Category Archives: Growth Causes and Consequences

Handle’s theory of consolidation

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Referring to Hayek’s claim that local knowledge favors decentralized decision processes, Handle comments,

IT and increasingly capable and sophisticated management information systems, which themselves benefit from massive economies of scale, and the management techniques they enable, has invalidated this argument. If anything, big companies now seem to have a clear advatange with regards to acquiring and leveraging ‘local knowledge’, and combined with the other advantages of brand recognition, size and sophistication and capacity for, e.g., rent-seeking and bearing the burden of compliance overhead, that leaves “the little, genuinely-independent guy” with zero chance in the long run

1. I wonder if this applies to government. If the U.S. federal government took advantage of Big Data, could we be as well-run as Singapore or Norway? I tend to doubt it. Perhaps someone wants to argue that we could be that well-run if we had an epistocracy.

2. Once again, I am reminded of a Diamond Age world. Technology can allow giant enterprises to meet everyone’s needs cheaply. By the same token, luxury consists of goods and services provided by small artisan craftspeople.

3. This is another instance in which the Internet vision of the 1990s, the days of the “hippie Internet,” is turning out to be wrong.

4. Will there be sufficient dynamism in this big-firm economy? Where will competition come from? From small firms that can suddenly get big and unseat big incumbents? From big incumbents trying to encroach on one another’s turf?

Disaggregating the economy: clusters ten years later

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A dozen years after coming out with The Clustering of America, Michael Weiss published The Clustered World, in 2000. This incorporated census data from 1990, which moved the analysis 10 years forward, but still leaves it well out of date as of 2017.

There was a movement to outlying locales that Weiss described as “repopulating rural America,” which struck me as a questionable description. I wonder if instead it represented metro areas spreading out into “edge cities.”

There was a rise in the Hispanic population, and Weiss claimed that this population was showing signs of wanting to stick together, rather than to assimilate into the rest of the country. He also saw an increase in isolation of the African-American population, which is the opposite of what one would have extrapolated based on prior trends toward integration.

Weiss used a survey of journalists to find that they lived predominantly in a few clusters toward the upper end of the income and status scale. It was already clear to him that they would have difficulty relating to people in middle-class and poor clusters.

Writing in 2000 and looking ahead, Weiss foresaw a continued increase in growth in far suburbs. Also, he made the straightforward projection that the Baby Boom generation would be headed toward a lifestyle characterized by retirement. With aging in general, he expected to see new clusters emerging with the age 55-75 bloc, as well as a cluster of people over 85 and ensconced in assisted living facilities.

He thought that there would be a distinctive Asian cluster, but my impression is that this has not developed. If I am correct about that, then the explanation is pretty simple. The “Asian” category is too broad, encompassing mainland Chinese, Taiwanese, Japanese, Koreans, Vietnamese, Indians, Pakistanis, and so on. These disparate nationalities do not all naturally congregate with one another. Instead, one is likely to find them dissolved into the rest of the U.S. population.

I would be curious to see what clusters would show up today. I assume that Charles Murray’s Coming Apart story means that we would see clusters that differ dramatically by marital status. We would see households with two married adults in relatively large numbers in affluent zip codes, and we would see single parents prevalent in poor zip codes.

I speculate that we would see a decline in the share of employment in the for-profit sector and an increase in employment in non-profits. This is based in part on the growth of the New Commanding Heights of education and health care. Also, I am guessing that the super-rich are inclined to fund non-profits, so that the size of that sector goes up as more wealth accrues to the super-rich. I do not know how significant a trend this is, or how well it can be measured.

I speculate that we would see an increase in the urban-rural divide. That is, compare average incomes in zip codes where most households are within, say, 25 miles of a major city (one of the top 20, say) with zip codes where most households are more than 50 miles from a major city.

I speculate that differences in average levels of education across zip codes now are even more predictive of income differences than they were twenty years ago.

