The science of inequality (Special Issue of Science magazine)

Posted: 2014/06/02 by Punkonomics (@dearbalak) in Links/Articles/Video
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Science 23 May 2014: 
Vol. 344 no. 6186 pp. 818-821 
DOI: 10.1126/science.344.6186.818



What the numbers tell us

Gilbert Chin,
Elizabeth Culotta
Gilbert Chin is a senior editor for Science and Elizabeth Culotta is a deputy news editor for Science.

In 2011, the wrath of the 99% kindled Occupy movements around the world. The protests petered out, but in their wake an international conversation about inequality has arisen, with tens of thousands of speeches, articles, and blogs engaging everyone from President Barack Obama on down. Ideology and emotion drive much of the debate. But increasingly, the discussion is sustained by a tide of new data on the gulf between rich and poor.

This special issue uses these fresh waves of data to explore the origins, impact, and future of inequality around the world. Archaeological and ethnographic data are revealing how inequality got its start in our ancestors (see pp. 822 and 824). New surveys of emerging economies offer more reliable estimates of people’s incomes and how they change as countries develop (see p. 832). And in the past decade in developed capitalist nations, intensive effort and interdisciplinary collaborations have produced large data sets, including the compilation of a century of income data and two centuries of wealth data into the World Top Incomes Database (WTID) (see p. 826 and Piketty and Saez, p. 838).

It is only a slight exaggeration to liken the potential usefulness of this and other big data sets to the enormous benefits of the Human Genome Project. Researchers now have larger sample sizes and more parameters to work with, and they are also better able to detect patterns in the flood of data. Collecting data, organizing it, developing methods of analysis, extracting causal inferences, formulating hypotheses—all of this is the stuff of science and is more possible with economic data than ever before. Even physicists have jumped into the game, arguing that physical laws may help explain why inequality seems so intractable (see p. 828).


In the United States, the new information suggests a wide rift between top and bottom. Tax data from the WTID suggest that today the top 1% control nearly 20% of U.S. income, up from about 8% in the 1970s. But inequality is increasing within the 99%, too, as a consequence of a growing premium on college and postgraduate education: The fates of the tech-savvy worker at Google and the blue-collar employee at General Motors have been decoupled (see Autor, p. 843). According to surveys by the Census Bureau, in 2012 the richest 20% of Americans enjoyed more than 50% of the nation’s total income, up from 43% in 1967. The middle 20%—the actual middle class—received only about 14% of all income, and the poorest got a mere 3% (see p. 820).

Flip to a world map, and America’s inequality, despite reaching levels last seen in the Gilded Age, turns out to be far from extreme. Many nations, especially emerging economies, have even larger chasms between the super-rich and the poor. One widely used metric, the Gini coefficient, estimates inequality as an index between 0—at which point everyone has exactly equal incomes—to 1, in which a single person takes all the income and the rest get nothing. The U.S. Gini, at 0.40 in 2010, seems relatively high compared with, for example, Japan at 0.32. But South Africa is a sky-high 0.7.

Many assume that governments in emerging economies have chosen to favor growth even at the cost of inequality on the grounds that “a rising tide lifts all boats.” But evidence that this trade-off is necessary is sparse, and recent data show that policies to reduce inequality need not stymie growth (see Ravallion, p. 851).

What of those at the bottom? Research has established a base of knowledge about the harmful effects of disadvantageous circumstances on education and health. These influences can begin early in life, even prenatally (see Aizer and Currie, p. 856). But researchers are still exploring whether the stress of being low-ranked itself adds to the poor’s burden, causing illness and even early death (see p. 829). In addition, psychological mechanisms may spur a negative feedback loop in which poor individuals behave in ways that help keep them poor (see Haushofer and Fehr, p. 862).

Harsh as life can be for those at the bottom, the opportunity to move up the ladder can compensate. Newly available data from taxes and other records promise to yield insights into intergenerational mobility, in which children advance from their parents’ socioeconomic status. But so far, researchers have a relatively limited view of how and why people move into different social, as well as economic, classes (see p. 836 and; also see Corak, p. 812).

Few would deny that excessive inequality can be unhealthy for societies and economies, but the new data don’t pinpoint a desirable level. They do show that the forces that foster inequality—from the patchy distribution of resources among ancient hunter-gatherers to the sheer earning power of capital today—are many and potent. It is up to society to decide whether, and how, to restrain them (see p. 783).

  1. Suzanne says:

    Hi there, the whole thing is going fine here
    and ofcourse every one is sharing data, that’s actually excellent,
    keep up writing.


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