Progress Daily

A series of experiments by Kees Keizer, Siegwart Lindenberg, & Linda Steg (”The Spreading of Disorder“; methodology .pdf file here) suggest that signs of vandalism, litter and low-level lawbreaking increase the number of people who are prepared to litter and steal.

The first experiment was conducted in an alley that is frequently used to park bicycles. The researchers created two conditions: one of order and the other of disorder. In the former, the walls of the alley were freshly painted; in the latter, they were tagged with amateurish graffiti. In both states a large sign prohibiting graffiti was put up. All the bikes then had a flyer promoting a non-existent sports shop attached to their handlebars. This needed to be removed before a bicycle could be ridden.

There were no rubbish bins in the alley, so a cyclist could take the flyer with him, hang it on another bicycle or throw it to the floor. When the alley contained graffiti, 69% of the riders littered compared with 33% when the walls were clean.

In a 2nd experiment, a temporary fence was used to close off a short cut to a car park, except for a narrow gap. Two signs were erected, one telling people there was no throughway and the other saying that bicycles must not be left locked to the fence. In the “order” condition (with 4 bicycles parked nearby, but not locked to the fence) 27% of people were prepared to trespass by stepping through the gap, whereas in the disorder condition (with the 4 bikes locked to the fence) 82% took the short cut.

It is against the law to let off fireworks in the Netherlands for several weeks before New Year’s Eve. In the 3rd experiment, 2 weeks before the festival, the researchers randomly let off firecrackers near a bicycle shed at a main railway station. With no fireworks, 48% of people took the flyers with them when they collected their bikes. With fireworks, 20%.

In the final experiment, an envelope with a €5 ($6) note inside (and the note clearly visible through the address window) was left sticking out of a mailbox. In a condition of order, 13% of those passing took the envelope. But if the post box was covered in graffiti, 27% did. When the mailbox had no graffiti on it, but the area around it was littered with paper, orange peel, cigarette butts and empty cans, 25% still took the envelope.

“Can the can,” The Economist

Discrimination arising from the prejudices of employers (though not of customers or workers) is economically inefficient, yet racial discrimination persists. For example, the work of Marianne Bertrand & Sendhil Mullainathan (”Are Emily and Greg More Employable than Lakisha and Jamal?” — .pdf file here) suggests that US firms are about a third less likely to interview a person with a recognizably “black” name.

New research by Ross Levine & Yona Rubinstein (”Racial Discrimination and Competition”; .pdf file here) suggests that the liberalization of US banking markets, between the mid-1970s and 1994, indirectly reduced the wage gap between blacks and whites.

Before the mid-1970s most US states had laws preventing banks incorporated in one place from opening branches in other states. This decreased competition and created a localized banking industry, in which many customers had access to only one bank. From then onwards, technological and legal changes increased competition in the industry, which led to lower overheads and lower interest rates on loans, which eased business financing, which increased the number of start-ups, which increased competition throughout the economy.

Using the tide of bank deregulation, the researchers were able to identify whether this made a difference to the racial wage gap. To compare the degree of pre-existing racial bias across states, the researchers contrasted their rates of interracial marriage with what would result if people were randomly matched to partners.

They found that the black-white wage gap declined the most in states with an initially high degree of racial bias. For high-bias states, about 22% of the racial gap was competed away, and black workers reported more hours of work and higher wages, after bank deregulation. There was little change in states with a low degree of racial bias before deregulation.

“Race and red tape,” The Economist

America, Britain, the euro area and Japan are probably in recession according to the popular rule of thumb of two successive quarters of falling GDP.

In an updated World Economic Outlook, published on November 6th, the IMF predicted that world GDP growth would fall to 2.2% in 2009, based on purchasing-power parity (PPP) weights, from 5% in 2007 and 3.7% in 2008.

Global GDP has not fallen in any year since the 1930s Depression. Its worst years since then were 1982 and 1991, with growth of 0.9% and 1.5% respectively.

