What Happened in Ohio

Adam Martin
The Book Aisle
Published in
25 min readJan 6, 2021


This is the fourth part in my 2020 election analysis series and this should be an interesting one. Ohio is the first of a couple states that I did not get to talk about in my pre-election series. But given how close it was and the compelling story behind it, I couldn’t ignore the Buckeye State forever. Now because I didn’t talk about it before, I’ll be spending a little more time on each subsection and describe their basic demographic and socioeconomic breakdown, much like what I did in my pre-election series. Still, I think this discussion is worth having.

With that said, let’s dive in.

Big Picture

Joe Biden- 2,679,165 (45.24 percent, up 1.68 percent from Clinton in 2016)

Donald Trump- 3,154,834 (53.27 percent, up 1.58 percent from 2016)

FiveThirtyEight Projection- 49.2 for Biden (up 3.96), 49.8 for Trump (down 3.47)

RCP Average- 46.3 for Biden (up 1.06), 47.3 for Trump (down 5.97)

OurProgress Projection- 48.49 for Biden (up 3.25), 48.56 for Trump (down 4.71)

Now things are starting to get interesting. Ohio is another Rust Belt state, sandwiched between Michigan and Pennsylvania, but it has largely followed its own path when it comes to presidential elections. While it’s regularly considered a swing state, it has been a consistent bellwether by backing the eventual winner. Going into 2020, Ohio had sided with the eventual winner in every election since 1964, the longest ongoing streak of any state.

Despite this ability to swing to different parties, that doesn’t make contests here close. In 2016, Trump won the state by almost 450,000 votes, hardly the biggest nail biter in that election. Even so, most polls and analysts saw Ohio being a tight contest. While President Trump was the favorite across most of the projection models, it was expected to be much closer than the 2016 result, akin to Biden’s bid to win Georgia. On the other hand, with an almost six-decade streak of picking the winner, could this give Biden (the heavily favored winner nationally) an edge? Would voters care about upholding such a legacy?

In the end, the answer was no. Not only did President Trump win Ohio, but did so with a comparable margin to his 2016 performance. So much for a nail biter.

As we’ll see in this article, many of the same trends that kept Trump relatively competitive in Michigan, Pennsylvania, and Wisconsin apply to Ohio as well. A key difference, however, is that the elements that made Trump’s 2016 victory possible are more prominent in Ohio than those other states while the counterforces that helped Biden recapture those other states were considerably weaker here. The fact that the state was able to sustain a 52-year tradition of backing the eventual presidential winner regardless of party suggests that this has been the case historically. As a result, Trump’s capture of the state’s traditionally Democratic regions only gave him a stronger advantage in Ohio than in other states, which was much harder for Biden to overcome in 2020.

As of Election Day, there have been 226,138 COVID cases in Ohio, the 12th highest among the states. But considering that Ohio is the 7th largest state by population, this lowers the incidence rate to just 1.9 percent, the ninth lowest in the nation. On the other hand, there have 5,373 deaths as of Election Day (the 13th highest), setting the fatality rate at 2.4 percent (16th highest). Meanwhile, the economic trajectory has been slightly worse than the national average, but not the worst. Ohio went from 5.4 percent unemployment in March to 17.3 percent in April, a 11.9 percent increase that ranks 11th among the states.

According to the US Crisis Monitor, there have been 498 BLM protests in Ohio as of Election Day, the ninth highest of any state. Similar to other states in the Midwest, Ohio’s demographics are not dominated by the groups most likely to organize and participate in such events. Ohio has the 11th largest black population by raw numbers (and 18th by percentage of the total population), the 8th highest amount of college graduates (and 36th by percentage), and the 7th largest young adult population (and 36th by percentage). To this end, this indicates that much of the state’s protest activity is driven simply by the state’s large overall population rather than a strong presence among specific groups.

As for the exit polls, Biden retained 93 percent of Ohio’s Clinton voters while picking up 68 percent of third-party and write-in voters and 62 percent of those who did not vote in 2016. Meanwhile, President Trump retained 95 percent of his 2016 voters; however, these voters make up a larger share of Ohio’s electorate than the rest of the country, meaning that Biden’s gains were not as significant.

