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).
With Donald Trump railing about how mail ballots encourage fraud and other insidious crimes associated with the this type of voting method, I would expect that some Republican voters would opt for voting in person, even in the midst a hundred year pandemic.
My curiosity led me to rank the counties by the percentage of mail ballots returned compared to their total number of registered voters. This would put all counties on an even playing field, regardless of their population. Using this comparison, little Monroe County outperformed Miami Dade on a percentage of registered voters basis.
Table 1 below lists the percent of mail votes returned as compared to their total resisted voters for each county.
COUNTY
PERCENT MAIL BALLOTS PER REGISTERED VOTERS
Alachua
32.37
Baker
16.78
Bay
23.24
Bradford
21.59
Brevard
32.49
Broward
37.44
Calhoun
17.79
Charlotte
37.28
Citrus
33.49
Clay
20.93
Collier
44.37
Columbia
22
DeSoto
19.34
Dixie
24.95
Duval
20.84
Escambia
26.46
Flagler
34.55
Franklin
30.15
Gadsden
24.62
Gilchrist
20.46
Glades
24.4
Gulf
19.5
Hamilton
21.81
Hardee
12.63
Hendry
17.23
Hernando
32.22
Highlands
29.59
Hillsborough
36.09
Holmes
20.06
Indian River
36.63
Jackson
20.93
Jefferson
24.33
Lafayette
16.05
Lake
26.21
Lee
45.76
Leon
30.91
Levy
26.05
Liberty
15.15
Madison
17.43
Manatee
38.45
Marion
27.89
Martin
36.61
Miami-Dade
32.66
Monroe
39.2
Nassau
25.14
Okaloosa
25
Okeechobee
20.9
Orange
32.29
Osceola
31.99
Palm Beach
38.01
Pasco
31.43
Pinellas
48.91
Polk
28.47
Putnam
17.76
Santa Rosa
20.91
Sarasota
41.52
Seminole
30.96
St. Johns
27.41
St. Lucie
34.26
Sumter
38.65
Suwannee
22.17
Taylor
24.2
Union
15.78
Volusia
35.86
Wakulla
22.21
Walton
20.16
Washington
17.63
Table 1 Mail-in Ballots as a percent of registered voters
The Top Five Counties are Pinellas at number one, followed by Lee County, Collier County, Sarasota County, and Sumter County. So what do these counties have in common?
Surprisingly, these five counties have a high proportion of registered Republicans. In Pinellas County, virtually half of the county’s vote went to Trump. The same is true of Sarasota County, where Trump won by 1.5% and Trump carried Collier by 25%. In Monroe County he won by 9 points and Lee County by 20 percent.
In the chart below, I list the top ten mail-in ballot Counties. The only two county’s on the top ten list that Biden won were Palm Beach and Broward Counties, which finished 8th and 9th respectively.
COUNTY
PERCENT MAIL BALLOTS
Charlotte
37.29
Broward
37.51
Palm Beach
38.06
Manatee
38.51
Sumter
38.67
Monroe
39.4
Sarasota
41.62
Collier
44.46
Lee
45.86
Pinellas
49.05
But Democrats did beat the Republicans in the total number of mail ballots with 5,303,254 to the Republicans’ 5,169,012, a difference of 134, 242 ballots counted.
It’s obvious from this list that Trump’s concern about fraud in mail-in ballots was not shared by many Republicans. Otherwise he might have lost the state.
So which state won Doctor Politics first Presidential Quadrennial Election Mail In Ballots Award? Pinellas County with a remarkable 49% of registered voters sending in mail ballots in the Florida 2020 Election!
That’s a record that will be hard to beat, at least without a Small Pox Pandemic on election day! Make sure you have your shots and, of course, be safe…
After every election, many political pundits conduct the inevitable election autopsy. For winners, it is more about taking credit for the win. For the losers, its not to take the blame at all. This post is neither. I’m just curious how Florida vote changed since 2016.
To understand Florida you need to look to the individual counties and not the state as a whole. That’s because Florida is several states on one narrow peninsula. The people living in Wakulla have as much in common with Broward voters as New Yorkers have with Birmingham, Alabama voters.
So to analyze Florida you need to look at each county and see if the state shifted to the right since Trump’s victory in 2016. Specifically, did all or only a few counties turned a brighter shade of red.
To do this we have to make sure we are not mixing apples with watermelons. The most obvious way is to compare each county’s total vote for either Trump or Clinton (2016) with the 2020 county vote for either Trump and Biden.
Although that seems sound, it would not be accurate because of each county’s population and registration changes during the past four years. More voters equals more votes. In Florida, the population changes each hour let alone in a four year period. In addition, some counties grow exponentially and others don’t change at all.
The solution is to calculate each candidate’s county percent of the two party vote. In other words, dropping the third party candidates from the analysis completely and comparting those percentages to the previous election. Using the two-party percentages acts as a control variable that is independent of the total vote.
On Florida’s 2020 ballot for example, there were five other candidates in addition to Trump and Biden. Although they didn’t accumulate a significant number of votes, combined they still walked away with over 100,000 votes.
