MEET THE VOTERS WHO COULD WIN FLORIDA FOR BIDEN

October 28, 2020

Florida has a total of 3,783,286 No Party Affiliation voters (NPA). Over a million have already voted in the Presidential Election. If you are a Democrat or a Republican you have a high probability of voting for the candidate representing that Party. But what about the NPA’s? Most folks call them independents, but as I have posted previously, most independents tend to lean toward one party. http://thepoliticsdr.com/wp-admin/post.php?post=1735&action=edit

Political pundits on TV show polling results comparing men vs woman, young vs old, whites vs blacks will vote. But you never see surveys that compare NPA’s vs Republicans or Democrats. NPA’s do vote in presidential elections, but are largely absent in local elections. At this point, 1,395,712 NPA’s have already cast their vote. That’s 20% of the early vote.

But is there a way to estimate how the NPA registrants might vote based on the 2016 election data to see how they might vote on Tuesday? The answer is yes, but it is a little complicated. So bear with me and I will simplify as best I can.

Using election data from Florida’s 2016 Presidential Election, in particular voter registration data at the county level, I designed a model that estimates the percentage of NPA voters who voted for Clinton.

The statistical method is called multiple regression, which I have used in previous posts. In political science this is the most used model in academic studies.

A simple explanation for this statistical method is that it allows for the control of other influential variables, thus isolating the independent impact of the variable of interest, which in this case is the county level registration of NPA voters on Hillary Clinton’s total vote.

The table below shows the models explanatory statistics. Focus on the R square statistic which is .998. This means that nearly 100 percent of the variance in the dependent variable (Clinton’s vote) is explained by the model. That’s as high as it gets.

Model Summary
ModelR SquareAdjusted R SquareStd. Error of the Estimate
 .998.997.997
TABLE 1

In order to isolate other variables that could affect her vote, we need to control for the county level registration of Democrats and Republicans which would, of course, have a significant effect on her vote.

Coefficients
ModelUnstandardized Coefficients
Std. ErrorBeta .SIG
(Constant)-879.101 .490
NPA.REG.578.075 .000
DEMOCRAT.674.040 .000
REPUB-.203.034 .000
TABLE 2

Notice how the Republican registration unstandardized coefficients variable (REPUB) has a negative sign, meaning it reduces her votes which we would expect. The Democratic variable has positive sign, which indicates it has a positive effect on her vote. And the NPA registration also has a positive sign as well.

To see how the model actually performs we need to see how it performs on the 2016 election, which is shown in the Chart 1 below. It displays the models scatterplot of the NPA registration with Clinton votes based on the model’s estimate.

In the Chart, the small circles are the 67 Florida counties. As the number of NPA registrations increase, so does the total county votes for Clinton as well. The straight line reflects how linear the relationship is between NPA registration on her vote while controlling for Democratic and Republican’s county registration.

What does this mean? Well it means we can now estimate

Clinton’s likely vote from NPA voters alone. If you look back at Table 2, labeled “Coefficients,” you will see a column labeled Unstandardized Coefficients. Next to the NPA REG, is the .578 coefficient. What this tells us is that a one unit change in the dependent variable (Clinton vote) changes if we increase the independent variable by one unit (.578) keeping other independent variables constant.

OK, let’s use examples of how this affects Clinton’s vote. For every increase of NPA registration by .578 increases Clinton’s vote by one. In plain terms, an increase of 100 NPA registrations increased her vote by 58.

Now let’s apply this estimate to Biden’s vote. Currently, 1,395,712 NPA’s have already voted and using our estimate that would mean that 806, 721 voted for Biden. In other words, he is likely getting 58% of the NPA vote.

Let’s estimate that 75% of NPA voters participate in this election. That means that 2,837,465 total NPA votes, which would add 1,645,729 votes to the Biden total column. That is 16% of the total vote if we have a 75% turnout.

Now for the caveats. First, the model is an estimate based on the a previous election. Secondly, the model should be considered a broad estimate. Saying that, what this analysis does show is that Democratic candidates benefit from higher NPA turnout.

Personally, I don’t know if either the Florida Democratic Party or the Biden campaign had a get out the vote program for NPA voters. If they haven’t they should add one to swinging state in the future. Be safe and vote…

By Jim Kane

Jim Kane is a pollster and media advisor, and was for fifteen years an Adjunct Professor of Political Science at the University of Florida. Kane is founder of the polling firm USAPoll and served as the Director of the Florida Voter Poll. His political clients have included both Republican and Democratic candidates, including the Republican Party of Florida, and both the Sun-Sentinel and Orlando Sentinel newspapers. At the University of Florida, Professor Kane taught graduate level courses in political science on Survey Research, Lobbying and Special Interest Groups in America, Political Campaigning, and Political Behavior. In addition to his professional and academic career, Jim Kane has been actively involved in local and state policy decisions. He was elected to the Broward County Soil and Water Conservation Board (1978-1982) and the Port Everglades Authority (1988-1994). Kane also served as an appointed member of the Broward County Planning Council (1995-2003), Broward County Management Review Committee (Chair, 1990-1991), Broward County Consumer Protection Board (1976-1982), and the Broward County School Board Consultants Review Committee (1986-1990).

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