Progress Daily

Bradford DeLong has estimated that for most of the the past 7,000 years economic growth proceeded at a steady exponential rate, with a doubling of output about every 900 years (see “Estimating World GDP, One Million B.C.–Present“). Within the past few centuries, output began doubling faster and faster (the Industrial Revolution), approaching a new steady doubling time of about 15 years. That’s about 60 times faster than in the previous seven millennia.

In the roughly 2 million years our ancestors lived as hunters and gatherers, the population rose from about 10,000 protohumans to about 4 million modern humans. If, as we believe, the growth pattern during this era was fairly steady, then the population must have doubled about every quarter million years. Then, beginning about 10,000 years ago, a few humans began to settle down and live as farmers. The resulting communities grew so fast that they quickly accounted for most of the world population (the Agricultural Revolution). From that time on, the farming population doubled about every 900 years — some 250 times faster than before.

Both eras before now switched suddenly to a new era having a growth rate that was between 60 and 250 times as fast. Both switches were completed in much less time than it had taken the previous regime to double — from a few millennia for the agricultural revolution to a few centuries for the industrial one.

If a new revolution were to show the same pattern as the past two, then growth would quickly speed up by between 60- and 250-fold. The world economy, which now doubles in 15 years or so, would soon double in somewhere from a week to a month. If the new revolution were as gradual (in power-law terms) as the Industrial Revolution was, then within three years of a noticeable departure from typical fluctuations, it would begin to double annually, and within two more years, it might grow a million-fold. If the new transition were as rapid as the Agricultural Revolution seems to have been, change would be even more sudden.

In the era of hunting and gathering, the economy doubled nine times; in the era of farming, it doubled seven times; and in the current era of industry, it has so far doubled 10 times. So if the number of doublings is similar across these three eras, then we seem overdue for another transition.

About two-thirds of all income in the rich countries is paid directly for wages, and much of the remaining third represents indirect costs of labor.

As machines become more “intelligent,” the economy would start growing much faster. We could create machine workers in much less time than it takes to breed, rear, and educate new human workers. Being able to make and retire machine workers as fast as needed could easily double or quadruple growth rates.

The cost of computing has long been falling much faster than the economy has been growing. When the workforce is largely composed of computers, the cost of making workers will therefore fall at that faster rate.

As the economy begins growing faster, computer usage and the resources devoted to developing computers will also grow faster. And because innovation is faster when more people use and study something, we should expect computer performance to improve even faster than in the past.

“Economics Of The Singularity,” by Robin Hanson

Early in the twentieth century, the share of total national income drawn by the top 1% of US earners hovered around 18%. That share hit an all-time high in 1928 — when top earners took home 21%, including capital gains. The top 1% of earners took home less than 10% of all income through the 1960s and 1970s, 15% in 1996, and 20% in 2006.

Americans at the 95th income percentile or higher can expect to live nine years longer than those at the 10th percentile or lower.

The US ranks 21st among the 30 nations in the OECD in terms of life expectancy, and 25th in terms of infant mortality.

The Gini coefficient measures income distribution on a scale from zero (where income is perfectly equally distributed among all members of a society) to one (where a single person possesses all the income). For the US, the Gini coefficient has risen from .35 in 1965 to .44 today. On the per-capita GDP scale, our neighbors are Sweden, Switzerland, and the U.K.; on the Gini scale, our neighbors include Sri Lanka, Mali, and Russia.

In 1965, the average salary for a CEO of a major US company was 25 times the salary of the average worker. Today, the average CEO’s pay is more than 250 times the average worker’s. The current top marginal tax rate — 35% — is far lower than the 91% tax levied on top earners from 1951 to 1963.

Societies with higher inequality tend to have higher crime rates, although it’s not clear which way the causal arrow runs, or if it exists.

When a society is starkly divided along racial or ethnic lines, the affluent are less likely to take care of the poor, Edward L. Glaeser and Alberto Alesina have found. Internationally, welfare systems are least generous in countries that are the most ethnically heterogeneous. Those US states with the largest black populations have the least generous welfare systems. And in a nationwide study of people’s preferences for redistribution, Erzo F.P. Luttmer found that people who lived near poor people of the same race were likely to support redistribution, and people who lived near poor people of a different race were less likely to do so (see “Group Loyalty and the Taste for Redistribution”; pdf file here).