For race, Trump won 60 percent of white voters, down from the 62 percent he won in 2016; however, he also won 39 percent of Hispanic voters, a 13-point improvement from 2016. On the other hand, he only won 8 percent of black voters, similar to his margin from four years ago, while Biden picked won 39 percent of white voters (a 6-point improvement from Clinton in 2016).

Regarding educational attainment, President Trump won 43 percent of college graduates (mirroring his national performance), including 46 percent of white college graduates. While this is a key setback for Trump from four years ago, he shored up his support with non-college graduates, winning 58 percent of these voters (an 8-point improvement from his national performance) along with 67 percent of whites without a college degree. Both of these figures are improvements from his 2016 national performance.

As for age, there was also a generation gap that has widened from 2016. Biden won 57 percent of voters in the 18–29 age bracket and 51 percent of those in the 30–44 age bracket. But on the other hand, President Trump wins 57 percent of voters in the 45–64 age bracket and 62 percent of voters over 65. Unlike the generation gaps seen in other states, this one appears to be more skewed towards the older voters, where older voters shifted more towards Trump than younger voters shifted towards Biden.

Geographically, President Trump some key advantages in Ohio. While Biden did win 59 percent of urban voters, President Trump won 55 percent of suburban voters (a 7-point improvement from his national performance). But the other critical factor is that Trump also won a staggering 71 percent of rural voters, a 14-point improvement from his national performance. While some can say that the geographical composition of Ohio skews more rural than the rest of the nation, such differences do not explain the immense increase in support that Trump received in these regions relative to the rest of the country. Once again, Biden’s base appears to be too small to win the state.

Socioeconomically, 46 percent of Ohio voters said their family’s financial situation is better than what it was four years ago (compared to 41 percent nationally), of which 83 percent backed President Trump. 18 percent said their family’s financial situation is worse than what it was four years ago (compared to 20 percent nationally), of which 84 percent voted for Joe Biden. And 36 percent said their family’s financial situation is about the same as four years ago (compared to 39 percent nationally), of which 67 percent voted for Joe Biden. Regarding income brackets, Biden only won 52 percent of voters making under $50,000 (below the 55 percent he received nationally). But President Trump won 55 percent of those in the $50,000-$99,999 bracket (a 13-point improvement from his national performance) and 56 percent of those making over $100,000 (compared to 54 percent nationally). Overall, this demonstrates a broader appeal for President Trump than the rest of the country, where he was able to win among both middle class and upper class voters, a critical component of his win in the state.

When asked about their most important issue, 40 percent of Ohio voters said the economy (compared to 35 percent nationally), of which 89 percent voted for President Trump (compared to 83 percent nationally). Meanwhile, 15 percent said the pandemic was the most important issue and 17 percent said it was racial inequality, of which 90 percent and 91 percent voted for Joe Biden respectively. These figures are consistent with national trends, but also demonstrate how President Trump’s economic message resonated with many voters in the state. Not only did more Ohio voters say the economy was their most important issue, but more of those voters supported Trump in turn. This also carries over when asked what was more important to accomplish, where only 47 percent said it was more important to contain the virus (of which, 83 percent voted for Biden) and 48 percent said it was more important to reopen the economy (of which, 86 percent voted for President Trump).

Now that we’ve gone over the exit polls, let’s run some regressions. First, here are various regression results for Biden’s county-level vote share.

For Ohio, we see a similar relationship to the overall COVID incidence rate (B= -1.60; -1.23) and Biden’s vote share that was seen in Wisconsin, where a higher incidence rate decreases Biden vote share. But unlike Wisconsin, there is no indication that a larger increase in unemployment between March and April increases Biden vote share. In fact, Model 1 (B= -0.37) establishes a negative relationship between these two variables. These findings don’t exactly mean that the incidence rate or unemployment rate were necessarily lower in the counties that Biden won. In fact, t-test results indicate that the incidence rate was higher in counties that Biden won (u=2.1 percent) versus those that Trump won (u=1.7 percent), while there’s no statistically significant relationship for the unemployment increase. Even so, these findings indicate that the pandemic’s severity didn’t necessarily help Biden in Ohio.

Outside of that, we continue to see gaps in age and educational attainment seen in other swing states. And similar to those other states, the amount of BLM protest activity had minimal effect on Biden’s county vote share.

