause to drive it. Yes it might have several causes, but each will then have to be big. So something really big is going on. And whatever it is, it is big enough to drive many other trends that people have been puzzling over.

Added 5p: This graph gives the figure for every year from ’73 to ’07.

Added 8p: This post shows debt/equity of S&P500 firms increasing from ~28% to ~42% from ’75 to ’15 . This can explain only a small part of the increase in intangible assets. Adding debt to tangibles in the numerator and denominator gives intangibles going from 13% in ’75 to 59% in ’15.

Added 8a 6Apr: Tyler Cowen emphasizes that accountants underestimate the market value of ordinary capital like equipment, but he neither gives (nor points to) an estimate of the typical size of that effect.

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Why Not Sell Cities?

Economists don’t like seeing economic inefficiency, and there’s a lot of it out there to bother us. But some of the very worst we see is in cities; there are many incredible inefficiencies in city land use and in supporting utilities. Which of course makes economists wonder: how could we do better?

Here is one idea that should seem obvious to most economists, but even so I can’t find much discussion of it. So let me try to think it through. What if we auctioned off cities, whole?

Specifically, imagine that we sell all the land and immobile property in an urban region, including all the municipal property, plus all the rights to make urban governance choices. We sell this to a single buyer, who might of course be a consortium. The winning bid would have to be higher than the prior sum of all regional property values, plus a gain of say 50%. The money would be paid to all the prior property owners in proportion to prior property values. (“Prior” should be well before the auction was announced.)

The winning buyer would control all property and governance in this region for a specific time period, say twenty years, after which they’d have to divide the region into at least a thousand property units and auction all them off again individually. Urban governance would revert back to its previous system, except that there’d be a single up-or-down vote on one proposal for a new governance regime offered by this buyer, using previous rules about who can vote in such things.

The idea here is of course to “internalize the externalities”, at least for a while. This single buyer would encompass most of the varying conflicting interests that usually cause existing inefficiencies. And they’d have the power to resolve these conflicts decisively.

OK, now let’s ask: what could go wrong? Well first maybe no bidder could actually collect enough money to make a big enough bid. Or maybe the city inefficiencies aren’t big enough to produce the 50% added value requirement. Or twenty years isn’t long enough to fix the deep problems. Or maybe the plan leaks out too early and pushes up “prior” property values. In these cases, there’d be no change, so not much would be lost.

Another thing that could go wrong would be that larger units of government, like states or nations, might try to tax or regulate this single buyer so much as to take away most of their gains from this process. In expectation of this outcome, no one would bid enough for the city. And again there’d be no change, so little would be lost. So we should try to set this up to avoid such taxation/regulation, but knowing that the downside isn’t terrible if we fail.

Finally, the new city owner might price-discriminate against residents who are especially attached to the city, and so are especially unwilling to leave. Like an old couple whose children all live nearby. Or a big firm with an expensive plant located there. If the new owner cranks up their rent high, these folks might lose on net, even if they are paid a 50% bonus on property values. Of course one might try to set rules to limit price-discrimination, though that might create the over-regulate scenario above. Also, if selling off cities whole became a regular thing, then people may learn to not get too attached to any one city.

I don’t see any of these problems as overwhelming, so I’d endorse trying to do this. But I don’t actually expect many places to try it, because I think most voters whose support would be needed would see their status as threatened. They’d be offended by the very idea of a single powerful actor having strong control over their lives, even if that actor had to pay dearly for the right, and even if they end up better off as a result. So I’d guess it is pride that most goeth before our city falls.

As I’ve mentioned before, people tend to love cities even as they hate firms, mainly because firms tend for-profit, while cities tend democratic. People now mostly accept for-profit firms because the non-profit ones don’t offer attractive jobs or products. Similarly, I’d predict that if there were many for-profit cities most people would be okay with them, as they’d be reluctant to move to worse-run non-profit cities. Also, if almost all firms were non-profit, people might be reluctant to rely on for-profit firms due to their bad public image. Multiple equilibria are possible here, and we may not be in the best one.

Added 9p: Many commentaries seem to fear private city owners evicting undesirable people from the city, in contrast to democratically controlled cities which they see as fountains of altruism toward such people. But see here, here, here, or consider that democracies regularly vote to exclude immigrants who would in fact benefit them materially.

Added 9a:

At the state and local level, government is indeed engaged in redistribution — but it’s redistribution from the poor and the middle class to the wealthy. (more)

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Automation vs. Innovation

We don’t yet know how to make computer software that is as flexibly smart as human brains. So when we automate tasks, replacing human workers with computer-guided machines, we usually pay large costs in flexibility and innovation. The new automated processes are harder to change to adapt to new circumstances. Software is harder to change than mental habits, it takes longer to conceive and implement software changes, and such changes require the coordination of larger organizations. The people who write software are further from the task, and so are less likely than human workers to notice opportunities for improvement.