“Unequal America,” by Elizabeth Gudrais

For the third successive year, America’s Border Patrol reports a sharp drop in arrests on and near the frontier. In 2006 the figure dropped 8% to around 1m. Last year it dropped by a full fifth. The six months to March showed a year-on-year drop of 17%. By the (imperfect) measure of border arrests, the migrant flow today is roughly half that of 2000, when 1.6m arrests were made.

Mexico’s central bank reports that, after years of rapid growth, the amount of cash sent home by migrants inside America is falling. Last year such flows were worth $24 billion (more valuable than tourism). But in the first quarter of this year the year-on-year figure was down 2.9%.

A poll of migrants across America published by in April confirmed that fewer are sending money back regularly: in 2006 three-quarters of migrants did, this year only half report doing so. Brazil, the second-largest recipient of remittances in the region, saw them slide by 4% last year, to $7.1 billion.

A study by the Institute for Public Policy Research (IPPR) this year noted that of the 1m or so East Europeans who came to Britain since 2004, around half have already left. The inflow of migrants to Britain from this region has also dropped sharply, by 17% last year.

In Britain the economy is slowing, and the sharp drop in the value of the pound has cut the attraction of the country to foreign workers. Every pound a Pole sent home in May 2004 earned him seven zloties; today he gets little more than four.

East European economies have grown relatively fast in recent years, their labour forces are shrinking fast (partly because of emigration, partly because of ageing populations) and unemployment has dropped quickly in the past half-decade.

Kathleen Newland suggests that based on the experience of countries like Spain, Portugal, Greece and South Korea, emigration usually slows when income per person approaches a threshold level in relation to income in the richer countries where the migrants are heading. The tipping point is when the ratio of incomes reaches about 1:4 or 1:5, especially if the upward trend seems stable. For migrants looking to go to western Europe and North America, this would imply a threshold level of $6,000-7,000.

“A turning tide?,” The Economist

Once someone owns something, he places a higher value on it than he did when he acquired it. “The endowment effect” has been seen in hundreds of experiments, the most famous of which found that students were surprisingly reluctant to trade a coffee mug they had been given for a bar of chocolate, even though they did not prefer coffee mugs to chocolate when given a straight choice between the two.

The effect is not universally observed. Whereas coffee mugs generate an endowment effect, tokens that can be exchanged for coffee mugs do not.

Owen Jones and Sarah Brosnan suspect that, in the evolutionary past, giving things up, even when an apparently fair exchange seemed to be on offer, was just too risky. To test their theory, they have been training chimpanzees to trade (see “Law, Biology, and Property” — pdf file here).

When presented with a choice between peanut butter and frozen juice bars, 60% of the chimps preferred peanut butter to juice. However, when they were endowed with peanut butter, 80% of them chose to keep it instead of exchanging it for juice. And an opposite endowment effect was observed when the chimps were given juice.

Before they started work Jones & Brosnan predicted that the strength of the effect would vary with the evolutionary salience of the item in question. As predicted, when they tried the same experiments using bone and rope toys, no endowment effect was seen. Food is vital. Toys are not.

“The endowment effect,” The Economist

About one in 20 children have a group of symptoms that has come to be known as attention-deficit hyperactivity disorder (ADHD). About 60% of them carry those symptoms into adulthood. ADHD is believed to be genetic, and is associated with particular variants of receptor molecules for neurotransmitters (chemicals that carry messages between nerve cells) in the brain. In the case of ADHD, the neurotransmitter is often dopamine, which controls feelings of reward and pleasure. People with ADHD apparently receive positive neurological feedback for “inappropriate” behaviour.

ADHD sufferers are impulsive. They have trouble concentrating on any task unless they receive constant feedback, stimulation and reward. They tend to perform poorly in modern society and are prone to addictive and compulsive behaviour.

