A lot of press coverage of Trump’s win in Florida surrounded the HUGE Republican gains in Miami-Dade County. Don’t get me wrong, it was critical and impressive, but the Republican performance in Osceola County is an underreported spectacle of Republican success.
Below are some graphics representing the success of Osceola County compared to other counties. I plan on exploring this data at a precinct level in a future blog.
County Comparison
From 2016 to 2020, Osceola County Republicans performed 6.7% better in terms of Presidential election vote share. This was the second highest increase in Republican vote share among all Florida counties. The two darkest counties represent Osceola and Miami Dade County. Miami Dade is at the southern tip of Florida.
Below is a graphic displaying the change in Republican votes from 2016 to 2020. The x-axis represents the percentage change of vote for the Republican presidential candidates. The y-axis represents the change in Republican turnout. The size of the circles represents a county’s vote share in comparison to the entire state.
In terms of raw numbers, the Republican presidential candidate received 23,228 more votes in 2020 than in 2016, compared to a roughly 12,000 vote gain for the Democratic candidate.
However, in this case the research question is “In Florida, are Republicans leaving the party? Follow up: How does that rate compare to Democrats leaving their party? Is there an uptick in Replicans leaving the party?”
Methodology
I found some old voter-files in a desk drawer.
file 1 – Florida Voter-file December 2017
file 2 – Florida Voter-file December 2020
file 3 – Florida Voter-file – February 2021
Exploration 1: December 2017 –> February 2021.
Exploration 2: December 2020 –> February 2021.
I loaded each voter file in its entirety. Then I joined each by the state’s voter ID number. I dropped any observations that were not on both rolls. Then I simply looked at the party registration in the first file, looked at the party registration in the second file and if they differ deemed them a “switch”.
Florida Voters December 2017 vs Florida Voters February 2021
In this graph, on the right hand side is Dec 2017 and on the right hand side is the switch. This graph allows us to see how the switches flowed. (click the graph for a larger view.)
But this shows us that in that time, 271,431 (22% of total switches) Republicans switched their registration compared to 387,005 (31% of total) Democrats, and 557,092 (45% of total) NPAs.
So in this time period, MORE Democrats in Florida fled their party.
R Detail
In this Rep detail, 46% of the switches moved from Rep to Dem, 44% of the switches moved to from Rep to NPA, and 11% moved to Other.
Dem Detail
In this Dem detail, 53% of the switches moved from Dem to Rep, 40% of the switches moved to from Dem to NPA, and 6% moved to Other.
NPA Detail
In this case, 52% of the switches moved from NPA to Dem, 40% of the switches moved to from NPA to Rep, and 8% moved to Other.
Florida Voters December 2020 vs Florida Voters February 2021
In this case we redo the counting, but comparing Dec 2020 to Feb 2021.
In this graph, on the right hand side is Dec 2020 and on the right hand side is the switch. This graph allows us to see how the switches flowed. (click the graph for a larger view.)
This shows us that in that time, 39,815 (60% of total switches) Republicans switched their registration compared to 12,933 (20% of total) Democrats, and 1,718 (3% of total) NPAs.
So, we observe a dramatic increase in the proportion of switches – Republicans are moving in greater numbers than they have in the past two years.
R Detail
In this case, 59% of the switches moved from Rep to NPA, 23% of the switches moved to from Rep to Other, and 17% moved to Dem.
Dem Detail
In this case, 57% of the switches moved from Dem to NPA, 31% of the switches moved to from Dem to NPA, and 12% moved to Other.
NPA Detail
In this case, 42% of the switches moved from NPA to Rep, 40% of the switches moved to from NPA to Dem, and 18% moved to Other.
Plot twist
In an interesting plot twist and going against the conventional wisdom that the GOP is bleeding ‘suburban women’, 51% of Republican party switchers are male. Of the Democrat switchers 56% of them are female.