This is a big reason why it will take automation a lot longer to replace human workers than many recent pundits seem to think. And this isn’t just abstract theory. For example, some of the most efficient auto plants are the least automated. Read more about Honda auto plants:

[Honda] is one of the few multinational companies that has succeeded at globalization. Their profit margins are high in the auto industry. Almost everywhere they go — over 5 percent profit margins. In most markets, they consistently are in the top 10 of specific models that sell. They’ve never lost money. They’ve been profitable every year. And they’ve been around since 1949. …

Soichiro Honda, the founder of the company … was one of the world’s greatest engineers. And yet he never graduated college. He believed that hands-on work as an engineer is what it takes to be a great manufacturer. … Continue reading "Automation vs. Innovation" »

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Irreducible Detail

Our best theories vary in generality. Some theories are very general, but most are more context specific. Putting all of our best theories together usually doesn’t let us make exact predictions on most variables of interest. We often express this fact formally in our models via “noise,” which represents other factors that we can’t yet predict.

For each of our theories there was a point in time when we didn’t have it yet. Thus we expect to continue to learn more theories, which will let us make more precise predictions. And so it might seem like we can’t constrain our eventual power of prediction; maybe we will have powerful enough theories to predict everything exactly.

But that doesn’t seem right either. Our best theories in many areas tell us about fundamental limits on our prediction abilities, and thus limits on how powerful future simple general theories could be. For example:

  • Thermodynamics – We can predict some gross features of future physical states, but the entropy of a system sets a very high (negentropy) cost to learn precise info about the state of that system. If thermodynamics is right, there will never be a general theory to let one predict future states more cheaply than this.
  • Finance – Finance theory has identified many relevant parameters to predict the overall distribution of future assets returns. However, finance theory strongly suggests that it is usually very hard to predict details of the specific future returns of specific assets. The ability to do so would be worth such a huge amount that there just can’t be many who often have such an ability. The cost to gain such an ability must usually be more than the gains from trading it.
  • Cryptography – A well devised code looks random to an untrained eye. As there are a great many possible codes, and a great many ways to find weaknesses in them, it doesn’t seem like there could be any general way to break all codes. Instead code breaking is a matter of knowing lots of specific things about codes and ways they might be broken. People use codes when they expect the cost of breaking them to be prohibitive, and such expectations are usually right.
  • Innovation – Economic theory can predict many features of economies, and of how economies change and grow. And innovation contributes greatly to growth. But economists also strongly expect that the details of particular future innovations cannot be predicted except at a prohibitive cost. Since knowing of innovations ahead of time can often be used for great private profit, and would speed up the introduction of those innovations, it seems that no cheap-to-apply simple general theories can exist which predict the details of most innovations well ahead of time.
  • Ecosystems – We understand some ways in which parameters of ecosystems correlate with their environments. Most of these make sense in terms of general theories of natural selection and genetics. However, most ecologists strongly suspect that the vast majority of the details of particular ecosystems and the species that inhabit them are not easily predictable by simple general theories. Evolution says that many details will be well matched to other details, but to predict them you must know much about the other details to which they match.

In thermodynamics, finance, cryptography, innovations, and ecosystems, we have learned that while there are many useful generalities, the universe is also chock full of important irreducible incompressible detail. As this is true at many levels of abstraction, I would add this entry to the above list:

  • Intelligence – General theories tell us what intelligence means, and how it can generalize across tasks and contexts. But most everything we’ve learned about intelligence suggests that the key to smarts is having many not-fully-general tools. Human brains are smart mainly by containing many powerful not-fully-general modules, and using many modules to do each task. These modules would not work well in all possible universes, but they often do in ours. Ordinary software also gets smart by containing many powerful modules. While the architecture that organizes those modules can make some difference, that difference is mostly small compared to having more better modules. In a world of competing software firms, most ways to improve modules or find new ones cost more than the profits they’d induce.

If most value in intelligence comes from the accumulation of many expensive parts, there may well be no powerful general theories to be discovered to revolutionize future AI, and give an overwhelming advantage to the first project to discover them. Which is the main reason that I’m skeptical about AI foom, the scenario where an initially small project quickly grows to take over the world.

Added 7p: Peter McCluskey has thoughtful commentary here.

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I Still Don’t Get Foom

Back in 2008 my ex-co-blogger Eliezer Yudkowsky and I discussed his “AI foom” concept, a discussion that we recently spun off into a book. I’ve heard for a while that Nick Bostrom was working on a book elaborating related ideas, and this week his Superintelligence was finally available to me to read, via Kindle. I’ve read it now, along with a few dozen reviews I’ve found online. Alas, only the two reviews on GoodReads even mention the big problem I have with one of his main premises, the same problem I’ve had with Yudkowsky’s views. Bostrom hardly mentions the issue in his 300 pages (he’s focused on control issues).

