Progress Daily

The graph below is from a fascinating new paper, “What Happens When We Randomly Assign Children to Families?,” by Bruce Sacerdote. Holt’s International Children’s Services places children, primarily Koreans, with families in the United States. Children are randomly assigned. Sacerdote has collected data from children who were adopted between 1970-1980, and thus who today are in their mid-20s or -30s, and their adoptive parents.

The graph shows how parent income at the time of adoption relates to child income for the adopted and “biological” (non-adopted) children. The income of biological children increases strongly with parental income but the income of adoptive children does not.

The graph does not say that adopted children necessarily have low income; some have high and some have low income and the same is true of biological children. What the graph says is that higher parental income predicts higher child income but only for biological children and not for adoptees.

“Nature, Nurture and Income” by Alex Tabarrok

In 1900, the vast majority of very bright young adults did not get a college education, and even by the mid-1920s only about half of those in the top IQ decile were entering college. By the 1960s, the probability that those in the top IQ decile would enter college was almost 100%, regardless of whether they were rich or poor, white or black.

The mean SAT score for entering freshmen at Harvard rose so dramatically that the average freshman in 1952 would have been in the bottom 10% of the class in 1960.

In constant dollars, an engineer earned about $30,000 in 1952 compared with $20,000 for a manufacturing worker, which was not much different from the ratio at the beginning of the century. By 1988, the engineer earned almost $75,000 compared with $22,000 for the manufacturing worker.

The NLSY (National Longitudinal Survey of Youth) contains a sample of almost 13,000 young people who have been interviewed periodically from 1978 on. By 1992, the subjects were 28 to 35 years old. The data on siblings applied to nearly 3,000 sibling pairs who had the same biological parents, lived with their biological parents at least through the younger sibling’s 7th year, and had valid scores on the Armed Forces Qualification test. Where the IQ differed, the results were striking. For example, where both children had attended elementary and secondary schools for the same number of years, only 18% of the siblings with “normal” IQs (in the 90 to 109 range) got bachelor’s degrees, while 83% of their brothers or sisters in the very bright category (IQ of 125 or above) did so.

A measure called the Duncan scale, which runs from 1 to 100, ranks occupations according to pay, prestige, educational requirements, and similar factors. For the siblings with normal IQs, the median Duncan score was 41. For the brightest brothers and sisters it was 62 — indicating managerial, administrative, and professional positions — and for the dullest it was 11.

Median income was $19,000 for the middle IQ range, for the brightest it was $30,000, and for the dullest it was $7,500. Particularly for those in the brighter groups, incomes can be expected to increase as they get older, while those in occupations lower in the Duncan scale cannot expect such increases later in life.

“Income Inequality and IQ” by Charles Murray

Paul W. Glimcher trained thirsty monkeys to direct their eyes to one of two illuminated targets, which earned them differing chances of getting juice rewards — a 50% chance of getting a full cup of juice for looking right, say, versus a 75% chance of getting 1/2 a cup of juice for looking left. The game was repeated many times, with the probabilities changing periodically.

Before long, the monkeys were dividing their time between the illuminated targets in a way that roughly maximized their payoffs. When the odds favored looking right, they looked right; when the odds favored looking left, they looked left.

Glimcher’s experiment implies that monkey brains act as if they were solving a mathematical problem, which is what economists assume when they depict people as rational agents trying to maximize their well-being (”utility”).

“Mind Games” by John Cassidy

Also see Behavioral Monkeynomics

The best companies in terms of comparative return on invested capital (ROIC) are also the most highly valued, even though most investors have never even heard of return on invested capital. The market recognizes value, even though it couldn’t say why.

Every year, Michael Mauboussin hands his students a form and asks them to estimate IBM’s assets at the end of 1989 (not a number that you would expect even business students to know exactly). Every year, without fail, the mean of all the responses is within 5% of the actual number.

Every year, Mauboussin assembles a good-sized group of people (100-125 people) and gives them a ballot for the Oscars. On one side are the six most popular categories and on the other are six more estoeric categories. Each participant chips in a dollar and then guesses who will win the Oscar in each category. Without fail, the group’s mean response across the 12 categories does better than any single human.

Experiments like the ones that Mauboussin does work best when all the actors make their guesses independent of what everyone else is guessing. In other words, neither the IBM nor the Oscars experiments would work if people shouted out their answers one by one, because hearing the answers of others would shape the decisions of those that followed.

But in the stock market, of course, people are always shouting out their answers. As a result, the market is subject to manias and panics, which you might define as periods when investors are only worrying about how everyone else is answering the question, instead of what the right answer is.