I speculate that we would see little progress in integration of African-Americans and Hispanics. They would continue to appear in their own distinctive clusters more often than mixed in with clusters of non-Hispanic whites.

Tim Harford and Russ Roberts

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An econtalk podcast, of course. At one point, Harford says,

one thing I learned is not to undervalue innovations that are important simply because they have become very, very cheap, so they’ve become ubiquitous. The other thing I learned was not to forget the way that inventions reshape organizations, reshape the way we live, reshape societies. Often in order to use an invention, take advantage of an invention, you need an awful lot of adjustment. The classic example, which will be well known, I think, to some EconTalk listeners, is Paul David’s essay on “The Dynamo of the Computer”, reflecting on how long it took electric motors to be adopted in manufacturing in the late 19th-early 20th century, because people had to completely readjust, reconfigure the factories, retrain the workers. I mean, just everything had to change in order to take advantage of this new technology. And initially when it was used, they tried to direct replacement to the steam engine–just rip out a big steam engine, replace it with a big electric motor, and that should be fine. And of course that doesn’t realize the gains. Because to really take advantage of these technology, we often have to change, and adjust the way we do things–the way we work, the way we live. Otherwise we don’t enjoy the benefits. And sometimes those changes can be–well, they are very hard to predict, but they are occasionally quite hard, quite wrenching.

Disaggregating the economy/New Commanding Heights watch

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A chart from Jeff Desjardins shows the largest employer in each state. The results: Wal-mart is the largest in 22 states. A health care network is the largest in 12 states. A university system is the largest in 11 states. That leaves 5 states with “other,” only one of which is a manufacturing firm (Boeing in the state of Washington).

I think that this reflects a Great Consolidation in retail and in health care. Mom-and-pop stores and small medical practices have been wiped out. That means you want to be really careful about interpreting statistics that seem to say that Americans aren’t starting new businesses the way that they used to. The opportunities are not what they used to be.

Hal Varian’s Rule

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I’ve come across it in several places recently, such as this podcast with Tim O’Reilly. The rule says,

A simple way to forecast the future is to look at what rich people have today; middle-income people will have something equivalent in 10 years, and poor people will have it in an additional decade.

I can think of many exceptions off the top of my head, and it depends on definitions. There will always be a luxury form of something–the private jet, for example.

But overall I think it’s a view of the world that is more sensible than “robots are going to kill all the jobs and there will be mass poverty.”

Ray Dalio’s data points

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The essay is on inequality, but there are interesting statistics scattered throughout. For example,

While many of the major causes of death have been flat or falling over the last 15 years, deaths from drugs and alcohol more than offset it among the bottom 60%. And the rise in drug-related deaths is not happening across the world—the phenomenon is unique to the US.

Pointer from John Mauldin.

I could swear that when I first looked at Dalio’s piece, he had more tables with more statistics, including death rates that are preventable with health interventions (higher for the U.S.) Those tables, which are in the appendix, do not show up in the version of Chrome on my laptop. Ah, there they are. They show up fine on the Microsoft browser and on Chrome on my tablet. They appear to be graphics. If you don’t see a table called “Health Care Performance Measures Across Developed Nations,” try a different browser. Those tables are a big reason that I am sending you to his essay.

The Servant Aggregators

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Several years ago, I asked,

In an economy where some folks are very rich and many folks are unemployed, why are there not more personal servants?

Recently, someone pointed me to Umair Haque’s column from two years ago.

I’m going to call it a Servitude Bubble. For the simple reason that it is largely based on creating armies of servants. You can call them whatever buzzwords you like — “tech-enabled always-on super-hustling freelance personal brand capitalists”. But the truth is simpler. The stuff of the Servitude Bubble makes a small number of people something like neofeudal masters, lords with a corncucopia of on-demand just-in-time luxury services at their fingertips. But only by making a very large number of people glorified neo-servants…butlers, maids, chauffeurs, waiters, etcetera.

Dog walkers, Uber drivers, etc. My question was answered.

