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Measure content performance. Develop and improve products. List of Partners vendors. A Lorenz curve is a graphical representation of income inequality or wealth inequality developed by American economist Max Lorenz in The graph plots percentiles of the population on the horizontal axis according to income or wealth.
It plots cumulative income or wealth on the vertical axis, so that an x-value of 45 and a y-value of In practice, a Lorenz curve is usually a mathematical function estimated from an incomplete set of observations of income or wealth. The Lorenz curve is often accompanied by a straight diagonal line with a slope of 1, which represents perfect equality in income or wealth distribution; the Lorenz curve lies beneath it, showing the observed or estimated distribution. The area between the straight line and the curved line, expressed as a ratio of the area under the straight line, is the Gini coefficient , a scalar measurement of inequality.
While the Lorenz curve is most often used to represent economic inequality, it can also demonstrate unequal distribution in any system. The farther away the curve is from the baseline, represented by the straight diagonal line, the higher the level of inequality. In economics, the Lorenz curve denotes inequality in the distribution of either wealth or income; these are not synonymous since it is possible to have high earnings but zero or negative net worth , or low earnings but a large net worth.
A Lorenz curve usually starts with an empirical measurement of wealth or income distribution across a population based on data such as tax returns which report income for a large portion of the population. A graph of the data may be used directly as a Lorenz curve, or economists and statisticians may fit a curve that represents a continuous function to fill in any gaps in the observed data.
A Lorenz curve gives more detailed information about the exact distribution of wealth or income across a population than summary statistics such as the Gini coefficient or the Lorenz asymmetry coefficient. Because a Lorenz curve visually displays the distribution across each percentile or other unit breakdown , it can show precisely at which income or wealth percentiles the observed distribution varies from the line of equality and by how much.
However, because constructing a Lorenz curve involves fitting a continuous function to some incomplete set of data, there is no guarantee that the values along a Lorenz curve other than those actually observed in the data actually correspond to the true distributions of income. Most of the points along the curve are just guesses based on the shape of the curve that best fits the observed data points. So the shape of the Lorenz curve can be sensitive to the quality and sample size of the data and to the mathematical assumptions and judgments as to what constitutes a best-fit curve, and these may represent sources of substantial error between the Lorenz curve and the actual distribution.
The Gini coefficient is used to express the extent of inequality in a single figure. Complete equality, in which every individual has the exact same income or wealth, corresponds to a coefficient of 0. Plotted as a Lorenz curve, complete equality would be a straight diagonal line with a slope of 1 the area between this curve and itself is 0, so the Gini coefficient is 0. A coefficient of 1 means that one person earns all of the income or holds all of the wealth. Accounting for negative wealth or income, the figure can theoretically be higher than 1; in that case, the Lorenz curve would dip below the horizontal axis.
The curve above shows a continuous Lorenz curve that has been fitted to the data that describe the income distribution in Brazil in , compared to a straight diagonal line representing perfect equality. At the 55th income percentile, the value of the Lorenz curve is The 99th percentile corresponds to To find the approximate Gini coefficient, subtract the area beneath the Lorenz curve around 0. Divide the result by the area beneath the line of perfect equality, which yields a coefficient of around 0.
According to the World Bank, Brazil's Gini coefficient in was World Bank. Financial Ratios. Tools for Fundamental Analysis. Your Privacy Rights. To change or withdraw your consent choices for Investopedia. At any time, you can update your settings through the "EU Privacy" link at the bottom of any page. These choices will be signaled globally to our partners and will not affect browsing data.
Because work looms so large in our lives I believe that most of us don't reflect on its importance and significance. For most of us, work is well — work, something we have to do to maintain our lives and pay the bills. I believe, however, that work is not just a part of our existence that can be easily separated from the rest of our lives. Work is not simply about the trading of labor for dollars. Perhaps because we We need work, and as adults we find identity and are identified by the work we do.
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We may worry too much about good versus evil - big concepts that give us plenty of room to sit on the right side of the equation, he argues. Instead, we need to be thinking about how being good involves an active relationship toward others.
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Humor, joke telling, can serve as a narrative playlet to metaphorically illuminate a complex philosophical concept.
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