The Electoral Map is Completely Upside Down

Johannes Moenius Analysis, Employment, Income & Wealth, Reports 2 Comments

An international observer not familiar with the specifics of the U.S. political system might think that the more left-leaning party, the Democrats, would be especially popular with less fortunate economic groups. Consequently, Hillary Clinton, as the presidential candidate of the Democratic Party, should have been most successful in areas where more poor people live. This means that poor areas should be blue (Democrats), and rich areas should be red (Republicans). However, this is not what we observe in the actual election results by county:

Source: https://www.washingtonpost.com/2016-election-results/us-presidential-race/?hpid=hp_hp-bignews4_map-promo%3Ahomepage%2Fstory, retrieved 11/9/2016

Compare this map to a study that we completed a few years ago, already then titled, “The U.S. as a Tale of Two Countries: the Rich and the Poor”. As compared to the U.S. average, the golden color identifies areas where a higher share of high income earners lives, and the purple color identifies areas where a higher share of poor people lives:

Juxtaposing the two maps reveals that it was the Republicans who won in the poor areas, and the Democrats who won in the rich areas (the exact opposite of what an international observer would expect.) This highlights the problem that Bernie Sanders pointed out in the New York Times, namely that the Democratic Party should “[] become a grass-roots party of working people, the elderly and the poor.” Even more astounding is that the fact that the red-blue pattern of counties won has not substantially changed over the last few elections.

Author: Johannes Moenius, Ph.D.
Institute for Spatial Economic Analysis,
University of Redlands, School of Business

Contact: Johannes Moenius, Ph.D., isea@redlands.edu, 909-557-8161
Director, Institute for Spatial Economic Analysis,
University of Redlands, School of Business

Comments 2

    1. Post
      Author

      Philip, I think he is definitely on the right track. However, he does not show us the entire analysis, only the extremes. But his story is pretty convincing. Some regression analysis would have been nice to complement his work and control for diversity as well as other factors. But yes, generally I do agree that education was a key driver.

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