Now, let’s look at the regression models for the Democratic vote share change between 2016 and 2020.

Here, while the incidence rate and unemployment increase are not statistically significant in the change of Democratic vote share, the September unemployment rate is negatively associated in all four models. This indicates that while the pandemic’s severity and initial economic impact didn’t hurt Biden relative to Clinton’s 2016 performance, the lingering unemployment close to the election did harm him. In this case, counties with a high September unemployment rate are those that were already economically depressed before the pandemic (meaning that high unemployment was already a problem) or had a sluggish recovery in the months since the April peak. Once again, this speaks to President Trump’s ability to communicate to these voters that policies restricting economic activity would be more detrimental to their communities than a widespread virus outbreak.

Other than that, nothing is too surprising from results seen in other states. The most notable of which is that the gap in educational attainment has widened since 2016; voters with lower attainment support Trump more uniformly than four years ago and voters with higher attainment support Biden more uniformly than Clinton.

With all that established, let’s look at each of the subsections in Ohio.

Solidly Democratic Counties

Athens (southern part of state, on West Virginia border)- Biden Hold

Biden- 14,772 (56.55 percent, up 0.96), Trump- 10,862 (41.58 percent, up 3.02)

OurProgress Projection- 63.63 for Biden (up 7.08), 36.37 for Trump (down 5.21)

Cuyahoga (Cleveland city proper and surrounding communities)- Biden Hold

Biden- 416,176 (66.36 percent, up 0.4), Trump- 202,699 (32.32 percent, up 1.81)

OurProgress Projection- 71.71 for Biden (up 5.35), 28.29 for Trump (down 4.03)

Franklin (Columbus city proper)- Biden Hold

Biden- 409,144 (64.68 percent, up 4.25), Trump- 211,237 (33.4 percent, down 0.9)

OurProgress Projection- 66.77 for Biden (up 2.09), 33.23 for Trump (down 0.17)

Lucas (Toledo city proper and surrounding communities)- Biden Hold

Biden- 115,411 (57.39 percent, up 1.29), Trump- 81,763 (40.66 percent, up 2.34)

OurProgress Projection- 64.23 for Biden (up 6.84), 35.77 for Trump (down 4.89)

First, there are the solidly Democratic counties, where Hillary Clinton got at least 55 percent of the vote in 2016. Two of the state’s largest cities, Cleveland and Columbus, are included in this subsection. The other two counties include Toledo, a medium-sized city, and the Athens campus of Ohio University (not to be confused with Ohio State University, whose flagship campus is in Columbus). Historically, these counties tend to support Democrats. All four counties have backed the Democratic presidential candidate since at least 1996, three have done so since 1988, and one (Cuyahoga) has stayed blue since 1976. Collectively, these counties are foundational to the any Democrat’s strategy in Ohio; in 2016, 36.6 percent of Clinton’s vote total came from these four counties.

In 2016, Clinton underperformed in this subsection, only getting 62.1 percent of the vote here. Conversely, President Obama received 65.4 percent, translating to a net loss of 71,819 votes. While this isn’t the biggest loss in the world, when this is the main foundation for her electoral strategy, Clinton needed every vote she could get in this subsection, especially when she didn’t get much support elsewhere in the state.

Four years later, Biden did improve in this subsection, getting 64.2 percent of the vote, or a net gain of 78,831 votes. Much of this improvement came in Franklin, where he increased Clinton’s vote share by 4 percent, which is significant in such a large, urban county. He also made a modest improvement in Lucas County; however, Athens and Cuyahoga are pretty static from 2016. While this is somewhat impressive, Biden didn’t reach the same benchmark that President Obama received in 2012.

Demographically, this subsection strongly favors Democratic candidates. 33 percent of the population is nonwhite (more than double the state average) while 6.1 percent is Hispanic. Most of the nonwhite population is black and comes from Cuyahoga, Franklin, and Lucas, although there are smaller pockets of Asian Americans in these counties as well. Similarly, while Hispanics do not constitute a large share of the population, most of them come from the three counties mentioned above. And regarding educational attainment, three of these counties are above the Ohio average. Athens, being home to Ohio University, is ranked 13th (with 29.7 percent of the population having at least a bachelor’s degree), Cuyahoga is ranked 11th (with 31.9 percent), and Franklin, being home to both the state capital and the flagship campus of Ohio State University, is ranked 3rd in the state (with 39.3 percent). And while it’s below the state average, Lucas is ranked 20th (with 26.3 percent).