Let’s start with how Donald Trump’s percentage of the vote change from 2016 to 2020, as shown in Table 1 below.
COUNTY
TRUMP.2016 %
TRUMP.2020 %
Alachua
36.4
35.7
Baker
81.5
84.7
Bay
71.1
72.1
Bradford
73.7
75.8
Brevard
57.8
57.6
Broward
31.4
35
Calhoun
76.6
80.8
Charlotte
62.5
62.9
Citrus
68.3
70.7
Clay
70.4
67.9
Collier
61.7
62.4
Columbia
71
72.2
DeSoto
62.7
65.7
Dixie
80.8
82.7
Duval
48.9
47.4
Escambia
58.3
56.7
Flagler
58.9
60.2
Franklin
68.6
68.3
Gadsden
30.4
31.4
Gilchrist
80.1
81.5
Glades
68.8
72.8
Gulf
73.1
74.9
Hamilton
63.1
65.4
Hardee
69.1
72.2
Hendry
55.7
61.1
Hernando
62.9
64.6
Highlands
64.7
66.8
Hillsborough
44.7
45.9
Holmes
87.9
89.1
Indian River
60.8
60.4
Jackson
67.8
69.1
Jefferson
51.4
53
Lafayette
82.8
85.5
Lake
60
59.5
Lee
58.7
59.2
Leon
35.4
35.3
Levy
71
72.4
Liberty
77.2
79.9
Madison
57
59.4
Manatee
57
57.6
Marion
61.7
62.5
Martin
62
61.9
Miami-Dade
34.1
46.1
Monroe
51.6
53.5
Nassau
73.5
72.4
Okaloosa
71.3
68.6
Okeechobee
68.5
71.9
Orange
35.4
37.9
Osceola
35.9
42.6
Palm Beach
41.1
43.3
Pasco
58.9
59.5
Pinellas
48.6
49.3
Polk
55.4
56.7
Putnam
66.9
70.2
Santa Rosa
74.5
72.4
Sarasota
54.3
54.8
Seminole??
48.7
48.1
St. Johns??
65
62.8
St. Lucie
49.9
50.4
Sumter
68.8
68.1
Suwannee
76.4
77.9
Taylor
74.6
76.5
Union
80.2
82.2
Volusia
54.8
56.5
Wakulla
68.5
69.9
Walton
76.6
75.4
Washington
77.4
80.8
MEAN %
62.01
63.40
TABLE 1 COUNTY TRUMP/BIDEN PERCENT VOTE
If you look closely, you will notice that there is very little change from the 2016 election. For all 67 counties, the average difference was only 1.39%! In 2016, Trump spent in Florida over $10 million for an increase of less 2%. Of course, he did win the state.
How similar the two time periods are graphically displayed in Chart 1 below, where the blue line shows the Trump 2016 percent and the red line 2020. In many parts the lines merge into one line showing that the percentages are identical.
Now let’s look at the Clinton/Biden Florida county differences, as shown in Table 2 below.
CLINT.% 2016
BIDEN.% 2020
Alachua
59
62.9
Baker
16.7
14.6
Bay
24.9
27.5
Bradford
24.2
23.2
Brevard
38
41.2
Broward
66.5
64.6
Calhoun
20.4
18.7
Charlotte
34.7
36.3
Citrus
28.6
29.3
Clay
26.1
30.8
Collier
35.8
37.4
Columbia
26.5
27.2
DeSoto
35
33.6
Dixie
17.6
16.7
Duval
47.5
51.2
Escambia
37.7
41.6
Flagler
38.3
39.3
Franklin
29
30.9
Gadsden
67.9
67.9
Gilchrist
17.3
17.6
Glades
29.2
26.7
Gulf
23.6
24.3
Hamilton
34.9
33.7
Hardee
28.3
34
Hendry
41.5
38.1
Hernando
33.9
38.4
Highlands
32.7
34.8
Hillsborough
51.5
52.9
Holmes
10
10.2
Indian River
36.3
38.8
Jackson
30.4
39.1
Jefferson
46.3
46.1
Lafayette
15.3
13.9
Lake
36.9
39.5
Lee
38.3
40
Leon
60.5
63.5
Levy
26.3
26.8
Liberty
19.8
19.5
Madison
41.5
39.9
Manatee
39.8
41.5
Marion
35.5
36.6
Martin
35.2
37.4
Miami-Dade
63.7
53.4
Monroe
44.7
46
Nassau
23.3
26.5
Okaloosa
23.6
29.4
Okeechobee
29
27.5
Orange
59.8
61.1
Osceola
61
56.4
Palm Beach
56.6
56.1
Pasco
37.4
39.4
Pinellas
47.5
49.5
Polk
41.3
42.3
Putnam
30.5
28.9
Santa Rosa
21
25.8
Sarasota
42.7
44.4
Seminole??
47.1
50.8
St. Johns??
