1 Introduction

In this work we analyse how some socioeconomic characteristics relate to the results of the 2008, 2012 and 2016 US presidential elections at county level. The socioeconomic variables that we take into account are associated to the income, the ethnicity, the level of education, and the health access of the population. Three hypotheses are studied in this work, for which two regression models are proposed. The hypotheses are that (i) on average, counties that share similar socioeconomic characteristics have a similar voting behaviour; (ii) for a given county, deviations of its socioeconomic variables from their mean strengthen (or weaken) the correlation with the election results; and that (iii) the way in which the socioeconomic variables relate to the voting behaviour has changed from election to election.

The most relevant findings are that the variables that related in favour of the GOP, are the percentage of white population, the median household income, and the percentage of uninsured population; and the variables related against the GOP are the population density, the unemployment rate, the gini index and the percentage of population with college or more. For a given county, we found that a positive change in the population density and in the median household income (the rest constant) implied that the GOP received proportionally less votes. Also, compared to the 2008 elections, in the 2016 elections the population density and the percentage of population with college degree weighted more against the GOP in 2016. Similarly, the variables percentage of white people, the mean household income and the percentage of uninsured people weighted more in favour of the GOP, which can be interpreted as an increasingly polarized population.

2 Socioeconomic variables

The unit that we use for the analysis is the county. For each county, we have measures of seven socioeconomic variables for the years 2007, 2011 and 2015. These are the years previous to the presidential elections in 2008 and 2012, won by Obama; and 2016, won by by Trump. Also, for each county, we have the results of the three presidential elections, which we will relate to the socioeconomic variables measured in the previous year. For simplicity of exposition, we only refer to the years 2008, 2012 and 2016 in this work, with the understanding that the socioeconomic variables were measured in the years 2007, 2011 and 2015. The variables that we consider in this work are listed below.

Variable Range Description
density \(\mathbb{R}\) Population density in the county
perc_gop [0,1] Percentage of the population that voted for the republican party (GOP)
pop_perc_white_nh [0,1] Percentage of the population that belongs to the white (non hispanic) ethnic group
eco_unemp_rate [0,1] Unemployment rate
eco_med_income \(\mathbb{R}\) Median household income
eco_gini [0,1] Gini index. A measure of income inequality, where 0 is no inequality and 1 is extreme inequality
edu_perc_college_and_more [0,1] Percentage of the population of 25 years old and over that has a college degree or higher
hc_perc_unins [0,1] Percentage of the population that has not a health insurance

The data of socioeconomical variables used in this work come from the United Stated Census Bureu’s American Community Survey (ACS) for the years 2007, 2011 and 2015. The 1-year estimates of the ACS are used1. The number of counties in the data is 788, 811 and 819, respectively for for the three years, which correspond to the ones with more than 65,000 inhabitants2. The county level election results come from the Github page of tonmcg.

2.1 Population density

Comparing the population density with the percentage of votes that the GOP received in the past three elections we observe a negative correlation: the more dense the counties, the more less proportion of vote the GOP received. If we regard the density of population as an indicator of the level of urbanization, we can assert that more urbanized counties voted less (proportionally) for the GOP.

2.2 Ethnicity

We compare the percentage of white (non hispanic) people vs the proportion of votes received by the GOP in the three years. In the three elections we observe a general trend: the more white the population is in a county, the more proportion of votes that the GOP received. For counties with less than 50% of white population the trends are similar for the three years. For counties where more than 50% of the population is white, the percentage of votes for the GOP is greater in 2012 and 2016 than in 2008. But, interestingly, in the 2016 elections the trend changes in counties with highly predominant white population (\(>85\%\)): they voted more, proportionally, for the GOP than in previous years. Another interesting fact is that, in general, the counties with high population densities are more diverse.