Dan Eisenberg speculated that such behavior may be advantageous for people who lead a peripatetic life. Since today’s sedentary city dwellers are recently descended from such people, natural selection may not have had time to purge the genes that cause it.

Eisenberg tested this by studying the Ariaal, a group of pastoral nomads who live in Kenya. The receptor Mr Eisenberg looked at was the 7R variant of a protein called DRD4, a variant is associated with novelty-seeking, food- and drug-cravings, and ADHD. (See “Dopamine receptor genetic polymorphisms and body composition in undernourished pastoralists.”)

The researchers looked for 7R in two groups of Ariaal. One was still pastoral and nomadic. The other had recently settled down. They found that about a fifth of the population of both groups had the 7R version of DRD4. However, the consequences of this were very different. Among the nomads, who wander around northern Kenya herding cattle, camels, sheep and goats, those with 7R were better nourished than those without. Among their settled relations, those with 7R were worse nourished than those without it.

This discovery fits past findings that 7R and a set of similar variants of DRD4 (the “long alleles”) are more common in migratory populations.

There remains the question of why 7R is found in only a fifth of the Ariaal population. One possibility is that its effects are beneficial only when they are not universal, and some sort of equilibrium between variants emerges.

“The misfits,” The Economist

According to research by Kerwin Kofi Charles, Erik Hurst and Nikolai Roussanov (”Conspicuous Consumption and Race“), conspicuous consumption serves less to establish the owner’s positive status as affluent than to fend off the negative perception that the owner is poor. The richer a society or peer group, the less important visible spending becomes.

An African American family with the same income, family size, and other demographics as a white family will spend about 25% more of its income on jewelry, cars, personal care, and apparel. For the average black family, making about $40,000 a year, that amounts to $1,900 more a year than for a comparable white family. To make up the difference, African Americans spend much less on education, health care, entertainment, and home furnishings. (The same is true of Latinos.)

The researchers hypothesized that visible consumption lets individuals show strangers they aren’t poor. Since strangers tend to lump people together by race, the lower your racial group’s income, the more valuable it is to demonstrate your personal buying power.

To test this idea, the researchers compared the spending patterns of people of the same race in different states — say, blacks in Alabama versus blacks in Massachusetts, or whites in South Carolina versus whites in California. They found that, all else being equal (including one’s own income), an individual spent more of his income on visible goods as his racial group’s income went down. In places where blacks in general have more money, individual black people feel less pressure to prove their wealth.

The same is true for whites. Controlling for differences in housing costs, an increase of $10,000 in the mean income for white households — about like going from South Carolina to California – leads to a 13% decrease in spending on visible goods.

This suggests why emerging economies like Russia and China, despite their low average incomes, are such hot luxury markets today.

Conspicuous consumption, then, is not a universal phenomenon. It’s a development phase that declines as countries, regions, or distinct groups get richer.

In The Middle-Class Millionaire, Russ Alan Prince and Lewis Schiff analyzed the spending habits of the 8.4 million American households whose wealth is self-made and whose net worth, including their home equity, is between $1 million and $10 million. Aside from a penchant for fancy cars, these millionaires devote their luxury dollars mostly to goods and services outsiders can’t see: concierge health care, home renovations, all sorts of personal coaches, and expensive family vacations.

“Inconspicuous Consumption,” by Virginia Postrel

The biggest investment boom in history is under way. Over half of the world’s infrastructure investment is now taking place in emerging economies, where sales of excavators have risen more than fivefold since 2000. In total, emerging economies are likely to spend an estimated $1.2 trillion on roads, railways, electricity, telecommunications and other projects this year, equivalent to 6% of their combined GDPs — twice the average infrastructure- investment ratio in developed economies.

Morgan Stanley predicts that emerging economies will spend $22 trillion (in today’s prices) on infrastructure over the next ten years, of which China will account for 43%. China has spent more (in real terms) in the past five years than in the whole of the 20th century.

Never before has infrastructure spending been so large as a share of world GDP. Even at the peak of Britain’s railway mania in the 1840s, total infrastructure investment was only around 5% of GDP; China is already spending around 12% of its GDP.