31.6
36.1
St. Lucie
47.5
48.9
Sumter
29.5
31.7
Suwannee
21.2
21.3
Taylor
23.2
22.7
Union
17.8
16.9
Volusia
41.8
42.9
Wakulla
28.3
29.1
Walton
20.4
23.7
Washington
20.3
19.2
MEAN %
35.07
35.7
Table 2
Here I show the Clinton parentage results for 2016 when Hilary Clinton opposed Donald Trump in Florida. Alongside are the Biden percentages for each county in 2020. The average percentage difference between the two Democrats was only 0.63%. Biden’s campaign, after spending over $100 million, he increased Clinton’s percentage by less than one percent.
This hypothesis is antithetical to campaign consultants. It all boils down to how you spend the money that matters. For Biden, his last minute bid to defeat Trump in Florida failed. More importantly, his increase over Clinton’s vote was still less than one percent.
In the end, however, this analysis demonstrates that Florida hasn’t yet turned a deeper shade of purple yet. In fact, it hasn’t significantly changed at all in four years and continues its valid claim to the title of the “swingiest state in the Union.” Be safe…
OK the polls were generally off again. They underestimated the Trump vote even after all the changes recommended by independent experts since 2016. In the last post, I showed that Trump voters were not candid about who they were voting for on election day, a form of social desirability effect. “The Return of the Shy Voter?”
As I was analyzing polling data before the Presidential election, I was having some doubts about the polling data. A little voice in my head kept saying “are you sure these numbers are right?”
At the time, I was trying to predict the election outcome in key swing states like Florida. As you may recall, the average of polls for Florida gave Biden a statewide lead of 1.2%. Making a prediction for Florida on that statistic would be like betting on a horse with one fast time but who never won a race. So I called the state for Trump. That’s how scientific it was.
I have always been convinced there had to be a better way to predict an election other than based on polls only. But my previous attempts to find that method have always led to failure.
But that has never deterred me from continuing my gallant quest to discover the magic variable that would solve the election prediction problem. Until now…
I have always been interested in the “favorability rating,” which supposedly measures how voters feel about the candidate. The question is simple: “Do you have a favorable or unfavorable opinion of Donald Trump?”
As you can tell, this question doesn’t measure anything specific like the common Job Approval rating, which measures the incumbent’s performance in office. The favorable rating is considered a popularity measure, but I’m now convinced that it is more than that.
There is a general lack of studies on what the rating means due to a lack of analysis on the subject. It was generally believed that they correlated with job approval ratings, but when Bill Clinton’s affair became public his favorability declined significantly but his job approval rose.
The academic literature has only a few studies about the impact favorability rating except to suggest that it is more than just another way to measure an incumbent’s job approval.
This brief study shows that in the late stages of a Presidential campaign “the candidate with the stronger favorable rating in the late stages has won every election since 1980, and there has been an almost-perfect correspondence between the margin of the favorability gap and his margin of victory or defeat in the popular vote.” As important as this statement is, they posted no data to confirm this assumption. But this was my first clue that the favorability rating was more than just a popularity variable.
Some of you know my fondness for job approval ratings and why they matter for the incumbent. But the biggest issue with this rating is it doesn’t apply to non-incumbents who are challenging the President. Consequently, we cannot measure the difference between the two, which could tell us how the voter would likely choose on election day.
But that is not the case with the favorability ratings. It applies to both the incumbent and the challenger, allowing us to make a significant comparison on how voters feel about candidates. At least that is my hypothesis.
But there is one important problem. Most pollsters don’t ask this question at the state level. At least until now. There is a new resource for state by state surveys from a relatively new company called Civiqs.
Their methodology is an opt-in survey panel covering every state in the country (https://civiqs.com/). One of their continuing questions is the favorability rating. Each day the data is uploaded to their public site.
Using this data, I started compiling the favorability rating for Trump and Biden for each state as shown in Table 1.The date for these ratings was October 25, 2020, some nine days prior to the election .
STATE FAVORABILITY RATING
TRUMP
BIDEN
Alabama
62.5
36.4
Alaska
51
40
Arizona
49
49.5
Arkansas
62.6
34.6
Calfornia
33.4
64.6
Colorado
41.9
55.4
Connecticut
40.4
58.1
Delaware
39.8
58.8
Florida
51.2
47.9
Georgia
46
46
Hawaii
25
59
Idaho
63.9
33.1
Illinois
42.3
55.8
Indiana
57.1
41
Iowa
53.2
45
Kansas
56.5
43.3
Kentucky
62.1
36.2
Louisiana
58.5
39.8
Maine
44.2
52.9
Maryland
34.9
63.3
Massachusetts
32.6
65.6
Michigan
47.9
50.6
Minnesota
41
47
Mississippi
59.7
38.8
Missouri
56.9
41.3
Montana
56.9
40.6
Nebraska
58.6
39.2
Nevada
40
45
New Hampshire
45.6
52.8
New Jersey
37
54
New Mexico
43.6
54.2
New York
43
55.7
North Carolina
50.1
48.7
North Dakota
65.5
31.9
Ohio
51
43
Oklahoma
65.4
32.3
Oregon
40.6
57
Pennsylvania
49.1
49.7
Rhode Island
39.1
59.4
South Carolina
55.1
43.4
South Dakota ?