CONCLUSION
In the larger context, in the past two years, the Democrat party lost 387,005 voters to other parties while the Republican party lost 271,431 voters to other parties. This is compared to 557,092 NPAs that registered with a different party – 52% of them registering as Dems and 40% of them registering as Rep.
REMINDER: this analysis is not looking at new registrations or removals (death).
However, the data doesn’t lie and there is a red flashing light:
In the past 2 years, 22% of the voters switching parties were Republicans.
In the past 2 months, 60% of the voters switching parties were Republicans.
The rate of Republicans switching parties has definitely increased in comparison to a base line and it is something to watch very closely moving forward.
Most interesting research questions begin with a real life problem.
A general political consultant we work with wanted to target digital ads to ‘people who are thinking about running for office.’ This is what we do – we build data driven audiences for people to connect with using various media.
So the question is “What type of insane people run for political office and why?” If we could better answer this question, we could build a rock solid digital media audience to target for this political consultant.
While we do not yet have the ability to read people’s minds as to their political ambition, we start by asking who has done research in this area. At times, the world aligns and you find a good paper that has done just that – reviewed the literature for you.
Dr. Gulzar, from Stanford, does a review of the literature – using comparative data and US data.
This paper presents the difficulty of such a “simple question.”
“Who runs for office and why?” is difficult to even conceptualize and attempting to delve into the ‘whys’ illustrates how completely messy human behavior is.
At Ozean, when we begin an analysis for a potential political candidate there are three main areas we look at: political, environment and then and only then do we look specifically at the candidate.
What are the political considerations? This is where we take a look at the rules, the political calendar, the district or political boundaries, the historical returns, the political media environment. Items that are constant over time in this district, state.
What is the current political enviroment? This is where we look at district composition, incumbency, current polling information, the national political enviroment, where the party is in recruitment process, what additional items are on the same ballot, who else may be in the race from the same party, who else may be in the race from the competiting party, and potential shifts from considerations observed in first phase. (example – is there a pending change in political boundaries?)
Candidate Traits. This is the difficult one because depending on 1 and / or 2, specific candidate traits may be irrelevant. As the old saying goes, the district may pick the representative. However, assuming 1 & 2 are favorable, what traits make a successful candidate? Because we have seen in close election after close election, candidates do matter.
But even that progression shows the difficulty in reviewing this literature. My conceptualization above is more in line with asking “What makes a successful candidate?” not “Who runs for office?” Two very different questions.
The research does a good job of exploring the challenge of “unseen candidates”. These are the candidates that seriously consider a run and don’t declare for whatever reason.
The research attempts to classify three determinants – individual, group, and institutional.
On the individual front, Black is quoted as saying an individual will consider the probability of winning * the benefit of winning – Cost. Is that net benefit higher than other options? Like any models this is very simplistic, and I think assumes way too much rationality in the decision making process. The model completly ignores some of the most important individual traits – the least of them being EGO.
In addition, the author explores the insitutional factors – primarily party recruitment and allocation and steering of resources.
Another group or instutional factors is one that I despise, but it is a reality – dynastic political families –name ID and political networks mean a lot in this game, and much to my chagrin, kids are able to plug into or grew up in these networks.
Finally, a final instutional factor is the rules. Filing fees, timeframes, Hatch Act considerations…etc. The rules of the game – especially when it comes to ballot access – matter a lot in politics.
The author then explores political competency and asks is there a trade off between political competency and political representation. Said another way, should the elite (weathy, highly educated (so many lawyers), leadership skills) rule us? Should they rule us when they are significantly different than the district’s citizens? It is an interesting section, but doesn’t really bring us closer to answering the pivotal question – “Who Runs for Office?”
Well, in this review of the literature – the author admits in the last paragraph – we really don’t have good data on this.