But it’s not just a few rich people with access to these services.

Bob Lutz thinks as I do

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The GM executive writes,

in 15 to 20 years — at the latest — human-driven vehicles will be legislated off the highways.

The tipping point will come when 20 to 30 percent of vehicles are fully autonomous. Countries will look at the accident statistics and figure out that human drivers are causing 99.9 percent of the accidents.

Lutz thinks that this will mean the end of the automobile as a household-owned transportation apparatus. Read the whole thing. Pointer from James Pethokoukis.

Reality vs. Kurzweil’s expectations

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One way to track scientific and technological progress is to compare outcomes to predictions that were made by futurists. So I pulled out my copy of Ray Kurzweil’s The Age of Spiritual Machines, written 20 years ago, which has predictions for 2009 and every decade thereafter. Are there predictions that he made for 2019 that came true sooner? Are there predictions that he made for 2009 that came true much later?

I will get into some specifics below, but some general points that occur to me from re-examining these predictions are the following.

1. Relative to his predictions, I can think of few “upsides” (something that appeared sooner or turned out better than predicted) and many “downsides.” Most of his predictions for 2009 have come to pass only in the past few years, and some are still remote. But to offer a more positive take, the fact that most of his milestones for 2009 have been hit as of 2017 is probably a better outcome than most other prognosticators would have been willing to bet on in 1999.

Roughly 50 percent of his predictions for 2019 now appear likely to be realized between 2025 and 2030, and the remaining 50 percent ought to be pushed back even farther.

2. I sense that a lot of progress that he expected has been held back by ergonomic issues. For example, language translation software may be effective, but people find ear buds and microphones to be uncomfortable. Similarly, augmented reality has been held back by the poor ergonomics of what goes over your eyes and ears. Collaboration across distance is not nearly as effortless as Kurzweil anticipated, even though software firms have put a lot of resources into “collaboration tools.”

Maybe more venture capital resources ought to be focused on finding breakthroughs in ergonomics.

3. Progress also has been slow in developing applications that react to the emotional state of human users. This is particularly important if computers are going to contribute outstanding value in education.

4. There is considerable cultural drag. Kurzweil predicted that by 2019 there would be parts of the road system dedicated exclusively to self-driving cars. One can argue that the technology is here to do that, but the culture is not ready to accept the idea.

I think that this cultural drag is becoming increasingly important. William Gibson’s saying that “The future is already here. It’s just not very evenly distributed” is even more apt than when he said it. Continue reading →

The AI productivity paradox

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Erik Brynjolfsson, Daniel Rock, and Chad Syverson write,

Systems using artificial intelligence match or surpass human level performance in more and more domains, leveraging rapid advances in other technologies and driving soaring stock prices. Yet measured productivity growth has declined by half over the past decade, and real income has stagnated since the late 1990s for a majority of Americans. We describe four potential explanations for this clash of expectations and statistics: false hopes, mismeasurement, redistribution, and implementation lags. While a case can be made for each, we argue that lags have likely been the biggest contributor to the paradox. The most impressive capabilities of AI, particularly those based on machine learning, have not yet diffused widely. More importantly, like other general purpose technologies, their full effects won’t be realized until waves of complementary innovations are developed and implemented. The required adjustment costs, organizational changes, and new skills can be modeled as a kind of intangible capital. A portion of the value of this intangible capital is already reflected in the market value of firms. However, going forward, national statistics could fail to measure the full benefits of the new technologies and some may even have the wrong sign.

That is from the abstract. I cannot find a free ungated version of the full paper. Meanwhile, my thoughts:

1. I don’t have enough confidence in productivity data to believe a statement like “productivity growth has declined by half.” I’ve already explained why. I already think that the national statistics are misleading.

2. As to the diffusion explanation, maybe we’re in a situation today where AI and machine learning are like mainframe computers, with seemingly only a few giant firms able to take advantage. Maybe if somebody comes up with “AI and machine learning for the rest of us” the story will be different.