All of which makes it look like I’m the one with the problem; everyone else gets it. Even so, I’m gonna try to explain my problem again, in the hope that someone can explain where I’m going wrong. Here goes.

“Intelligence” just means an ability to do mental/calculation tasks, averaged over many tasks. I’ve always found it plausible that machines will continue to do more kinds of mental tasks better, and eventually be better at pretty much all of them. But what I’ve found it hard to accept is a “local explosion.” This is where a single machine, built by a single project using only a tiny fraction of world resources, goes in a short time (e.g., weeks) from being so weak that it is usually beat by a single human with the usual tools, to so powerful that it easily takes over the entire world. Yes, smarter machines may greatly increase overall economic growth rates, and yes such growth may be uneven. But this degree of unevenness seems implausibly extreme. Let me explain. Continue reading "I Still Don’t Get Foom" »

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Proverbs As Insight

Don Quixote’s lower class sidekick Sancho Panza quoted proverbs to excess. Among the intellectuals I know that class association continues – proverbs may help lesser minds, but we elites “think for ourselves.” Proverbs are also associated with older beliefs and attitudes, and so are seen as more politically conservative, and less relevant in our new changed world. Since the world today changes faster, has become less politically conservative, and has more educated folks who aspire to look more intellectual, you might think that we use proverbs less today than we did in 1800.

On the other hand, you might think of proverbs as well-packaged nuggets of useful insight. As the world continues to grow by accumulating insight and innovation, not only do we collect more gadgets, formulas, and words, we should also be collecting more useful proverbs. From this perspective, we should expect people to use more proverbs today.

To get some data on this, I found some lists of famous proverbs, and used Google books ngram viewer to plot their usage in books since 1800:

ProverbUsage

ProverbUsage2Overall usage seems to have gone up, not down. But two considerations complicate this interpretation. One is that I started from lists of proverbs famous today, instead of proverbs famous in 1800. The other is that the typical book reader and author today may be more lower class than they were in 1800, with books catering more to their proverb-friendly tastes.

I hope someone can get better data on this. Even so, maybe we should tentatively expect future folk to talk and write more like ole Sancho Panza, with many more proverbs.

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The Up Side Of Down

In her new book, The Up Side of Down: Why Failing Well Is the Key to Success, Megan McArdle takes some time to discuss forager vs. farmer attitudes toward risk.

Forager food sources tended to be more risky and variable, while farmer food sources are more reliable. So foragers emphasized food sharing more, and a tolerate attitude toward failure to find food. In contrast, farmers shared food less and held individuals responsible more for getting their food. We’ve even seen the same people switch from one attitude to the other as they switched from foraging to farming. Today some people and places tend more toward farmer values of strict personal responsibility, while other people and places tend more toward forager forgiveness.

McArdle’s book is interesting throughout. For example, she talks about how felons on parole are dealt with much better via frequent reliable small punishments, relative to infrequent random big punishments. But when it comes to bankruptcy law, a situation where the law can’t help but wait a long time to respond to an accumulation of small failures, McArdle favors forager forgiveness. She points out that this tends to encourage folks who start new businesses, which encourages more innovation. And this does indeed seem to be a good thing.

Folks who start new businesses are pretty rare, however, and it is less obvious to me that more leniency is good overall. It is not obvious that ordinary people today face more risk than did most farmers during the farming era. The US apparently has the most lenient bankruptcy law in the world, and that is indeed some evidence for its value. However, it seems to me more likely that US forager forgiveness was caused by US wealth than vice versa. McArdle says the US got lenient bankruptcy in the late 1800s via lobbying by senators representing western farmers in debt to eastern banks. And it is even harder to see how farming in the US west then was more risky than has been farming throughout the whole farming era.

Most likely what changed was the wealth of US farmers, and their new uppity attitudes toward rich elites. This fits with debt-forgiveness being a common liberal theme, which fits with liberal attitudes being more forager-like, and becoming more common as rising wealth cut the fear that made farmers. If lenient bankrupts is actually better for growth in our world, this would be another example of Caplan’s idea trap, where rising wealth happens to create better attitudes toward good policy.

Overall I found it very hard to disagree with anything that McArdle said in her book. If you know me, that is quite some praise. :)

Added 2May: The fact that most farmer cultures were clannish may be part of an explanation here. The strict farmer morality is mostly about how to deal with outsiders, distant from your immediate family. The clan is punished severely, but it is usually more forgiving internally. If farmer clans had lower risk than do isolated families today, that could be a reason to have more forgiving bankruptcy law today.