Socioeconomically, these counties are all over the place. By median household income, Franklin ranks 24th (with $60,383), Cuyahoga and Lucas are in the middle of the pack (with $50,006 and $47,865 respectively), and interestingly, Athens is ranked dead last in the state (with $40,416). Regarding other economic indicators, poverty is a bigger problem in this subsection compared to the rest of the state, as all four counties are in the bottom half of the state (or upper half, depending on your perspective). Franklin has the lowest poverty rate, but at 15.5 percent, it’s still pretty high. And Athens is the highest in the state, with a staggering 30.7 percent poverty rate. And by unemployment, these counties are generally more spread out across the spectrum. In August 2019, Franklin had the lowest unemployment rate in the subsection at only 3.5 percent. Meanwhile, Athens had the highest unemployment rate at 4.9 percent.

As of Election Day, there have been 68,322 COVID cases in this subsection, setting the incidence rate at 2.2 percent (slightly above the Ohio average). Meanwhile, there have been 1,726 deaths, setting the fatality rate at 2.5 percent (slightly above the Ohio average). As expected, most of these cases and deaths came from Cuyahoga and Franklin, the two largest counties in the subsection. Regarding timing, a considerable amount of cases occurred in the early months before rising in the summer months. And while it did decrease in the early fall months, the caseload was still substantial. And for unemployment, the subsection largely reflects the rest of the state, going from 5.5 percent in March to 18.7 percent in April. Notably, Athens and Franklin took much milder hits (5.3 points and 9.8 points respectively) while Cuyahoga and Lucas took more substantial hits (15.6 points and 17.9 points respectively). And while the subsection has mostly recovered in the months since then, the unemployment rate was still 9.5 percent as of September.

Finally, as of Election Day, there have been 174 BLM protests in this subsection, most of them occurring in Cuyahoga and Franklin, the two most populous counties. As mentioned above, this subsection does have considerable black and college graduate populations, but young adults also account for 15.1 percent of the population (above the Ohio average). As home to large college campuses, both Athens and Franklin have particularly large young populations, which further provides the demographic composition that would motivate increased protest activity.

Swing Counties

Hamilton (Cincinnati city proper and surrounding communities)- Biden Hold

Biden- 246,266 (57.15 percent, up 4.42), Trump- 177,886 (41.28 percent, down 1.17)

OurProgress Projection- 59.84 for Biden (up 2.69), 40.16 for Trump (down 1.12)

Lorain (Cleveland metropolitan area)- Trump Flip

Biden- 75,667 (47.96 percent, up 0.33), Trump- 79,520 (50.4 percent, up 2.87)

OurProgress Projection- 53.93 for Biden (up 5.97), 46.07 for Trump (down 3.98)

Mahoning (Youngstown city proper and surrounding communities)- Trump Flip

Biden- 57,641 (48.36 percent, down 1.5), Trump- 59,903 (50.26 percent, up 3.66)

OurProgress Projection- 59.41 for Biden (up 11.05), 40.59 for Trump (down 9.67)

Montgomery (Dayton city proper and surrounding communities)- Biden Flip

Biden- 135,064 (50.18 percent, up 2.94), Trump- 129,034 (47.94 percent, down 0.03)

OurProgress Projection- 51.81 for Biden (up 1.63), 48.19 for Trump (up 0.25)

Summit (Akron city proper and surrounding communities)- Biden Hold

Biden- 151,668 (53.92 percent, up 1.88), Trump- 124,833 (44.38 percent, up 0.96)

OurProgress Projection- 57.22 for Biden (up 3.3), 42.78 for Trump (down 1.6)

Next, there are five swing counties, where Hillary Clinton got between 45 and 55 percent of the vote in 2016. Hamilton County, home to Cincinnati, is the biggest prize; however, there are other notable areas, such as the medium-sized cities of Akron, Dayton, and Youngstown. The other county is Lorain, consisting of suburbs outside Cleveland. Despite being home to a major city, Hamilton was a Republican stronghold for decades, reflecting the socially conservative values of the southwestern corner of the state. While the inner city leans Democratic, Cincinnati remains more conservative than other metropolitan areas in the Midwest. Even so, Barack Obama flipped Hamilton in 2008 and the county has remained blue since then. Outside of that, the other counties have a more extended history of supporting Democratic candidates. Before 2016, each of the remaining four had backed every Democratic since 1992, three since 1988, and one (Mahoning) since 1976.

