Inequality growth in the U.S.

Andrey Kamenov

Andrey Kamenov, Ph.D. Probability and Statistics

Inequality growth in the United States has been relatively stable for at least the last 50 years. There are multiple way to measure the growth, but the most well-known seems to be the Gini coefficient. Calculated using the area under the income distribution curve, it shows the difference between the given income distribution and one where everybody receives the same income.

While the value of the Gini coefficient doesn’t mean much by itself, it allows us to compare different populations and examine how the coefficient has changed through time.

Speaking of which, the U.S. index value has been rising by roughly 1 percent per decade for nearly as long as the observations have been available. But let’s focus on the recent years – is the inequality the same in every state?

Gini coefficient in the U.S. by state

The chart shows some interesting patterns:

  • California, Illinois and New York have some of the largest income inequality values for both genders.
  • Lower-than-average values are observed for women living in the southeastern states.
  • Virginia, Oregon and Wyoming are the only states where Gini coefficient values are actually lower for men.

Finally, let's see how the index values have changed during the recent years. The following chart compares the aggregate values for the two consecutive year ranges:

Inequality growth by state

The chart shows that the income distribution dynamics is in reality much more complex than seen on the charts for the entire nation. While California and New York have shown an increase that is just above average, inequality growth was negative in Texas and Florida.

What about your state?


  • [Feng et al, 2006] Feng, S., R.V. Burkhauser and J.S. Butler, 2006, Levels and long-term trends in earnings inequality: overcoming Current Population Survey censoring problems using the GB2 distribution, Journal of Business and Economic Statistics 24, 57–62.


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About Andrey Kamenov

Andrey Kamenov

Andrey Kamenov, Ph.D. Probability and Statistics

Andrey Kamenov is a data scientist working for Advameg Inc. His background includes teaching statistics, stochastic processes and financial mathematics in Moscow State University and working for a hedge fund. His academic interests range from statistical data analysis to optimal stopping theory. Andrey also enjoys his hobbies of photography, reading and powerlifting.

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