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The Future Of Intellectuals

Back in 1991, … [a reporter] described Andrew Ross, a doyen of American studies, strolling through the Modern Language Association conference … as admiring graduate students gawked and murmured, “That’s him!” That was academic stardom then. Today, we are more likely to bestow the aura and perks of stardom on speakers at “ideas” conferences like TED. …

Plenty of observers have argued that some of the new channels for distributing information simplify and flatten the world of ideas, that they valorize in particular a quick-hit, name-branded, business-friendly kind of self-helpish insight—or they force truly important ideas into that kind of template. (more)

Across time and space, societies have differed greatly in what they celebrated their intellectuals for. Five variations stand out:

  • Influence – They compete to privately teach and advise the most influential folks in society. The ones who teach or advised kings, CEOs, etc. are the best. In many nations today, the top intellectuals do little else but teach the next generation of elites.
  • Attention – They compete to make op-eds, books, talks, etc. that get attention from the intellectual-leaning public. The ones most discussed by the snooty public are the best. Think TED stars today, or french public intellectuals of a generation ago.
  • Scholarship – They compete to master stable classics in great detail. When disputes arise on those classics, the ones who other scholars say win those disputes are the best. Think scholars who oversaw the ancient Chinese civil service exams.
  • Fashion – They compete to be first to be visibly associated with new intellectual fads, and to avoid association with out-of-fashion topics, methods, and conclusions. The ones who fashionable people say have the best fashion sense are the best. Think architecture and design today.
  • Innovation – They compete to add new results, methods, and conclusions to an accumulation of such things that lasts and is stable over the long run. Think hard sciences and engineering today.

Over the last half century, in the most prestigious fields and in the world’s dominant nations, intellectuals have been celebrated most for their innovation. But other standards have applied through most of history, in most fields in most nations today, and in many fields today in our dominant nations. Thus innovation standards are hardly inevitable, and may not last into the indefinite future. Instead, the world may change to celebrating the other four features more.

A thousand years ago society changed very slowly, and there was little innovation to celebrate. So intellectuals were naturally celebrated for other things that they had in greater quantities. The celebration of innovation got a big push from World War II, as innovations from intellectuals were seen as crucial to winning that war. Funding went way up for innovation-oriented intellectuals. Today, however, tech and business startups, and innovative big firms like Apple, have grabbed a lot of innovation prestige from academics. Many parts of academia may plausibly respond to this by celebrating other things besides innovation where those competitors aren’t as good.

Thus the standards of intellectuals may change in the future if academics are seen as less responsible for important innovation, or if there is much less total innovation within the career of each intellectual. Or maybe if intellectuals who are better at doing other things besides innovation to win their political battles within intellectual or wider circles.

If intellectuals were the main source of innovation in society, such a change would be very bad news for economic and social growth. But in fact, intellectuals only contribute a small fraction of innovation, so growth could continue on nearly as fast, even if intellectuals care less about innovation.

(Based on today’s lunch with Tyler Cowen & John Nye.)

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Rah Manic Monopolists?

The vast majority of economic growth is caused by innovation. So when it comes to long term policy, innovation is almost the entire game – whatever policy causes substantially more innovation is probably better, even if has many other big downsides.

One simple robust solution to the innovation problem would seem to be manic monopolists: one aggressively-profit-maximizing firm per industry. Such a firm would internalize the entire innovation problem within that industry, all the way from designers to suppliers to producers to customers – it would have full incentives to encourage all of those parties to put nearly the right amount and type of efforts into innovation.

Yes, even monopolists don’t have exactly the right incentives. They will tend to focus on what marginal customers want, at the expense of both lower-value customers pushed out by inflated monopolist prices, and higher-value infra-marginal customers. And when innovations can cross industry boundaries, industry monopolists may also fail to coordinate with monopolists from other industries. But still, this approach seems to get a lot closer to optimal that anything other simple policy. And if two industries had enough innovation interaction, one might just have a single firm cover both industries.

Ideally these monopolies would be global, but if not national ones might still be a big win over the status quo.

Admittedly, common intuitions don’t agree with this. For one thing we tend to think of monopolists as too lazy to innovate – it takes competition to push them out of their comfort zone. And I agree that this is a common situation for regulated utilities and government agencies. Often the employees of a monopolist tend to have enough political power to entrench themselves and resist change, at the expense of investors and customers. This is why I specified manic monopolists – we need investors to have enough power to impose their will, and we need to have  enough competition to fill these investor roles.

Yes, we also tend to be uncomfortable with the inequality and power concentration that manic monopolists would embody and require. It isn’t at all what foragers are prone to praise. But still, if innovation is important enough, shouldn’t we be willing to tolerate a lot more inequality to get it?

Added 8a 11Apr: In general, industries that are more concentrated, i.e., more in the direction of having a monopolist, have more patents, all else equal. This seems to be because they invest more in R&D. Data here, here.

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