In 2012, President Obama won all five counties with 55.1 percent of the vote. In fact, three of these counties (Lorain, Mahoning, and Summit) were classified as solidly Democratic after 2012. Four years later, Clinton still won four counties (allowing Montgomery to flip to Trump), but only got 50.5 percent, translating to a net loss of 72,305 votes. Even then, Clinton only carried Mahoning by 3,765 votes and Lorain by 131 votes. These margins were indicative of future trends.

This brings us to 2020, where the results were interesting. On one hand, Biden did improve slightly, getting 53 percent of the vote. He also flipped Montgomery back into the Democratic column and got a 4.4-point boost in Hamilton from Clinton, moving the latter into the solidly Democratic column. But despite receiving a higher vote share and winning a county that Clinton lost, Biden actually only won three of the five counties, one less than Clinton. President Trump was able to flip Lorain and Mahoning, making them part of a Clinton-Trump subsection. These haven’t been brought up yet as there weren’t any in the states discussed in previous parts; however, we will start to see these more, particularly in states that President Trump won.

What makes Lorain and Mahoning distinct from other swing counties? Demographically, these counties are more predominantly white than the rest of the subsection, making up 86.2 percent and 80.3 percent respectively. Educational attainment is also lower in these two counties than the rest of the subsection, having fewer college graduates and more residents that only have a high school diploma. Socioeconomically, neither county appears exceptionally better off (or worse off) than the rest of the subsection; however, they have been more severely affected by the unemployment induced by the pandemic. From March to April, the unemployment rate went from 7.7 percent to 24.8 percent in Lorain and from 7 percent to 20.2 percent in Mahoning, a much larger increase than the other swing counties. And while they have mostly recovered, unemployment remained fairly high in both counties as of September. Despite these severe economic hits, the virus incidence has not been significantly higher in these two counties than in other swing counties. This evidence indicates that these two counties contain demographics that Trump was able to appeal to in other regions in his 2016 campaign, but also the dire economic conditions that would make voters more receptive to his emphasis on reopening the economy in his 2020 campaign.

Demographically, this subsection is very diverse. 25.3 percent of the population is nonwhite (almost double the national average), although only 4.4 percent is Hispanic. Notably, the three counties that Biden won are more diverse than either Lorain or Mahoning in that they have a larger nonwhite population. But interestingly, Lorain has the largest Hispanic population in the subsection, with 5.2 percent, and Mahoning has the second largest. To that end, there is not a one-to-one comparison between racial and ethnic diversity and vote share, although it does appear that counties with a larger nonwhite population tend to lean slightly more Democratic. And regarding educational attainment, this subsection skews towards the top half of the state, although there appears to be a correlation between the counties that stuck with Biden and those that flipped to President Trump. For the counties that stuck with Biden, Hamilton is ranked 6th in the state (with 37.1 percent of the adult population having at least a bachelor’s degree), Summit is ranked 10th (with 32.1 percent), and Montgomery is ranked 17th (with 27.4 percent). As for the counties that flipped to Trump, Mahoning ranks 22nd (with 24.1 percent) and Lorain is right behind it at 23rd (with 24 percent).

Socioeconomically, this subsection is fairly mixed. By median household income, Lorain, Summit, and Hamilton are closely packed together in the top half of the state (with $59,265, $58,890, and $57,300 respectively). While not at the bottom ten, Montgomery and Mahoning skew towards the bottom half (with $51,071 and $48,010 respectively). Similar to the solidly Democratic counties, poverty is also a considerable issue in the swing counties as all of these counties are in the upper half of the state. Summit has the lowest poverty rate at just 12 percent, middle of the pack for the state. Meanwhile, Montgomery has the highest poverty rate at 16.9 percent which, while not in the top ten, is still a pretty high rate. And for unemployment, these counties generally hover around the middle of the state. In August 2019, Hamilton had the lowest unemployment rate at just 3.8 percent. Meanwhile, Mahoning had the highest unemployment rate in the subsection (and 11th highest in the state) with 5.3 percent in August 2019.