“The Dumb Smart Market” by James Surowiecki

Colin Camerer performed brain scans on a group of volunteers while they placed bets on whether the next card drawn from a deck would be red or black. In an initial set of trials, the players were told how many red cards and black cards were in the deck, so that they could calculate the probability of the next card’s being a certain color. Then a second set of trials was held, in which the participants were told only the total number of cards in the deck.

The second setup was more like the real world: the players knew something about what might happen, but not very much. With less information to go on, the players exhibited substantially more activity in the amygdala and in the orbitofrontal cortex, which is believed to modulate activity in the amygdala. “The brain doesn’t like ambiguous situations,” Camerer said. “When it can’t figure out what is happening, the amygdala transmits fear to the orbitofrontal cortex.”

The results of the experiment suggested that when people are confronted with ambiguity their emotions can overpower their reasoning, leading them to reject risky propositions. This raises the possibility that people who are less fearful than others might make better investors, which is precisely what George Loewenstein found when he carried out a series of experiments with a group of patients who had suffered brain damage.

Each of the patients had a lesion in one of three regions of the brain that are central to the processing of emotions: the amygdala, the orbitofrontal cortex, or the right insular cortex. The researchers presented the patients with a series of fifty-fifty gambles, in which they stood to win a dollar-fifty or lose a dollar. This is the type of gamble that people often reject, owing to loss aversion, but the patients with lesions accepted the bets more than 80% of the time, and they ended up making significantly more money than a control group made up of people who had no brain damage.

“Mind Games” by John Cassidy

The world as a whole has not had the sixteen-fold multiplication of its material prosperity seen in the United States over the past century. Only 12% of the world’s population lives in countries where GDP per capita at the start of the third millennium was more than $20,000 per year.

The average inhabitant of Thailand of Tunisia today has about 3 times the productive potential of the average inhabitant of the United States in 1900; and the average inhabitant of Argentina, Botswana, Uruguay, or Mexico has 5 times the material productive potential of the average inhabitant of the U.S. in 1900.

Perhaps 36% of the world’s population in 2000 lives in a country with a level of material output per capita less than that of the United States in 1900. Angus Maddison estimates that world per capita GDP at the end of the 20th century is 5 times what it was at the century’s start — and Maddison’s estimates make insufficient allowance for technological change and the invention of new commodities.

The 19th century saw perhaps a doubling of measured material standards of living in the United States — perhaps a tripling once proper account is taken of the impact of new technologies. The standard of living in the Netherlands, probably the richest economy in the world at the end of the 18th century, might (or might not) have been some 50% higher than it had been three centuries before.

Medieval historians speak of centuries and half-millennia when they speak of the pace at which key inventions diffused across the landscape.

“Cornucopia: Increasing Wealth in the Twentieth Century” by J. Bradford DeLong

During the run-up to the 2004 presidential election, while undergoing an fMRI bran scan, 30 men — half self-described as “strong” Republicans and half as “strong” Democrats — were tasked with assessing statements by both George W. Bush and John Kerry in which the candidates clearly contradicted themselves. Not surprisingly, in their assessments Republican subjects were as critical of Kerry as Democratic subjects were of Bush, yet both let their own candidate off the hook.

The neuroimaging results revealed that the part of the brain most associated with reasoning — the dorsolateral prefrontal cortex — was quiescent. Most active were the orbital frontal cortex, which is involved in the processing of emotions; the anterior cingulate, which is associated with conflict resolution; the posterior cingulate, which is concerned with making judgments about moral accountability; and — once subjects had arrived at a conclusion that made them emotionally comfortable — the ventral striatum, which is related to reward and pleasure.

Drew Weston: “We did not see any increased activation of the parts of the brain normally engaged during reasoning. What we saw instead was a network of emotion circuits lighting up, including circuits hypothesized to be involved in regulating emotion, and circuits known to be involved in resolving conflicts. Essentially, it appears as if partisans twirl the cognitive kaleidoscope until they get the conclusions they want, and then they get massively reinforced for it, with the elimination of negative emotional states and activation of positive ones.”

“The Political Brain” by Michael Shermer

If you present people with an even chance of winning $150 or losing a $100, most refuse the gamble, even though it is to their advantage to accept it. If you multiply the odds of winning — 50% — times $150, minus the odds of losing — also 50% — times $100, you end up with a gain of $25. If you accepted this bet ten times in a row, you could expect to gain $250. But, when people are presented with it once, a prospective return of $150 isn’t enough to compensate them for a possible loss of $100. In fact, most people won’t accept the gamble unless the winning stake is raised to $200.

