Political Pivots and Boomerangs

CLASS PROJECT: Robin Johnson (in back in center) poses with the students in his "Midwestern Politics" class, which did a deep dive into key counties in the 2020 presidential election.MONMOUTH, Ill. – A project by a Monmouth College political science class could offer early insight into the shape of the political landscape for the 2022 and 2024 general elections.

Students in political science lecturer Robin Johnson’s “Midwestern Politics” class examined two dozen of the more than 200 U.S. counties that were key factors in the 2016 and 2020 presidential elections. The students’ research found that while President Joe Biden impressively “boomeranged” enough of those counties to win the White House in 2020, Democrats could face several stiff challenges in 2022 and 2024.

In presidential elections, many U.S. counties vote for the same party every four years, but the nation also has about 206 of what Johnson calls “pivot counties” – mostly Midwestern counties that voted for Democrat Barack Obama in 2008 and 2012, then for Republican Donald Trump in 2016.

“We wanted to see how those pivot counties voted in the 2020 presidential election,” said Johnson. “Specifically, students in small groups were assigned two counties each – one that voted Trump (retained pivot) or one that switched back to (Democrat) Joe Biden in 2020 (boomerang counties).”

The students used demographic, economic, political and other data to determine why those counties diverged.

“We wanted to see how those pivot counties voted in the 2020 presidential election. Specifically, students in small groups were assigned two counties each – one that voted Trump or one that switched back to Joe Biden in 2020.” – Robin Johnson

The students found that Trump demonstrated strength in several voter categories: among voters 65 and older, white, non-Hispanics, and those with manufacturing jobs.

Biden’s support was strongest among foreign-born residents and those who spoke a language other than English; those who owned computers and had broadband; college-educated voters; and voters with higher median household incomes.

‘What going to Monmouth is all about’

“To be able to be involved in a project like this is pretty cool,” said C.J. Bonifer ’22 of Columbia, Kentucky. “I’m a public relations major, and being part of a cross-disciplinary project and class like this one is what going to Monmouth is all about.”

Bonifer teamed on the project with Riley Dulin ’22 of Monmouth, an accounting major.

“Being part of a cross-disciplinary project and class like this one is what going to Monmouth is all about.” – C.J. Bonifer

“While we were doing the data analysis in Excel, Riley was in his element, and when it came to telling the story of the data, that’s where I came in,” said Bonifer. “The data really speaks for itself, in my opinion.”

Johnson said that “most data categories had lopsided winners and only one was tied, highlighting the partisanship that splits the nation in most demographic groupings.”

Johnson said there are signs in the students’ research that point to a Republican advantage.

“Trump retained most pivot counties by large margins and appears likely to hold them into the future,” he said. “Biden barely won most pivot counties he ‘boomeranged,’ and his grip on them is likely tenuous into the future.”

In the 24 pivot counties that Johnson’s students examined, Trump’s average winning margin was 11.8% and Biden’s was 2.5%. Biden’s winning margin in seven of the 12 counties was less than 2%, while the margin of just two Trump counties was under 2%.

Midwest was a ‘pivotal’ region

Most of the pivot counties (55%) are located in the Midwest region. In 2020, the overwhelming majority of pivot counties (88%) were won by Trump, with Biden winning only 25 (11, or 44%, of his wins were in the Midwest).

“With 21 students in my class, the definition of the Midwest was expanded to include Pennsylvania, which is also a crucial state included in the ‘Blue Wall’ of Democratic states that were won by Trump in 2016, along with Wisconsin and Michigan,” said Johnson.

The students’ research included Knox County in Illinois, which neighbors Monmouth’s Warren County. States with multiple counties assigned included Michigan, Minnesota, Ohio, Pennsylvania, South Dakota and Wisconsin.

“The more diverse a county was, it was expected to vote for Biden. The older the average age, the more likely it would be to vote for Trump.” – Robin Johnson

Once the pairings of counties were assigned, students were given a variety of sources to explore why the two counties diverged in their voting, including U.S. Census Quickfacts, the American Communities Project and exit polling. Students gathered the data into a spreadsheet and gave presentations on their findings. They also submitted papers on the reasons for the different outcomes in their assigned counties.

“Students aggregated the data from each category from all 12 county pairings,” said Johnson. “For example, the more diverse a county was, it was expected to vote for Biden. The older the average age, the more likely it would be to vote for Trump. The class measured the outcome across all demographic and economic categories to determine which factors had the highest level of predictability for the winner.”

“I looked at Montgomery County, Ohio, which was a pivot county in 2020, voting for Biden by 2 points,” said Bonifer. “The 2016 election was a real shock, though, given the county’s voting history, as it has been a Democratic county historically. Ultimately, the reason for the swing back to Democrat in 2020 was, from my point of view, pandemic fatigue, given that the industry with the highest employment in the county is medical care.”