Monthly Archives: October 2011

US Grows Most ’70-’10

What nation increased its total economic consumption most from 1970 to 2010? If you’ve been reading too much about a US “great stagnation” in that period, the answer might surprise you — the US wins by a long shot. The top thirty gains:

United States 583, Japan 183, China 103, United Kingdom 73, Germany 63, France 53, India 47, Brazil 47, Italy 39, Canada 37, Mexico 37, Spain 28, Indonesia 14, Netherlands 11, Greece 9, South Africa 8, Thailand 8, Switzerland 8, Belgium 8, Austria 7, Colombia 7, Sweden 7, Philippines 7, Norway 7, Malaysia 7, Portugal 6, Chile 6, Finland 5, Ireland 5, Denmark 4. (source)

Units are tens of billions of dollars per year. All of Western Europe adds up to 285. Since total world change was ~1460, the US had ~40% of all consumption growth.

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Transferable Citizenship

In 20th century USA, many feared that if a black moved into their neighborhood, “white flight” would greatly lower their property values. In many places it was illegal to sell your house to a black. But it was never illegal to sell your house to outsiders. At the national level today, however, we actually do adopt the extreme “no house selling” analogy: we don’t let folks transfer their citizenship to foreigners.

Imagine each US citizen could transfer her citizenship to a foreigner, as long as she found somewhere else to live, [added: hadn’t recently given birth,] and wasn’t about to die, and the foreigner was at least as old, and wasn’t a terrorist, ex-con, etc. Benefits:

  • Citizenship could be collateral for loans for school, houses, etc.
  • We’ll prefer those who’d pay to come, over those who choose to leave.
  • Undesirable poor folk are especially likely to leave.
  • Retirees could be paid to retire more cheaply abroad.

Similar to those old rules against selling houses to blacks, we could also add more restrictions on to whom citizenship could be transfered. At least if we were willing to publicly own up to the racism, ethnism, etc. that such restrictions embodied.

Now folks like Julian Simon and Gary Becker have proposed selling citizenship before, without much success. But it seems to me better marketing to first focus on giving each person a direct benefit: more freedom to use an asset they already own, citizenship. First, get folks to see that selling citizenships makes as much sense as selling houses or club memberships. Then suggest that letting government add to the pool of citizenships for sale might raise revenue, and maybe help the economy as well.

This post was sparked by hearing a talk by Michael Clemens, who noted that we saw no effect on wages from either the Cuban boat lift that suddenly increased Miami’s population by 7%, nor the sudden elimination of migration restrictions within South Africa. Those sound like great pro-immigration arguments to an economist, but alas seem a bit too indirect for the public.

Added: Bryan suggests immigrants pay extra taxes, while Alex suggests giving visas to house buyers.

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Impossible Is Real

Fermi famously argued that either aliens aren’t out there, or they can’t or don’t want to get here, since we see none around us. An undated Stephen Hawking lecture makes a similar argument about time travel:

If sometime in the future, we learn to travel in time, why hasn’t someone come back from the future, to tell us how to do it. Even if there were sound reasons for keeping us in ignorance, human nature being what it is, it is difficult to believe that someone wouldn’t show off, and tell us poor benighted peasants, the secret of time travel. … If governments were hiding something, they are doing a pretty poor job of extracting useful information from the aliens. … Once you admit that some are mistakes, or hallucinations, isn’t it more probable that they all are, than that we are being visited by people from the future, or the other side of the galaxy? If they really want to colonize the Earth, or warn us of some danger, they are being pretty ineffective.

Many people seem quite resistant to the idea that fundamental limits might apply to our descendants, limits that continue even after trillions of years of advancement. But if we have vast hordes of descendants over trillions of years, almost none of them have the ability and inclination to travel back in time to visit us now. Because almost none are visiting. Some things really are impossible.

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Limits of Imagination


Our finite universe simply cannot continue our exponential growth rates for a million years. For trillions of years thereafter, possibilities will be known and fixed, and for each person rather limited.

Bryan Caplan:

He’s probably right for physical goods. But why couldn’t the quality of life in virtual reality grow at 4% [per year] for ever? Serious virtual reality wouldn’t be like toothpicks; it would be a vast array of virtual goods and experiences. And since these goods and experiences would be imaginary, there’s no reason they couldn’t grow forever. Laugh if you must: Imagination really is infinite!

Let me try to explain (again).

Imagine that in a million years, our descendants occupy all the 1070 atoms in our galaxy and its surrounding volume, and that it will take another million years to grow that number by a factor of ten, to 1071. They’ve spend a million years searching the space of possible physical devices: signal senders & processors, radiators, nuke & black hole power plants, etc. They’ve found some very good designs, and in another million years of searching don’t expect to find designs that are overall a hundred times more efficient. Even if computational capacity grew as the square of available mass (such as might be possible with black holes), for the next million years they expect their total computational capacity to grow by less than a factor of ten thousand, or 0.001% per year.

