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SmartData Collective > Big Data > Data Visualization > By the Data: The Geography of Gender-Based Income Inequality
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By the Data: The Geography of Gender-Based Income Inequality

Josh Knauer
Josh Knauer
5 Min Read
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These days, it feels like issues relating to gender-based income gap are finally coming to the forefront. In late February, actress Patricia Arquette used the internationally televised platform of an Oscar acceptance speech to remark on wage equality. A few days later, Hillary Clinton took to the stage at the Lead On Watermark Conference for Women in Silicon Valley and gave a speech noting the pay disparities in the tech sector.  With more and more prominent women speaking out, it feels like a mainstream conversation has begun.

These days, it feels like issues relating to gender-based income gap are finally coming to the forefront. In late February, actress Patricia Arquette used the internationally televised platform of an Oscar acceptance speech to remark on wage equality. A few days later, Hillary Clinton took to the stage at the Lead On Watermark Conference for Women in Silicon Valley and gave a speech noting the pay disparities in the tech sector.  With more and more prominent women speaking out, it feels like a mainstream conversation has begun.

It got us at Rhiza wondering: will granular data tell a story not uncovered by national statistics?  And is there a way to visualize this issue from another perspective? Using data provided by Simmons Local, we decided to look at males and females making $25,000 or less annually and break down those numbers geographically. The idea was to identify regional differences across the country. Where in the country do women make the least?  And how does it compare to how men fare in the same regions?

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The resulting heat maps highlight some interesting disparities across the United States. The visualization immediately spotlights certain regions. The Southern States in particular—especially Louisiana, Mississippi and Alabama—have the highest concentration (13.5-17.17%) of women making less than $25,000 per year. By contrast, only approximately 9.00-9.4% of men in those same states fall into the same category.

What does this tell us? Aside from the glaring disparities women and men face when it comes to income, this information highlights the power of hyper-local data. Presented in a visual format, the data takes on a new form. The numbers transform into a regional story, where clusters are identified and comparisons between genders tells a geography-based tale. By looking at individual regions, states or even counties, we were able to identify micro-trends that would’ve been masked by national-only data.

Some additional points we found include:

·       New England, particularly Maine, has a very high percentage of women (12.5-13.01%) making under $25,000 annually. By comparison, 7.25-8.7% of the male population of Maine are in the same income category.

·       American men seem to do especially poorly in Southern California, Arizona and pockets of Southern Texas, all bordering on Mexico.  10.4-12.93% of these men are making under $25,000 a year.

·       Woman seem to be faring better in Colorado, Utah and Nevada.  And there’s a swath of Mid-Atlantic States, from Delaware and Maryland in the south up to New Hampshire in the north, where female workers hold their own and only 9.8-11.5% of women make under $25,000 per year.

·       Both Washington State and Idaho boast relatively small under-$25,000 populations, among both women and men.

These regional insights can be gleaned from just a glance at a heat map. And while this granular data cannot necessarily deduce if the factors causing income disparity are policy-related, cultural, environmental or sociological, it does expose interesting patterns that are worth digging into deeper. By looking at income data by DMA and via a heat map, we can quickly understand the big picture (and even some brush strokes), as the issue of gender-based income disparity reaches a tipping point in the American consciousness.


Josh Knauer is president and CEO of Rhiza, an online platform pioneering the way marketers and salespeople make Big Data actionable.

 

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