As of Election Day, there have been 47,450 COVID cases in this subsection, setting the incidence rate at about 2 percent (roughly the same as the state average). While most of these cases came from Hamilton and Montgomery, overall the incidence rates aren’t too different across the subsection. Meanwhile, there have been 1,195 deaths from the virus as of Election Day, setting the fatality rate at 2.5 percent. Regarding timing, there has been a steady increase in cases during the pandemic, escalating in the summer months and again during the early fall months. And for unemployment, this subsection has mostly followed the rest of the state, going from 5.3 percent in March to 17.1 percent in April, a 11.8-point hit. Notably, Lorain and Mahoning had the highest unemployment rate in the subsection as of March and the highest rate in April, with Lorain taking the largest one-month hit (17 points). While this subsection has mostly recovered in the months still then, the unemployment rate was still at 8.7 percent as of September, with Lorain and Mahoning at 9.4 percent and 10.1 percent respectively.

Finally, as of Election Day, there have been 118 BLM protests in this subsection. 97 of these protests happened in the three counties that stuck with Biden, with 35 in Hamilton, 33 in Montgomery, and 29 in Summit. This is not only reflective of their populations, but also their inclinations towards supporting Democratic candidates in any given election. Meanwhile, there were only 21 protests in Mahoning and zero in Lorain which is interesting, considering that Lorain technically has a larger population than Mahoning. On the other hand, Mahoning is home to a medium-sized city in Youngstown, which offers a centralized hub for protestors to organize. As stated above, this subsection does have a substantial share of black residents, especially in the three counties that Biden won, and a decent share of college graduates.

Obama-Trump Counties

Ashtabula (northeastern corner of state, on Pennsylvania border)- Trump Hold

Biden- 16,497 (37.29 percent, down 0.82), Trump- 26,890 (60.79 percent, up 3.73)

OurProgress Projection- 48.38 for Biden (up 11.09), 51.62 for Trump (down 9.17)

Erie (Sandusky city proper, on Lake Erie)- Trump Hold

Biden- 17,493 (43.28 percent, up 0.55), Trump- 22,160 (54.83 percent, up 2.54)

OurProgress Projection- 50.65 for Biden (up 7.37), 49.35 for Trump (down 5.48)

Montgomery (Dayton city proper and surrounding communities)- Biden Flip

Biden- 135,064 (50.18 percent, up 2.94), Trump- 129,034 (47.94 percent, down 0.03)

OurProgress Projection- 51.81 for Biden (up 1.63), 48.19 for Trump (up 0.25)

Ottawa (Toledo metropolitan area, on Lake Erie)- Trump Hold

Biden- 9,008 (37.46 percent, up 0.17), Trump- 14,628 (60.83 percent, up 3.88)

OurProgress Projection- 45.85 for Biden (up 8.39), 54.15 for Trump (down 6.68)

Portage (Cleveland metropolitan area)- Trump Hold

Biden- 35,661 (42.95 percent, up 0.4), Trump- 45,990 (55.39 percent, up 2.9)

OurProgress Projection- 50.06 for Biden (up 7.11), 49.94 for Trump (down 5.45)

Sandusky (northwestern part of state)- Trump Hold

Biden- 10,596 (35.17 percent, down 0.24), Trump- 18,896 (62.72 percent, up 4.54)

OurProgress Projection- 44.62 for Biden (up 9.45), 55.38 for Trump (down 7.34)

Stark (Canton city proper and surrounding communities)- Trump Hold

Biden- 75,904 (39.93 percent, up 1.04), Trump- 111,097 (58.44 percent, up 2.3)

OurProgress Projection- 45.54 for Biden (up 5.61), 54.46 for Trump (down 3.98)

Trumbull (Youngstown metropolitan area, on Pennsylvania border)- Trump Hold

Biden- 44,519 (44.01 percent, down 0.78), Trump- 55,194 (54.57 percent, up 3.51)

OurProgress Projection- 54.35 for Biden (up 10.34), 45.65 for Trump (down 9.92)

Wood (Toledo metropolitan area)- Trump Hold

Biden- 30,617 (45.29 percent, up 2.83), Trump- 35,757 (52.89 percent, up 2.39)