The IMF suggests that a sufficient (although not necessary) condition for a global recession is any year in which world GDP per head declines. In each of the downturns in 1975, 1982 and 1991, growth in world GDP per head turned negative. In 2001, global GDP per head expanded by around 1%. The annual growth rate in world population has now slowed to 1.2%, so recent GDP forecasts would still allow average world income per head to rise.

The IMF forecasts that the advanced economies will shrink by 0.3% in 2009, which would be the first annual contraction since World War II. Emerging economies are expected to grow by around 5%.

Real income per head is expected to increase next year in countries that account for well over half of the world’s population. If the developed world does suffer an absolute decline, then 2009 would be the first year on record when emerging economies account for more than 100% of world growth.

“The global slumpometer,” The Economist

Over the past 30 years, the world’s urban population has risen from 1.6 billion to 3.3 billion, and over the next 30 years cities in the developing world are set to grow by an extra 2 billion.

 The World Bank’s 2009 World Development Report analyzed this boom.

Today’s cities are unprecedented in size. Mexico City, Mumbai, São Paulo and Shanghai each have over 15m people, whereas Paris and London, after their surge in the 19th century, had less than half that. The average population of the world’s 100 largest cities now exceeds 6m. In 1900, it was only 700,000. But relative to the size of countries’ populations, the current growth is not unusual. Between 1985 and 2005 the urban share of the population of developing countries rose by eight percentage points. Between 1880 and 1900 the urban share in then-industrialising Europe and America went up by about the same amount.

The population of boom cities has tended to follow a pattern: rapid population growth until city-dwellers make up about a quarter of their countries’ population, then stabilization when the country’s income hits about $5,000 per person. This roughly tracks the transition from an agricultural to an industrial base. Many countries are undergoing that sort of transition now, and therefore urbanization is accelerating — temporarily.

As people have moved to the city, urban wages have been typically 40-50% higher than unskilled farm earnings (that was the premium in Europe in the 19th century; it is about the same in developing countries today). But the income gaps of rich countries have narrowed, so living standards in the West today are roughly the same between town and country. That convergence has recently begun in poor countries.

“Lump together and like it,” The Economist

According to The World Economy by Angus Maddison, Gross Word Product (GWP) grew by about 0.1% a year between 1000 and 1500; 0.3% a year between 1500 and 1820; 1% a year between 1820 and 1870; 2% a year between 1870 and 1950; 5% a year between 1950 and 1973; and 3% a year between 1973 and 1998.

“Can Gross World Product Shrink?,” by Felix Salmon

Matthew Gentzkow and Jesse Shapiro analyzed media bias (”What Drives Media Slant? Evidence from U.S. Daily Newspapers”; pdf file here).

By running computer programs of debates in Congress, they identified phrases that were disproportionately used by Republicans or Democrats — for example “death tax” vs “estate tax.” The researchers then calculated the “slant” of 400+ US newspapers, based on their use of these terms.

They then assessed the political beliefs of different newspapers’ readerships, using 2004 presidential election data and political contribution data.

The political slant of the newspapers tended to match very closely that of their readers.

The researchers then tried to determine whether ownership or demand determines bias. Since large media companies sometimes own several newspapers, and often in markets that are politically very different, they could test whether the slants of newspapers with the same owner were more strongly correlated than those of two newspapers picked at random. They found that this was not so: readers’ political views explained about a fifth of measured slant, while ownership explained almost none.

“A biased market,” The Economist

Ara Norenzayan and Azim Shariff (”The Origin and Evolution of Religious Prosociality“; .pdf file here) analyzed 3 decades of empirical evidence looking for examples of religious prosociality (”the idea that religions facilitate acts that benefit others at a personal cost”). They found that religion encourages prosociality because the sense of being watched makes believers nervous about being selfish.

A study by Melissa Bateson & Gilbert Roberts (”Cues of being watched enhance cooperation in a real-world setting”; .pdf file here) found that just being under the gaze of eyes on a poster nearly tripled the contributions to an office coffee kitty.