“While researchers often focus on work on political entry or leadership that has a formal political flavor, more work is needed on the antecedents of political entry. What activities and jobs increase the likelihood of future participation in politics as a politician? Tracing the pipeline of political entry before it formally occurs could provide insights into how the political class may be broadened, for instance.”
CONCLUSION
While the review of the literature is informative and an relatively easy read, it does shed a light on that fact that we don’t really have great data on who runs for office.
I think some of the more interesting work mentioned in the paper is a new line of research being inspired by Dal Bó et al. They explored Sweden, but they are attempting to look at individual variables, and I think that has promise. If you have been in this business, you know there is a ‘type.’ and I would like to see more work done defining the individual traits of those that raise their hand and offer themselves for public service.
Year after year, digital media continues to make up larger shares of campaign budgets. This means new technology, new regulations, and a rapidly changing landscape. Compared to new, highly efficient methods, the “old digital” of yesterday is obsolete and in some cases – such as with political ads on Facebook – non-existent. Success in the digital sphere is reliant on how quickly you can adapt to, and take advantage of, these changes.
Many organization, political committee, and campaign digital strategies relied heavily or solely on Facebook. When the ban was put in place, they went dark and couldn’t compete.
Bottomline – it is malpractice to put all your eggs in one basket and be at the mercy of any single platform. Successful campaigns have the ability to digitally contact audiences through multiple avenues.
The New Kid on the Block – CTV and OTT
Another major contributor to the changing digital landscape is Connected TV (CTV) and Over-the-Top (OTT) advertising. The impact of CTV/OTT is so significant that it allows digital advertising to compete with traditional TV advertising. Roughly 25% of U.S. households are unreachable using traditional TV ads after “cutting the cord” and choosing streaming services over traditional cable – up from just 19% in 2019. By 2024, this number is expected to grow to 35%. https://techcrunch.com/2020/09/21/pandemic-accelerated-cord-cutting-making-2020-the-worst-ever-year-for-pay-tv/
CTV and OTT advertising is a highly accurate, highly efficient way to stream political ads into the living rooms of your target audience. Instead of blanketing an entire DMA with a traditional TV ad, CTV/OTT allows you to choose which households your ads are served to – cutting down waste and maximizing the use of every penny. Although it is unlikely that CTV/OTT will replace traditional TV ads in the near future, it is making a huge splash in the digital world.
Political Direct Mail, Door Knocking, and Voter Turnout
People often wonder whether campaign tactics actually get people to the polls… or is it a bunch of useless political hackery? Does mail actually work? What about door-knocking and those never-ending political phone calls?
In what is often regarded as the “gold standard” experiment in campaign effects and turnout, Gerber and Green (2000) tested this question in their study titled, The Effects of Canvassing, Telephone Calls, and Direct Mail on Voter Turnout: A Field Experiment.
The experiment took place during the 1998 election in New Haven, Connecticut, and involved over 30,000 registered voters. The authors contacted voters with voter-mobilization-themed messaging via direct mail, face-to-face canvassing, and telephone calls. The canvassing experiment began four weeks before the election, the direct mail experiment began 15 days before the election, and the telephone experiment began 3 days before the election.
The results showed that personal canvassing was the most effective campaign tactic for turning out voters, followed by direct mail. Phone calls had a negligible effect. Empirically, canvassing increased turnout by roughly 9.8% and direct mail increased turnout by .6% per mail piece.
How does this affect real-world campaigns? Knock on doors and send mail. One of the most important resources a candidate has is time. With such positive turnout outcomes from canvassing – candidates should spend their time knocking on doors and, of course, fundraising.
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Thank you for your interest in the original research study. This research is conducted with our non-partisan research partner Meer Research, and the research explores the opinions of candidates that were NOT successful in running for elected office. These are people that have been in the arena and their experiences are worthy of consideration.
In addition, 2/3 of the candidates studied tell us they are likely to run again – this time with lessons learned.
We consider this to be exploratory research, and we are especially interested in your feedback and suggested additional veins of research.
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