OurProgress Projection- 50.07 for Biden (up 4.78), 49.93 for Trump (down 2.96)

Next, there are the nine Obama-Trump counties of Ohio, of which Biden was only able to flip one of them back. Montgomery, overlapping with the swing counties, turned back to Biden as a fairly urban county, being home to the medium-sized city of Dayton. The others though remained firmly in Trump’s column, being concentrated in the industrial manufacturing-driven northeastern and northwestern corners of the state. On average, Biden only increased his per-county vote share by 0.7 percent in this subsection while President Trump increased his by 2.9 percent. Montgomery and Wood were the two biggest improvements for Biden, both of which are fairly urban or suburban, leaving the rest with minimal gains and even losses.

In 2012, President Obama won all nine counties with 52.7 percent of the vote. Three counties (Ashtabula, Erie, Trumbull) were classified as solidly Democratic after 2012, all of which are in the state’s manufacturing hubs. Four years later, Clinton suffered massive losses across the subsection, only getting 42.9 percent and receiving 89,399 fewer votes than President Obama. In six counties, Clinton underperformed by 10 percent or more and in three counties, she underperformed by 15 percent or more. As it happened, Montgomery was the smallest loss, at just 4 percent.

Going into 2020, winning back this lost ground was a massive undertaking. Although Ohio was not essential for a Biden victory, making it close would at least send a statement about his ability to rebuild the “Blue Wall”. But considering that the state lacked the broad foundation that other “Blue Wall” states had, winning the state would be extremely difficult without a strong showing in these Obama-Trump counties. Even the OurProgress model saw him winning five counties. But in the end, Biden only received 44.2 percent of the vote in the subsection, less than a 2-point improvement from 2016. As mentioned above, many places failed to produce a substantial boost for Biden, especially in the counties that rely heavily on manufacturing. While this theme has been present in other Midwestern states, this failure to win back these working class counties indicates that Biden’s overall victory came not so much from winning back the areas that Trump conquered, but rather by driving up turnout and consolidating support from demographics that were already trending towards Democrats, such as college-educated voters, suburban voters, and nonwhite voters.

Demographically, this subsection reflects the Obama-Trump counties seen in other Midwestern states. While it’s still above the state average, only 15.4 percent of the population is nonwhite and 3.4 percent is Hispanic, making it the least racially diverse of the subsections covered in this article. Unsurprisingly, Montgomery (the one county to flip back in 2020) is by far the most diverse county in the subsection, with 27 percent of its population being nonwhite. While there are smaller pockets in Erie, Stark, and Trumbull, all the other counties are below the national average for their racial diversity. And regarding educational attainment, this subsection spans the spectrum of the state. On one hand, five counties are in the top half of the state, with Wood ranked 8th (with 33.1 percent of the adult population having at least a bachelor’s degree), Portage is ranked 14th (with 28.7 percent), and Montgomery is ranked 17th (with 27.4 percent). On the other hand, there are four that are ranked in the bottom half of the state.

Socioeconomically, this subsection is mixed. By median household income, this subsection spans most of the spectrum. On one hand, Wood and Portage, both suburban counties, rank in the top fifteen for the state (with $64,282 and $63,689 respectively). Most of the others hover around the middle of the pack. And on the other hand, Trumbull and Ashtabula, both in the northeastern corner of the state, are in the bottom half of the state (with $47,424 and $46,590 respectively). For poverty, the subsection is split fairly evenly between counties in the top half and the bottom half of the state. On one hand, Ottawa has the lowest poverty rate at just 9.5 percent, ranking 22nd lowest in the state. And on the other hand, Trumbull has the highest poverty rate at 17.6 percent, ranking 15th highest in the state. And for unemployment, most of the subsection hovers around the middle of the pack; however, there are some outliers. On one hand, Wood had the lowest unemployment rate in August 2019 at just 3.5 percent. But on the other hand, Trumbull had the highest unemployment rate with 5.7 percent in August 2019 (the fourth highest in the state).