Over the last million years they’ve also been searching the space of enjoyable virtual reality designs. From the very beginning they had designs offering people vast galaxies of fascinating exotic places to visit, and vast numbers of subjects to command. (Of course most of that wasn’t computed in much detail until the person interacted with related things.) For a million years they have searched for possible story lines to create engaging and satisfying experiences in such vast places, without requiring more computational resources behind the scenes to manage.

Now in this context, imagine what it means for “imagination” to improve by 4% per year. That is a factor of a billion every 529 years. If we are talking about utility gains, this means that you’d be indifferent between keeping a current virtual reality design, or taking a one in a two billion chance to get a virtual reality design from 529 years later. If you lose this gamble, you have to take a half-utility design, which gives you only half of the utility of the design you started with.

If you spend all your time in virtual reality, and if your utility were your years of life times the virtual reality design quality, then you’d be indifferent between a 310 year life in your current design or a ten second life in the 529 year future design.

And 529 years is tiny on a cosmological scale. Over a million years 4% annual growth produces a factor of 1017,000. Could you really be indifferent between taking that infinitesimally small a chance of moving to a million year future virtual reality, where if you lose the gamble you have to accept a half-utility virtual reality? Would you really keep repeating this gamble as your utility fell to zero? And the universe will survive for many trillions of years — in a trillion years 4% annual growth gives a factor of over 101010.

It may be possible to create creatures who have such strong preferences for subtle differences, differences that can only be found after a million or trillion years of a vast galactic or larger civilization searching the space of possible designs. But humans do not seem remotely like such creatures. We like stories, to be sure, but most of us are pretty satisfied with simple variations on standard story lines – we just don’t get billions of times more value from the very best stories, over pretty good stories.

It is also very hard to see how creatures with such subtle preferences would have adaptive advantages in a competitive future scenario. And in a non-competitive scenario I for one don’t see much point in trying to populate our universe with such extremely picky creatures.

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The Future Of Cities

What sets city size? That is, what determines how many people all cluster together in an urban area? On the one hand, city size increases with feasible building height and with the gains to people and businesses from interacting closely with many others. On the other hand, city size decreases with how much space folks want, and with costs to transport people and goods within a city and from outlying regions. City size increases with more and cheaper nearby non-city economic activity.

Policy also matters; poor governance and positive externalities of density reduce city size, while being the center of government for a surrounding area increases city size. The size of big cities should be limited by the reluctance of nations to let their city activity be absorbed into big nearby foreign cities. And sunk costs and coordination failures can long delay the adaptation of city sizes and locations to changing circumstances.

In the farming era, cities held only a small fraction of the population, and so their size and locations were determined mainly by nearby farming activity. However, when most folks live in cities, then nearby non-city activity matters less, and decreasing transport costs make bigger cities more economical.

So how well have today’s city size and locations adapted to industry era tradeoffs? That is, how well do cities today trade the gains from more interaction in bigger cities for the added costs of transport and reduced personal space? While we expect optimal industry era cities to be more concentrated, i.e., fewer and larger, we also expect inertia, coordination failures, density externalities, and city mismanagement to slow the transition from an ideal farming era distribution of cities to an ideal industry era distribution. So cities today are probably too many and small. But how far off are they?

One clue – alas one that that is hard to interpret – is that today (log) city size follows a normal distribution, and (log) size changes follow a random walk. Another more informative clue is that in many large nations, a big (but not too big) fraction of the urban population is in the largest city. For example: South Korea 53%, Japan 44%, Egypt 43%, Argentina 37%, Bangladesh 34%, Philippines 28%, Mexico 24% (sources here, here). This weakly suggests that such cities might be running up against a political limit – the reluctance of neighboring nations to let these cities absorb their city activity.

How should we expect cities to change in a future em era, where trillions of human emulations live in virtual reality or in tiny android bodies? Since ems are easier to transport, require less space, and interact less with rural areas, optimal em cities should be even more concentrated than industry cities. Especially if ems learn to better subsidize density, to internalize today’s density externality. And since ems require quite different infrastructure from humans, and need large and rapid changes that most cities will initially be unwilling to allow, existing industry era cities may less constrain the size and location of em cities.

Together these suggest that em cities might be quite a bit more concentrated than our industry cities. Most ems might live within a half dozen or fewer really huge cities. Which would imply that only a half dozen nations would have substantial political power, allowing for easier global coordination.

If optimal em city concentration is really high, most ems might even live in just one biggest city. An analogy in the history of brains seems apt. Some of the first brains were spread out all over animal bodies, but then brains evolved to concentrate in one small region, to minimize signal delays within the brain.