Exposing participants in a laboratory economic game by Daniel Fessler to computer-generated eyespots while they played made them twice as generous as those who were not (”Nobody’s watching? Subtle cues affect generosity in an anonymous economic game“).

A study by Kevin McCabe & Vernon Smith found that participants in a laboratory economic game were nearly 4 times stingier with other players when they thought they were anonymous than when they thought they were being observed (”Social Distance and Other-Regarding Behavior in Dictator Games”; .pdf file here).

In an experiment by Richard Sosis and Bradley Ruffle (”Religious Ritual and Cooperation: Testing for a Relationship on Israeli Religious and Secular Kibbutzim”; .pdf file here), two players would simultaneously decide how much money to withdraw from the same envelope — if their combined withdrawals exceeded the amount in the envelope, neither would get any money. Systematically, less money was withdrawn when the game was played at religious kibbutzim than when it was played at secular kibbutzim.

In a 1989 study (Religious prosocial motivation: Is it altruistic or egoistic?“), volunteers were given the option to raise money for a sick child’s medical bills. Some would-be volunteers were told that it was very likely that they would be asked to help, while others were told that there was only a small chance that they would be called on. Only in the latter situation was a link between religiosity and volunteering evident. Religion played a role when it appeared that volunteering would improve one’s reputation without much personal cost.

In an experiment by Jesse Bering (”The Cognitive Psychology of Belief in the Supernatural“), when participants were told that the ghost of a dead student was haunting the experimental room, they cheated less on a computer test.

Brandon Randolph-Seng & Michael Nielsen report (”Honesty: One Effect of Primed Religious Representations“) that when experimental subjects were primed with religious words, they cheated significantly less on a subsequent task.

A cross-cultural analysis of 186 societies (”Belief in moralizing gods”; .pdf file here) by Frans Roes suggests that the larger a society, the more likely its members believe in deities that are concerned about human morality. In small hunter-gatherer bands or subsistence farming villages, it’s easy to keep track of how cooperative your neighbors are. But when groups grow, an all-seeing deity may help watch and punish.

“Does Religion Make People Nicer?” by Ronald Bailey

 Genes that make some people gay may make their siblings fecund.

Homosexuality is at least partly genetic. Studies of identical twins, for example, show that if one of a pair (regardless of sex) is homosexual, the other has a 50% chance of being so, too. How could a trait so at odds with reproductive success survive natural selection?

Brendan Zietsch, of the QIMR, thinks that genes which cause men to be more feminine in appearance, outlook and behavior and those that make women more masculine in those attributes, confer reproductive advantages as long as they do not push the individual possessing them all the way to homosexuality.

Gay men tend to rank higher than straight men in standardised tests for agreeableness, expressiveness, conscientiousness, openness to experience and neuroticism. Lesbians tend to be more assertive and less neurotic than straight women.

Though women prefer traditionally macho men at the time in their menstrual cycles when they are most fertile, at other times they are more attracted to those with feminine traits such as tenderness, considerateness and kindness, as well as those with feminised faces. This suggests that women prefer macho men for breeding but the more feminised phenotype for carers and providers (husbands). And husbands father most of the world’s children.

Zietsch’s researchers asked 4,900 individual twins, not all of them identical, to fill out anonymous questionnaires about their sexual orientation, their gender self-identification and the number of opposite-sex partners they had had during the course of their lives.

They found that the more feminine a man, the more masculine a woman, the higher the hit rate with the opposite sex — though women of all gender identities reported fewer partners than men did (which may reflect male boasting &/or female bashfulness).

Heterosexuals with a homosexual twin tend to have more sexual partners than heterosexuals with a heterosexual twin. The researchers then analyzed the relationships between twins (all genes in common for identical twins; a 50% overlap for the non-identical) and calculated that genes explain 27% of an individual’s gender identity and 59% of the variation in the number of sexual partners. (They also calculated that the genetic component of sexual orientation was 47% — similar to previous studies

“Gender bending,” The Economist