How Network Data Science Can Help Solve Global Inequality

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The debate over global economic inequality — including income inequality — is a data-based debate. Economists such as Branko Milanovic and Christoph Lakner argue the data shows things are getting better because more people are now above the extreme poverty line than ever before. The other side of the argument says that, although incomes have increased, the wealthy have jumped far ahead, exacerbating inequality. To provide some context, consider the following data points on global income inequality:

In 1975, developed economies had 10 times more wealth than undeveloped economies.
After the year 2000, incomes in developing countries started to increase for the lower class, decreasing inequality in those countries, while poor people’s incomes stagnated in developed countries, increasing inequality in those countries.
Overall, 71 percent of adults worldwide have less than $10,000 to their name.
The top 1 percent own 40 percent of the wealth.

Regardless of whether the poor have inched up in total median income worldwide, the fact still remains that the wealthy have outpaced them to an extraordinary degree. In 2017, the Panama Papers revealed the wealthy may be holding far more money in secret offshore tax havens than anyone realized, meaning wealth inequality could be much higher than previously estimated. There’s …

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