Of course one big em city could be vulnerable to bad governance, so perhaps the biggest city would change as biggest cities became badly managed. Especially if ems had better ways (e.g. prediction markets) to coordinate their city switching activities. Creates an interesting picture of a competitive world government – at any one time most world economic activity might be under a single central city government, and yet cities might compete to offer the best world governance.

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The End of Possibility

Once upon a time, down on the farm, ordinary lives had few options. Only a few neighbors were available as friends or lovers, only a few careers were possible, and most careers had rather predictable daily schedules. (Forager work varied only a bit more.) By contrast, cities, travel, and even war offered many exciting possibilities. Fiction celebrated these things, and fiction itself offered even more possibile experiences.

Our modern world is chock full of cities and travel, and many career and leisure options. Our diverse fiction celebrates this expansion of possibility. In fact, endless expanding possibility seems central to our modern view. We all “know” that new techs expand our possibilities, and an endless series of new techs lie ahead, each more unpredictable than the last. Science fiction emphasizes a blizzard of strange futures, from which most folks take the lesson that the future is so unpredictable that there is little point thinking about it. Most think we can’t even count on basic physics, as new paradigms could change everything.

But in the long run, this faith in endless possibility is completely wrong. Yes our dreamtime era is fantastically rich with change and possibility, but on cosmological time scales this simply cannot last. And not only is it possible for foresee outlines of the future, it is important that we do so.

Yes, our physics isn’t the last word, for but for most practical purposes it is damn close. New physics will only make a difference in incredibly unusual cases. Our understanding of basic economics is also hardly the last word, but we still understand enough for it to give useful insights into future societies.

Yes, new tech have recently given us each more options, but this is mainly because new tech tends to make us each richer. Wealth gives options. If our descendants are, as I suspect, much poorer than we, they may well have fewer options than us. And eventually economic growth and tech innovation must slow to a crawl. Our finite universe simply cannot continue our exponential growth rates for a million years. For trillions of years thereafter, possibilities will be known and fixed, and for each person rather limited.

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Hidden Trade Barriers

Christopher Magee asks why rich nation tariffs are not high. He concludes they are in fact high, but in hidden ways:

In the median industry … over $42 is transferred from consumers to producers for every $1 in efficiency costs caused by the tariff. … The industry lobby should be willing to contribute a lot to the politician to raise those tariffs. And because higher tariffs cause such a small reduction in overall welfare, the policy-maker should be willing to trade higher tariffs for campaign cash. … Thus, instead of asking why there are trade barriers at all, the real puzzle in the literature should be why the trade barriers are not extremely high in most industries.

Here is my assessment … I do not believe that policy-makers care only about social welfare and do not care about campaign contributions. … I also do not think that tariffs are low because users of imported intermediate goods spend a lot of time and money lobbying against tariff protection. … A moderately important reason why tariffs are low is that free riding limits industries’ ability to organise political lobbies. … I also consider the hidden costs of trade barriers as somewhat important in explaining low tariffs. Policy-makers understand the value of good international relations and the cost of trade wars. …

The most important explanation for the puzzle of surprisingly low tariffs is that the political economy literature is largely right: trade barriers are relatively high even in developed countries but they are hidden as quotas and other non-tariff barriers. Unfortunately, these non-tariff barriers, which do not generate government revenue and become more restrictive as the size of the market grows, harm the economy even more than open tariffs do. … In trade policy, what we don’t see is hurting us the most. …

Kee et al. (2004) estimate that the average manufacturing industry in the USA in 1996 had non-tariff barriers that added over 10% to the price of imported goods and that the non-tariff barriers were over three times larger than the tariff rates. In 2004, the ad valorem equivalent of core non-tariff barriers was 9.5% in the USA and 13.4% in the European Union according to estimates from Kee et al. (2009). Trefler (1993) … finds that … the non-tariff barriers were over six times as restrictive as tariffs and that the ad valorem tariff equivalent of US non-tariff barriers was over 20%. (more)

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A Theory Of Status

A few days ago I asked for a theory of status, to help predict how status will change in a rather different future. Today let me offer such a theory.

Here are our main clues about status:

  1. Status is a socially shared way to evaluate and rank people
  2. Status seems mostly relative; you can’t raise everyone’s status
  3. Human status has two main parts: dominance and prestige
  4. Most animals have dominance, which is who would win a pairwise conflict
  5. Prestige status seems to not exist in animals with simple social relations.
  6. Unlike other shared rankings, like sexiness or dominance, we seem unaware of what exactly prestige ranks.

So what is prestige? That is, what sort of ranking would be useful for human-like primates to track about each other, but also be something illicit, so that foragers would be reluctant to admit its true function? One obvious candidate stands out to me: one’s value as an ally in coalition politics. That is, how much better off is a typical coalition with this person as an ally, relative to not having them as an ally. This is clearly an important concept, well worth tracking. It only makes sense in groups with complex coalition politics, and foragers have norms against overtly engaging in such politics.

