Special report: The world economy
特别报告：世界经济
Like a piece of string
度量穷富差别的基尼系数
Sizing the gap
ECONOMIC INEQUALITY CAN be measured in many ways—by the distribution of wealth, income or consumption, or between races, sexes, regions or individuals. The resulting picture can vary a lot. In America, for instance, the income gap between blacks and whites, and men and women, has narrowed over the past 30 years, even as that between individuals has widened. Disparities in consumption are always smaller than those in income because people save and borrow to smooth their living standards. The distribution of wealth is usually less equal than that of annual incomes. Gaps in pre-tax income are larger than those in disposable income after taxes and government transfers.
经济不均等可以从多个角度来度量，如财富、收入和消费的差别，或者是种族、性别、地区、个人之间的差别。度量的结果往往千差万别。例如，美国的黑人和白人之间、男女之间的收入差别在过去三十年中是缩小的趋势，即便在同期中个人之间的收入差别有所扩大。消费差别总是小于收入差别，因为人们通过储蓄和借贷的办法来减少自己生活水准的波动。财富的分配通常比年收入的分配更为不均等。税前收入的差别比政府税收和转移支付之后的可支配收入差别要大。
The main measures of economic inequality used in this special report are the Gini coefficients for disposable income and consumption derived from household surveys. These surveys are now conducted in almost all countries. In the rich world and in Latin America, official Gini coefficients are usually based on income. In Asia and Africa consumption-based figures are more common.
在我们这个特别报告中，从家庭调查中获得的可支配收入和消费的基尼系数是衡量经济不均等的主要指标。目前几乎所有国家都在进行这种家庭调查。在富裕国家和拉美国家，官方的基尼系数通常是根据收入计算的；而在亚洲和非洲，以消费为依据的基尼系数更为常见。
Cross-country comparisons can be tricky. Inequality in India, for instance, is often said to be lower than in China. But China’s Gini coefficient of 0.48 measures inequality of income, whereas India’s official Gini of 0.33 measures consumption. Peter Lanjouw and Rinku Murgai of the World Bank calculated an income Gini for India which, at 0.54, is much higher than China’s and close to Brazil’s.
不同国家之间的比较可能并不准确。比如，人们常常说印度的经济不均等程度比中国低，但中国0.48的基尼系数衡量的是收入不均等，而印度0.33的官方基尼系数衡量的是消费。根据世界银行的皮特-兰舟和林库-莫尔盖的计算，印度的收入基尼系数是0.54，大大高于中国，和巴西接近。
Another problem is that there are several international databases, all slightly different. Nor are household surveys good at capturing inequality at the very top, not least because it is all but impossible to get the ultra-rich to take part in them. The best information on the highest incomes comes from tax returns, thanks to work pioneered by two French economists, Emmanuel Saez and Thomas Piketty, together with a Briton, Anthony Atkinson, and an Argentine, Facundo Alvaredo. These four have built a huge database of top incomes which now includes 26 countries. Their statistics go back much further than household surveys (in America’s case, to 1913).
另一个问题是，存在着好几个家庭调查的国际数据库，但它们的数据都各有一些差别。而且，这些家庭调查关于高收入人群的数据都很不可靠，很大原因是，几乎不可能让那些超级富豪接受调查。对于这些超高收入的人群，最靠得住的信息来自他们的缴税纪录。在这方面，两个法国经济学家（伊曼努尔-赛兹和汤姆斯-皮克蒂）与英国的安托尼-阿金森和阿根廷的法坤多-阿尔瓦利多做出了开创性的贡献，这四个人建立了一个现在包括26个国家的高收入人群的庞大的数据库。他们的统计资料比家庭调查涵盖的年代要久远得多（如美国的资料早自1913年）
Gini coefficients and the top income share can paint different pictures. Argentina’s Gini, for instance, has fallen sharply over the past decade even as the share of income going to the top 1% has risen. Germany’s Gini has risen by 32% since the early 1980s, but the share of income going to the very top has barely budged. One reason is that the statistics cover different people; another is arithmetic. The Gini aggregates all disparities, so it is a better summary measure, but it does not tell you where the gaps are growing.
基尼系数和高收入人群所占份额可能会给出不同的图景。例如，在过去十年中，阿根廷的基尼系数大幅下降，但同期中最富的1%的人群的收入份额却在增长；德国的基尼系数自1980年以来增长了32%，但同期中最富人群的收入份额却没有什么变化。其原因之一是不同的统计涵盖了不同的对象人群；原因之二是算数上的问题。因为基尼系数涵盖了所有阶层的收入差别，所以我们最好把它看作一个总体的概括性指标，它难以告诉我们差别是从哪里产生的。
网络
2012-10-17
经济学家
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