62
35
Tennessee
60.7
37.4
Texas
52.2
46.4
Utah
58
37.8
Vermont
30.8
66.4
Virginia
44.5
54.1
Washington
38.7
58.8
West Virginia
68.7
29.6
Wisconsin
48.9
49.6
Wyoming
70.4
26.7
AVG. FAVORAABILITY RATING
49.782
47.054
TABLE 1 FAVORABILITY RATNGS BY STATE as of October 25
If you look at Florida, you will see that the favorability ratings between Trump and Biden were quite close. There is just 3.3% difference between the two, in Trump’s favor. As we all know now, the Florida contest was close. In fact, when the dust cleared Trump defeated Biden by only 3% (51%-48%) in Florida.
At first, I didn’t see the similarity between the actual vote and the candidate’s favorability rating. When I took a closer look, I noticed that there was a 3.3% difference between Trump and Biden’s favorability ratings taken some 9 days before the election. Just three-tenths of a percent difference than the final results in Florida.
As interesting as that result seemed, I was not ready to say Eureka just yet. But it gave me the incentive I needed to compile by hand all the favorability ratings for all states on that same date, as shown below in Table 2 below.
A negative value indicates that Biden had a negative rating because I subtracted Trump’s percent from Biden’s in every case. For example, Alabama shows the favorability rating difference was -26.1%. That means Trump had 26.1% more favorable ratings than Biden in Alabama. In California, Biden had a positive 31.6%, which indicates he had 31% more favorable ratings than Trump in California.
As a comparison, I have added in the third column the final vote percent difference between Biden and Trump.
As an example, the final election vote for Biden in Maryland was 63.3%. For Trump it was 34.9%. If you subtract 34.9% from 63.3% your get 28.4% (Trump vote % – Biden vote %). The final vote difference on election day was exactly 28.4%!
STATE
BIDEN/TRUMP.FAV.DIFF
FINAL VOTE PERCENT DIFFERENCE
Alabama
-26.1
-26.05
Alaska
-11
-10.1
Arizona
0.5
0.5
Arkansas
-28
-28.5
California
31.2
31.6
Colorado
9
11.25
Connecticut
17.7
18.35
Delaware
19
19
Florida
-3.3
-3.15
Georgia
0
-0.1
Hawaii
34
29.4
Idaho
-30.8
-30.9
Illinois
13.5
12.75
Indiana
-16.1
-18.05
Iowa
-8.2
-8.1
Kansas
-13.2
-13.6
Kentucky
-25.9
-26.45
Louisiana
-18.7
-18.35
Maine
8.7
9.85
Maryland
28.4
28.4
Massachusetts
33
34
Michigan
2.7
2.35
Minnesota
6
6.5
Mississippi
-20.9
-20.45
Missouri
-15.6
-15.8
Montana
-16.3
-15.65
Nebraska
-19.4
-19.7
Nevada
5
5
New Hampshire
7.2
7.6
New Jersey
18.6
20.8
New Mexico
10.6
10.3
New York
12.7
15.35
North Carolina
-1.4
-1.4
North Dakota
-33.6
-33.3
Ohio
-8
-8
Oklahoma
-33.1
-33.05
Oregon
16.4
16.7
Pennsylvania
0.6
0.65
Rhode Island
20.3
20.15
South Carolina
-11.7
-11.85
South Dakota
-27
-26.5
Tennessee
-23.3
-25.15
Texas
-5.8
-5.9
Utah
-19
-19.5
Vermont
35.6
34.3
Virginia
9.6
9.3
Washington
20.1
21.05
West Virginia
-39.1
-39.05
Wisconsin
0.7
0.35
Wyoming
-43.7
-43.35
TABLE 2 BIDEN-TRUMP FAVORABILITY RATING AND FINAL VOTE DIFFERENCE
Out of the 50 states, the largest error rate between Trump and Biden’s final vote difference and their favorability difference was in Hawaii, with 4.6% difference. For all 50 states, the average error difference was only .04%.
In political science, we use regression models to determine the relationship between variables which also produces a scatterplot of the results. In the Chart below, this scatterplot shows how tight the “fit” is for the models estimates.
Each small circle represents a state and the red line the linear relationship between the Biden / Trump favorability difference and the final vote percent difference. From a statistical viewpoint, the relationship between the two measures is almost perfect (.994 R square).
In other words, we can now predict the final vote percent difference between two candidates by using only the favorability ratings prior to the election. More importantly, the error rate is only .04%.
Does this method apply to the national vote? The national favorability rating for Biden on October 25th was 45% and for Trump 42%, a 3% difference. The final national vote for Biden was 51.1% and for Trump 47.2%, a 3.9% difference. The final vote difference was 3.0%, an error of nine-tenths of one percent.
So why has no one discovered this by now? There a couple of possible reasons. First, there is very little research on the favorability ratings and what they mean to voters. Secondly, until recently, no polling firms have consistently used these ratings at the state level. Finally, with the exception of Nate Silver’s fivethiryeight review, no one else has seen any relationship between the ratings and the final election results.
The bad news is that Civiqs data does not go back to 2016, so we can’t compare the ratings to the actual vote in that Presidential election.