“Mind Games” by John Cassidy

The industrial revolution fully involved only 1/3 of the world’s population. The current industrial revolution covers most of the globe.

Emerging countries’ share of world exports has jumped to 43%, from 20% in 1970. They consume over half of the world’s energy and have accounted for 4/5s of the growth in oil demand in the past 5 years. They ahold 70% of the world’s foreign-exchange reserves.

Measured at purchasing-power parity (which takes account of lower prices in poorer countries) the emerging economies now make up over half of world GDP. At market exchange rates their share is still less than 30%. But even at market exchange rates, they accounted for well over 1/2 of the increase in global output last year. China and India together made up less than 1/4 of the total increase in emerging economies’ GDP last year.

Until the late 19th century, China and India were the world’s two biggest economies. Estimates by Angus Maddison suggest that in the 18 centuries up to 1820 these economies produced, on average, 80% of world GDP. By 1950 their share had fallen to 40%. In the past 5 years, their annual growth has averaged almost 7%, its fastest pace in recorded history and well above the 2.3% growth in rich economies. The IMF forecasts that in the next five years emerging economies will grow at an average of 6.8% a year, whereas the developed economies will notch up only 2.7%. If both groups continued in this way, in 20 years’ time emerging economies would account for 2/3rds of global output (at purchasing-power parity).

Since 2000, world GDP per head has grown by an average of 3.2% a year. That would beat the 2.9% annual growth during the golden age of 1950-73. Between 1870 and 1913 world GDP per head increased by an average of only 1.3% a year.

When America and Britain were industrialising in the 19th century, they took 50 years to double their real incomes per head; today China is achieving the same feat in nine years.

The sum of China’s total exports and imports amounts to around 70% of its GDP, against only 25-30% in India or America.

Over 1/2 of the combined exports of America, the euro area and Japan go to the emerging economies. The rich economies’ trade with developing countries is growing twice as fast as their trade with one another.

As China, India and the former Soviet Union have embraced market capitalism, the global labour force has, in effect, doubled.

The integration of China and other developing countries into the world trading system is causing the biggest shift in relative prices and incomes (of labour, capital, commodities, goods and assets) for at least a century, and this, in turn, is leading to a big redistribution of income. For example, whereas prices of the labour-intensive goods that China and others export are falling, prices of the goods they import, notably oil, are rising.

Workers’ share of national income in developed countries has fallen to its lowest level for decades, whereas the share of profits has surged.

An alarming number of economic variables are currently way out of line with what conventional economic models would predict. America’s current-account deficit is at a record high, yet the dollar has remained relatively strong. Global interest rates are still historically low, despite strong growth and heavy government borrowing. Oil prices have tripled since 2002, yet global growth remains robust and inflation, though rising, is still relatively low. (House prices, however, have been soaring in many countries.)

America’s total imports from the rest of the world last year amounted to only 4% of world GDP.

“The new titans” by Pam Woodall

The Vikings of Greenland refused to eat fish, disdained the hunting techniques of the Inuit, and consumed too much wood and topsoil. As a result their colony collapsed during the 15th century and they all died.

The Easter Islanders chopped down all their palm trees and the Mayans of Central America burned their forests to build temples.

Given that America returns land to the wilderness each year, the danger from deforestation is small.

The world is not breeding too fast — birthrates are everywhere falling — and the industrial countries (except for the Anglo-Saxons) are failing to reproduce at all.

Sparta, the model of slave-based military oligarchy, had 5,000 land-owning families at the time of the Peloponnesian War, but only 700 by the third century AD after Epiminondas broke the Spartan hold over its helot population. Rome’s population fell to perhaps 100,000 during the seventh century from 1 million in the second century. Between 150 AD and 450 AD, the population of Rome’s Western empire fell by about four-fifths. Constantinople held 250,000 people in the ninth century and between 600,000 and one million during the 12th century, yet it had fallen to only 100,000 when the Turks took it, at least in 1453. After Constantinople, the world’s largest city west of the Indus, well may have been the Aztec capital Tenochtitlan. Estimates of the annual number of humans sacrificed by the Aztecs range from 20,000 to a quarter million per year.

The Romans did not so much conquer Greece as to occupy its shell; the Germanic tribes did not so much conquer Rome so much as to move into what remained of it; and the Arabs did not so much conquer the Byzantine hinterland as migrate into it.

“Why nations die” by Spengler