Since an ability to win pairwise contests is useful to coalitions, we expect dominance to add to prestige. But humans and similar primates can also add value to a coalition by having skills that make them useful associates, and by being on good terms with other good-ally-material folks. And both skills and associations also seem to make important contributions to human prestige. Note that this theory predicts that other primates with complex coalition politics, like chimps, will also have a prestige status distinct from dominance status.

If prestige is about one’s value in coalition politics, what does that predict about em prestige? Of the list I gave, items 2,5,7,12,16, should be substantially related to prestige.

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Allen & Greaves On Ems

Paul Allen and Mark Greaves say the “singularity” is over a century away:

This prior need to understand the basic science of cognition is where the “singularity is near” arguments fail to persuade us. …. A fine-grained understanding of the neural structure of the brain … has not shown itself to be the kind of area in which we can make exponentially accelerating progress. … By the end of the century, we believe, we will still be wondering if the singularity is near.

But what about the whole brain emulation argument that we can simulate a brain without understanding it? They say:

For example, if we wanted to build software to simulate a bird’s ability to fly in various conditions, simply having a complete diagram of bird anatomy isn’t sufficient. To fully simulate the flight of an actual bird, we also need to know how everything functions together. In neuroscience, there is a parallel situation. Hundreds of attempts have been made (using many different organisms) to chain together simulations of different neurons along with their chemical environment. The uniform result of these attempts is that in order to create an adequate simulation of the real ongoing neural activity of an organism, you also need a vast amount of knowledge about the functional role that these neurons play, how their connection patterns evolve, how they are structured into groups to turn raw stimuli into information, and how neural information processing ultimately affects an organism’s behavior. Without this information, it has proven impossible to construct effective computer-based simulation models.

This seems confused. No doubt a detailed enough emulation of bird body motions would in fact fly. It is true that a century ago our ability to create detailed bird body simulations was far less than our ability to infer abstract principles of flight. So we abstracted, and built planes, not bird emulations. But this hardly implies that brains must be understood abstractly before they can be emulated.

Yes you need to understand a system well in order to know what details you can safely leave out and still achieve the same overall functions. But if you can afford to leave in all the details, you don’t have to understand what is safe to leave out. We apply this principle every time we play a song or movie. Since we know that a song or movie recording contains enough detail to reproduce a full sound or visual experience, we don’t have to understand a song or movie in order to be able to replay it for someone, and achieve most of the relevant artistic experience.

Projecting trends like Moore’s law suggests that our ability to simulate low level brain processes should increase by fantastic factors within a century. These factors seem plenty sufficient to model entire brains at low levels of detail. So if we have not understood brains well enough by then to know what details we can safely leave out, we should be able to reproduce their behavior via brute-force simulation of lots of raw detail.

Added 10p: As I explained in January:

We should expect brain emulation to be feasible because brains function to process signals, and the decoupling of signal dimensions from other system dimensions is central to achieving the function of a signal processor.

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What Status Ems?

While many things count for status in our society, most of us have a rough idea of their relative weight, at least for common evaluations. But we understand the origins of these weights poorly. This ignorance seems especially clear when we consider how status might change in the future. For example, I’ve been pondering the scenario of a future world dominated by ems (whole brain emulations), and realize that it seems especially unclear what would count more for status among ems. Some possibilities:

  1. Pure physical size or power
  2. Impressiveness in conversation or verbal sparring
  3. How well its personality embodies the ideals of its age
  4. How mental, complex, or abstract is its job
  5. # other statusful ems this em commands or controls
  6. The accomplishments of this copy, since its last split.
  7. # other high status ems know it personally
  8. Political influence of this em in local disputes
  9. Personal em wealth
  10. Current daily wages
  11. Current daily profit, of wages minus cost to exist
  12. The status its human had in the pre-em world
  13. Total time this mind has experienced subjectively
  14. Time expected until em forced to retire/archive
  15. # active copies expected of this em at a future date
  16. # active “clan” copies, all of the same pre-em human
  17. # active copies expected of this clan at a future date
  18. The total accomplishments of the entire copy clan
  19. # other high status ems know anyone in clan
  20. Total wealth of its copy clan
  21. Total potential political influence of its copy clan

Of course if we had a good theory of status, we could use that to predict future status. For example, if status were a measure of future evolutionary success, then #15 would make sense. But if status were instead a measure of the value of an ally in local coalition politics, then #8 would make more sense.

Many of these measures (e.g., #14) could produce an abrupt change in status when a new copy is created. Do abrupt status changes make sense when others’ opinions about you haven’t changed?

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