Who knows, in the future we might be able to cancel the election altogether and just rely on this system instead. I’ll have to check with my pocket Constitution to see if that is legal. Be safe…
I’m sure you have heard or read that the Presidential Election polls screwed up again. Initially I was skeptical, of course, since 2016 almost all polling firms had made significant changes to their methodologies such as weighting voter education.
But after all the studies and soul searching, whatever changes that were made did not cure most if not all the errors, at least to Donald Trump’s share of the vote.
Using only swing states and not the national vote, I have compared the polling averages from surveys taken from polls conducted within the final 30 days prior to the election.
The states I analyzed are Florida, Georgia, Pennsylvania, Wisconsin, North Carolina, Arizona, Michigan and Ohio. No polls were excluded because of political bias or voter interview methods (live-interviews, online, or IVR, etc.).
I computed the absolute error between the polling averages and the actual state election results for both Biden and Trump. For example, if the final state result had Trump with 48% and the polling average at 46%, that would mean an error of 2%.
In the table below are the Trump and Biden absolute error rates for each state, starting with North Carolina, which had a Trump polling error of 2.3% and for Biden, 1.1%.
If you go down the list, all state polls except Florida, had Trump’s polling percent with greater error than for Biden. In all eight states, Trump’s average absolute error was 2.93% and Biden’s .062. All the state differences were statistically significant (T-Test).
TRUMP
BIDEN
STATE
ERROR
ERROR
N.CAROLINA
2.3
1.1
OHIO
6.2
-1.05
PENNSYLVANIA
1.6
1.1
WISCONSIN
5.1
-1.4
GEORGIA
2.3
1.1
MICHIGAN
2.9
0.1
ARIZONA
2.6
0.4
FLOIIDA
0.4
3.6
AVG. % ERROR
2.93
0.062
The average error for all of these states for Trump’s share of the poll percent’s was a significant 2.9%. But for Biden it was only .062%. In other words, the polls consistently underestimated Trump’s vote by nearly three percent.
Random Error vs. Systematic Error
There is some error in every poll and there is nothing we can do to prevent it. Of course you can increase the sample size, but that can only reduce the error. Pollsters expect this, but they often pretend that polls properly conducted represent the future outcome. Polls are estimates and not absolute predictions.
And then there is systematic error. Before the survey begins, pollsters try to predict the turnout. Who votes and those who do not can alter that polling estimate regardless of statistical error. Overestimating or underestimating one group can have a significant effect on the final results. That is systematic error.
So how did lightening strike twice in two elections. After 2016, the best minds in survey research came up with few potential errors:
1. Undecided voters broke for Mr. Trump in the final days of the race. But that didn’t happen this year according to exit polls and independent surveys.
2. Turnout among Mr. Trump’s supporters was somewhat higher than expected. No, that did not happen this time. Pollsters expected high turnout from both Biden and Trump voters.
3. Trump’s support in the decisive Rust Belt region, in part because those surveys did not adjust for the education. Not this time: Every major pollster adjusted for education in this election.
4. Some type of “shy Trump” voter bias was dismissed as unlikely.
What stands out to me is how the Biden poll estimate was right on the money, with an error rate of only .062%, which is about as perfect as it gets in surveys.
But the Trump voter error was almost 3%. This is undoubtedly a systematic error and not random. And this is the second Presidential election this has occurred.
The obvious answer to the failure of polls for the last two election cycles are with the responses of Trump voters. The average Biden poll percent of the vote was on the mark. All the error came from the responses of Trump supporters.
So let’s narrow down the search for the systematic error as to why Trump voters were underestimated when every other possibility has been eliminated.
We have eliminated previous possibilities, so that suggests that either Trump voters refused a polling interview, didn’t answer the phone or misled as to their real preference.
In the later case, this is a type social desirability effect called self-deceptive enhancement (SDE). SDE response bias is any systematic tendency to answer questionnaire items on some basis that interferes with accurate self-reports.
Self-deceptive enhancement bias is common in surveys on sensitive issues such as job performance surveys and sexual behavior. Pollsters have known this for decades. The cure for this bias in many cases is the application of computerized surveys.
But the issue of who you are voting for has never been considered sensitive enough to cause significant errors.
If self-deceptive effects are occurring, then we should see more accurate results from firms using Interactive Voice Recording (IVR) and online surveys, where the voter expresses their choice to a machine and not to a live person. This would be similar to a computerized survey when an honest/accurate response is important.
In my insatiable quest for truth in polling, I compiled a list of polling firms by their interview technique: live calls, IVR (robocalls) and online surveys listed on 538’s website.
Then I compared their interview method with the their last months Trump survey results and compared it to the final vote percent for Trump. (31 polling firms met this criteria). If there is no bias, we should see similar results from all three methods when compared to the actual vote.
My hypothesis is that the IVR and online polls were significantly (<.001 level) different than live caller polls and more accurate in Trump’s final vote. This would mean that Trump voters were not truthful in their responses to the live interviewers as compared to non-live caller interviews (IVR/online). In other words, the Trump shy-voter lives!
The results to this experiment were conclusive. As the chart below graphically demonstrates, live-interviewer polls have a significantly larger error rate for Trump supporters than either IVR or IVR/online polls, with an average error rate of 5.62% (red bar).