The World Bank estimates that a 1% increase in a country’s infrastructure stock is associated with a 1% increase in the level of GDP.

Goldman calculates that a 1% increase in the share of people living in cities leads to a 1.8% increase in demand for installed electricity capacity. A 1% rise in income per head leads to a 0.5% increase in demand. Putting this together, electricity capacity may have to surge by 140% in China and by 80% in India over the next decade.

A 1% increase in income per person leads to a 1.4% increase in the number of passengers travelling by air, so the number of air passengers could jump by more than 350% in China and by 200% in India over the next decade.

“Building BRICs of growth,” The Economist

According to a new report from a UN commission, 2 in every 3 people (some 4 billion in total) are “excluded from the rule of law.” Around 40% of the developing world’s five-year-old children are not registered as even existing. Later, people will find that the home they live in, the land they farm, or the business that they start, is not protected by legally enforceable property rights. Even in the rare cases when they can afford to go to court, the service is poor. India, for example, has only 11 judges for every 1m people.

Because they are outside the rule of law, the vast majority of poor people are obliged to work (if they work at all) in the informal economy, which is less productive than the formal, legal part of the economy. According to the report, this is one of the main reasons why so much of humanity remains mired in poverty.

“The law poor,” The Economist

Ray Kurzweil predicts that if you can live another 15 years, your life expectancy will keep rising every year faster than you’re aging. And then you can be around for the Singularity (when humans and/or machines start evolving into immortal beings with ever-improving software) a few decades later.

In 1976, when Kurzweil pioneered a device that could scan books and read them aloud, it was the size of a washing machine. Two decades ago he predicted that “early in the 21st century” blind people would be able to read anything anywhere using a handheld device. In 2002 he narrowed the arrival date to 2008. Kurzweil debuted his cellphone-sized reader this year.

In the late 1980s, Kurzweil predicted the explosive growth of the Internet in the 1990s and a computer chess champion by 1998 (a year late, it turned out).

Kurzweil makes his predictions using what he calls the Law of Accelerating Returns. More than a century ago, machines’ computing power doubled about every three years; then in midcentury the doubling came every two years; now it takes only about a year.

During the past century there has been exponential growth in the number of patents issued, the spread of telephones, the money spent on education, etc.

Exponential progress has recently begun in nanotechnology, the ease of gene sequencing, and the resolution of brain scans.

Kurzweil says that if his predictions seem overly optimistic that’s because exponential upward curves appear deceptively gradual at first.

“Scientists imagine they’ll keep working at the present pace. They make linear extrapolations from the past. When it took years to sequence the first 1% of the human genome, they worried they’d never finish, but they were right on schedule for an exponential curve. If you reach 1% and keep doubling your growth every year, you’ll hit 100% in just seven years.”

“The Future Is Now? Pretty Soon, at Least,” by John Tierney

A new study by Luigi Guiso, Paola Sapienza, et al. (”Culture, Gender, and Math“), took data from the 2003 OECD Programme for International Student Assessment (in which some 280K 15-year-olds from 40 countries took the same math and reading tests) and compared the results, by country, with each-other and with various measures of social sexual equality (such as the World Economic Forum’s gender-gap index).

On average, girls’ maths scores were lower than those of boys. The gap was largest in countries (such as Turkey) with the least equality between the sexes, & vanished in countries with the most equality — except for geometry scores, which had no relation to sexual equality. The researchers did some additional statistical checks to ensure the correlation was material, and not generated by another, third variable that is correlated with sexual equality, such as GDP per person.

The gap in reading scores not only remained, but got bigger as the sexes became more equal. Average reading scores were higher for girls than for boys in all countries. But in more equal societies, not only were the girls as good at math as the boys, their advantage in reading had increased.

This may explain why, despite girls’ rise to mathematical equality in some countries, women in those countries have not invaded math-heavy professions, such as engineering. Economic optimization is about comparative advantage. The rise in female reading scores alongside their math scores suggests that female comparative advantage in this area has not changed.

“Vital statistics,” The Economist