As of Election Day, there have only been 28,573 COVID cases in this subsection, setting the incidence rate at just 1.7 percent (below the national average). On the other hand, there have been 821 deaths, setting the fatality rate slightly above the national average. Regarding timing, this subsection is similar to the rest of Ohio in that there has been a steady increase as the months went on, seeing a rise in cases during both the summer and early fall months. Meanwhile, the economic trajectory for the subsection has been largely consistent with the rest of the state, going from 5.6 percent unemployment in March to 17.5 percent in April, a 11.9 percent increase. Erie County, whose economy is driven by both manufacturing and tourism, took the biggest hit with 18.8 points. And while the subsection has mostly recovered in the months since then, the unemployment rate was still 8.1 percent as of September. Every county except Trumbull had an unemployment rate in single digits by then.

Finally, as of Election Day, there have only been 85 BLM protests in this subsection, with 33 occurring in Montgomery, the most racially diverse county and one that has a lot of college graduates. As noted above, this subsection’s demographics are not prone to increased protest activity. It seems that much of it comes down to geography, with many of them either being medium-sized cities or located close to major cities in Cleveland Cincinnati. But on their own, these areas do not have much of an appetite for protest activity.


As with the other states, there are a few reclassifications for counties based on how their voting behavior changed from 2016 to 2020. These changes are reflected below.

Delaware (Solidly Republican to Swing)

Hamilton (Swing to Solidly Democratic)

Lorain (Clinton to Trump)

Mahoning (Clinton to Trump)

Montgomery (Swing to Solidly Democratic)

Wood (Obama-Trump to Swing)

Regarding geographic and political factors, these reclassifications are pretty well balanced throughout the state. Two counties went from the swing to solidly Democratic column, both urban and in the southwestern part of the state. Two moved from the solidly Republican column into the swing column, both of which are suburban in nature. In this case, we have Delaware, a historically Republican county consisting of suburbs outside Columbus, and Wood, not far outside Toledo.

But most notably are the two counties that moved from the Clinton column in 2016 into the Trump column this time around, both of which are manufacturing hubs in the northeastern part of the state, pretty close to Pennsylvania. Mahoning County, home to Youngstown, had voted Democratic in every election since 1972 before this past election. The fact that this county went to Trump after turning him down the first time around speaks not only to Trump’s ability to retain the working class elements that comprise the region, but his ability to expand in these parts while losing significant group in the suburban, affluent, and highly educated counties elsewhere.


In my prediction article, I said that Ohio would choose Trump and break its long streak of picking the eventual presidential winner. At the time I made it, I was going off all the polls and projection models that had the race as essentially a coin flip (although Trump had a small edge). Aside from that edge, the main reason I chose Trump to win was that there weren’t any catalyst factors that would benefit Biden, such as a competitive Senate race.

In the end, I was correct in my prediction; however, it wasn’t exactly for the same reasons that I laid out in that article. As it happened, Ohio was not as close as the polls indicated. Trump won by a comparable margin to his 2016 performance and he even managed to flip two counties that had gone to Clinton. Similar to Wisconsin, Ohio’s major cities (Cleveland, Columbus, and Cincinnati) are not as dominant in the state’s population as other states. Its population is much more spread out, with medium-sized cities and rural regions playing a more pivotal role in the state politics, hence why it isn’t typically considered a part of the “Blue Wall”.

While it’s easy to point to same culprits seen in other states for why Trump was more competitive than the polls indicated, such as high Republican turnout and high retention by Obama-Trump voters, I think it’s better to illustrate Ohio as a microcosm of how polarized American politics has become. A key theme demonstrated in previous parts and will come up more in subsequent parts is that the Democratic coalition became more uniformly metropolitan and college-educated in 2020 while the Republican coalition became more rural and working class. While this is seen in the small subsection of counties that flipped, it’s seen more so in how many counties either remained the same or shifted more in the direction they went in 2016. And Ohio is a great example of this phenomenon in both parties.

It’s also fair to reassess Ohio’s status as a bellwether state, at least in presidential elections. While it had been correct for over five decades before this past election, will Ohio encapsulate President Trump’s legacy by retaining this urban/rural divide in future elections? Will Ohio move from being a bellwether into a solidly Republican state, much like Missouri? Only time will tell, of course, but I think this past election offers these questions for us moving forward.

So that will do it for the fourth part in this series. If you enjoyed this, please like and follow the Book Aisle. Also share this article on Facebook, LinkedIn, and other social media platforms.