The survey method that was the most accurate on the Trump responses was the IVR/Online surveys, with an average error rate of only 1.6%. Next accurate was the IVR poll, with an error rate of 2.85%. Bringing up the rear, of course, are the respected and dominate forms of polling – the live-caller interviewer surveys with a 5.62% error rate!
The survey firms in this last category are the country’s most respected and considered the most accurate pollsters in the country. You know who I’m talking about.
I’m not going to criticize these major firms since I quite frankly didn’t believe that social desirability effects were causing these survey errors either until I looked at the data.
But in hindsight, I should have considered it. After all, Donald Trump considers the Proud Boys as a socially acceptable group. For many Republican voters, this is probably not an acceptable opinion (along with many others he has espoused). Consequently, when talking to a live-interviewer, they made a small fib, even though they planned to vote for Trump.
This insight, if used in Presidential election surveys where one of the candidates has opinions that are outside the mainstream, such as Donald Trump running again in 2024, should cure this problem.
Let me hear from you on what you think. I could use your comments. Be safe…
Ok, tomorrow is Election Day (thank God). And with caution thrown to the wind, I will make my key state predictions. Using the latest large sample surveys that are available, and the early partisan votes to confirm my intuition.
First, the basics: All surveys have must have at least 700 or more interviews. No surveys are excluded for their political bias, as long as their methodology is acceptable.
Florida:The Swinging Shine State
DATE
BIDEN
TRUMP
MOE
10/29 – 10/31
48
47
3.5
10/29 – 10/30
51
45
3.3
10/29 – 10/30
49
48
1.9
10/27 – 10/31
47
44
3.2
10/26 – 10/29
50
47
—
10/25 – 10/28
47
50
2.9
10/24 – 10/29
48
50
4
AVG.
48.6
47.3
3.1
These two charts display the current averages between Biden and Trump. With only a day to go, Biden in the last seven polls has 48.6% versus Trump’s 47.3%. That’s only a 1.3% difference and far less a difference than the average margin of error of +/-3.1% (MOE).
But when you look at the early partisan voting turnout, Democrats have only a 108,000 vote lead over registered Republicans. Now I understand that you can’t know how these partisan voters voted, but most will vote along party lines.
The problem is that a 108,000 may not be enough Democratic voters to offset the lead the Republicans can generate on election day. This is the day that Republicans come out of the woodwork to vote. And many Democratic leads have failed to make the finish line after all the votes are cast.
That said, the large NPA turnout may offset this advantage. As I have posted recently, NPA voters have a 58% probability to vote Democratic. This could male the difference for a Biden victory.
It’s obvious that from a statistical point of view, Florida is a tossup and we could wait several days, if not weeks to find out who won. My guess: Donald Trump. When it’s close, the Republicans always seem to find a way to win in Florida.
Doctor Politics Florida Call: Trump
Arizona
DATE
BIDEN %
TRUMP %
MOE
10/29 – 10/31
48
46
3.6
10/27 – 10/29
45
49
3.5
10/26 – 10/30
49
43
3
10/23 – 10/30
50
46
3
10/25 – 10/28
46
49
4.1
AVERAGE
47.6
46.6
3.44
Well if you thought Florida is close, Arizona makes Florida look like a landslide. The average of the last five polls shows Biden with a one point lead, with a margin of error of +/-3.44%. If you look up the word “tossup” in the dictionary you would see a map of Arizona.
And early voting gives the Democrats a lead of only 43,055 votes. This gives Trump a pretty good shot on winning this state.
DR. POLITICS NORTH CAROLINA CALL: TRUMP
GEORGIA POLLS:
BIDEN
TRUMP
MOE
10/29 – 10/31
48
49
3.5
10/28 – 10/28
47
48
3.6
10/27 – 10/28
48
46
3.8
10/23 – 10/27
50
46
4.4
AVERAGE
48.25
47.25
3.825
Georgia hasn’t voted for a single Democratic candidate since 1996. But as you can see, the last four larger sample polls, the difference is only one percent.
Georgia does not require a party registration, so we don’t know the partisan early/mail vote party differences. Atlanta has the largest proportion of Democratic voters. So far 780,000 Atlanta votes have been cast, out of a total vote off four million votes cast so far, or about 20% of the vote.
I’m sticking to tradition: Dr. Politics Calls Georgia for Trump
THE BLUE WALL RISES
The Keystone State: Pennsylvania
DATE
BIDEN
TRUMP
MOE
10/31 – 11/1
50
47
3.5
10/30 – 10/31
46
48
2.9
10/29 – 11/1
51
46
4.4
10/27 – 11/1
51
45
4.3
10/27 – 10/31
49
43
2.4
49.4
45.8
3.5
Next to Florida, this is a state that really matters if you are a Trump fan. If he loses this state on Tuesday, Donald Trump can go ahead and rent that moving van. (He will, of course, contest this and several other state totals, so he can probably wait a few more weeks.)
Biden is leading in every recent poll except Trafalgar, which is the pollster who called Trump winning in 2016. They have Trump up by 2 points. The average Biden lead among all surveys is 3.6%, just above the margin of error.
As far as the early vote, Democrats have over a one million mail vote lead over Republicans going into election day.
Dr. Politics Call: Biden
Michigan
DATE
BIDEN
TRUMP
MOE
10/30 – 10/31
46
48
2.9
10/29 – 10/30
52
45
3.4
10/27 – 11/1
52
42
4
10/29 – 10/29
52
45
3.4
50.5
45
3.425
In the last four Michigan surveys, Biden leads in all but one poll. It is, of course, the Trafalgar survey with Trump leading by 2%. On average, Biden leads by 5.5%, above the average margin of error of 3.4%.
Wisconsin: The Blue Wall Holds
Excluding Trump’s narrow win in 2016, no Republican presidential candidate has won this state since 1988.
DATE
BIDEN
TRUMP
MOE
10/29 – 10/30
53
45
3.5
10/27 – 11/1
53
43
4.2
10/26 – 10/30
52
41
3.2
10/24 – 10/25
48
47
2.9
10/23 – 10/30
52
44
3.9
10/21 – 10/25
48
43
4.4
AVERAGE
51
43.8
3.7
And as we enter election day, it looks like this trend will continue. Biden now has a 7.2% lead. The average margin of error is +/-3.7%, absent 2016 polling errors, this looks Biden has this state’s 10 electoral votes.
IMPORTANT: Biden can win the electoral college vote without Florida, Georgia, North Carolina, Ohio, Texas, Arizona and Nevada, if he carries Pennsylvania, Wisconsin, Minnesota, and Michigan. (And the other states Hilary won easily in 2016).
This would give Biden 280 Electoral Votes and the keys to the White House.
If you are concerned a 2016 poll redux, I don’t seeing this happening in any significant way. All the pollsters I have talked to have resolved many of the weighting issues that caused most the errors. More importantly, we have far more state-level surveys than we did in 2016 making the averages more reliable.
As for watching the election results on TV, make sure you have plenty of alcohol on hand. It’s going to be a long night… be safe.
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
Model
R Square
Adjusted R Square
Std. 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
Model
Unstandardized Coefficients
Std. Error
Beta .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…
This a quick update on seven key battleground states. In the chart and table below, is a one month comparison of Joe Biden’s average poll lead in these key states.
POLL DATE
23-Sep
25-Oct
STATE
BIDEN LEAD %
BIDEN LEAD %
FLORIDA
1.5
-0.4
WISCONSIN
6.9
5.5
MICHIGAN
6.5
9.4
PENN
3.8
3.8
MINNOSOTA
10.2
6
ARIZONA
4.4
2.4
N. CAROLINA
0.7
0.8
AVERAGE
4.86
3.9
The last two columns are the end dates of each series of surveys. First series is Biden’s lead in seven battleground states completed on September 23. The second series on October 25, a little over one month apart. The chart shows a graphical representation of each state’s changes during this period.
In all seven states, Biden lost on average one percent. The only state he increased his lead was Michigan, where he improved his lead by nearly 3%. And he is still ahead of Trump in the key state of Pennsylvania, at 3%.
He has fallen slightly behind Trump in Florida. In general, however, Biden is holding his own with only one week to go. But its clear that Florida, Pennsylvania, Arizona and North Carolina are still very close and still in play. That’s 75 electoral votes.
Make sure you get a nap on November 3rd, cause it looks like its going to be a long night. Be safe …
As expected, early voting is benefiting the Democrats. Data collected by the Elections Project (United States Elections Project) from the Florida Division of Elections shows that Democratic voters as of October 25, have a 6.4% lead over Republican voters, as shown below.
Total Voted by Party Registration
OCT. 25
Party
Count
Percent
Democrats
2,440,470
42.8
Republicans
2,076,621
36.4
Minor
69,798
1.2
No Party Affiliation
1,119,404
19.6
TOTAL
5,706,293
100
TABLE 1
CHART 1
As of this date, Democrats have a 363, 849 vote advantage over the Republicans.
Most of this early Democratic advantage comes from Mail-in ballots. In Table 2 below, you will find the Democrats have returned 594,110 more ballots than Florida Republicans and have a return rate of 65% compared to the Republicans 61.8% rate.
Mail Ballots Returned by Party Registration
25-Oct
Party
Returned Ballots
Freq. Distribution
Requested Ballots
Return Rate
Democrats
1,744,527
47.1
2,671,740
65.3
Republicans
1,150,417
31
1,862,285
61.8
Minor
45,116
1.2
82,195
54.9
No Party Affiliation
765,729
20.7
1,353,719
56.6
TOTAL
3,705,789
100
5,969,939
62.1
TABLE 2
Where the Republicans excel is in the in-person voting. As displayed in Table 3 below, the Republicans lead by 11.5% in this category.
In-Person Votes by Party Registration
Party
Count
Percent
Democrats
695,943.00
34.80
Republicans
926,204.00
46.30
Minor
24,682.00
1.20
No Party Affiliation
353,675.00
17.70
TOTAL
2,000,504.00
100.00
TABLE 3
At this point, Republicans have outvoted in-person the Democrats by 230,261 ballots. And on Election Day, this is where the Republicans will close the gap.
With the Democrats significant lead in Mail-in ballots, the Republicans need to make up a deficit of 363, 849 votes on November 3rd. But don’t underestimate the Election Day Republican vote. This is when they start showing up at the polls. This lead will evaporate quickly.
In 2016, there were 9,122,861 total ballots cast which equated to a 75% turnout of registered voters.
2016
VOTES CAST
TRUMP
4,617,886
CLINTON
4,504,975
TOTAL
9,122,861
TABLE 4
If the 75% turnout rate holds, that means there are still at least 5,125,108 votes still to be cast. That’s still a lot of votes and only a week to cast them. If you haven’t voted already, make sure you are part of that 5 million votes. Be safe…
The impact of the incumbent’s Job Approval rating on his reelection nationally is well established. Since 1948, the beginning of modern polling, only one incumbent president, Harry Truman, has won reelection with an job approval rating less than 48%.
Below is a table showing all incumbent presidents since that election with their job approval ratings in June and just prior to the election.
PRESIDENT
YEAR
June of reelection year
Final measure before election
Won reelection
% Approve
% Approve
Obama
2012
46
52
Yes
G.W. Bush
2004
49
48TRTR
Yes
Clinton
1996
55
54
Yes
G.H.W. Bush
1992
37
34
No
Reagan
1984
54
58
Yes
Carter
1980
32
37
No
Ford
1976
45
n/a
No
Nixon
1972
59
n/a
Yes
Johnson
1964
74
n/a
Yes
Eisenhower
1956
72
68
Yes
Truman
1948
40
n/a
Yes
GALLUP SURVEYS
TABLE 1
As the table shows, eight of eleven of incumbents won reelection during this period, and no President won with a job approval of less than 48% (Truman). And the average approval rating is 51.2%.
Political scientists believe this one metric more than any other, determines an incumbents reelection chances. This makes sense if you think of a reelection as determining whether an employee, the chief executive of the nation, should be retained. If he has done a good job, you keep him on for another four years. If he hasn’t, you send him packing even if you like him.
The job approval poll question was created by George Gallup for that one reason. If you’re wondering, as of this date Trump’s national average Job Approval is at 44.5%. And his average rating since he was elected stands at 40%, the lowest average since the question has been asked.
It is possible that Trump could break this record and win the November 3rd election. But that isn’t my interest here. I’m interested if the job rating can be applied at the state level.
In other words, can Donald Trump win Florida, for example, with a statewide job approval of less than 48%, or does this metric only apply to national elections?
In my quest, I scoured Google Scholar for any academic articles that would answer this question and came up empty handed. I could not find a single article that addressed this question at all.
The reason for this dearth of scholarship on the subject should have been obvious to me from the start. State polls don’t ask this question, except in rare cases.
But recently, Civiqs has developed an large opt-in online panel that conducts daily surveys of randomly selected (list based) registered voters from its large panel from all 50 states.
A regular question asked each day is the standard job approval rating. And from their database, I have now found job approval ratings for all 50 states as of this date. I want to stress that this exercise is experimental and the likelihood that a state approval rating could predict the winner is unlikely. (That’s my null hypothesis.)
As a baseline, I am using a 2017 Gallup state by state survey using the standard job approval rating. At this point I am only interested in these swing states: Arizona, Florida, Georgia, Iowa, Michigan, North Carolina, Ohio, Pennsylvania, Texas, and Wisconsin. But I may add the other 40 as we get closer to the election.
In Table 2 below, lists the 2017 approval rating and the current October 22, 2020 rating in each of these states. In the fourth column, is the percent difference between the two surveys, which are all positive. The last column is Trump’s current average poll percent lead or deficit in each state.
For example, in Arizona, Trump had a job approval rating of 41% in 2017 and a current rating of 44%, which is 3% higher than in 2017. In the latest average of polls, Trump is behind Biden by 3.2%.
TRUMP JOB APPROVAL 2017-2020
STATE
2017
2020/CURRENT
DIFF%
POLL%
Alabama
53
Alaska
50
Arizona
41
44
3
-3.2
Arkansas
50
California
29
Colorado
37
Connecticut
31
Delaware
36
Florida
41
45
4
-1.5
Georgia
41
45
4
-1.2
Hawaii
29
Idaho
53
Illinois
33
Indiana
44
Iowa
43
47
4
-0.6
Kansas
48
Kentucky
51
Louisiana
49
Maine
42
Maryland
30
Massachusetts
27
Michigan
40
41
1
-7.8
Minnesota
37
Mississippi
48
Missouri
47
Montana
52
Nation
38
Nebraska
49
Nevada
42
New Hampshire
42
New Jersey
34
New Mexico
35
New York
30
North Carolina
40
44
4
-1.5
North Dakota
57
Ohio
45
46
1
0.6
Oklahoma
53
Oregon
36
Pennsylvania
42
42
0
-5.1
Rhode Island
32
South Carolina
48
South Dakota
54
Tennessee
50
Texas
39
48
9
4
Utah
48
Vermont
26
Virginia
37
Washington
34
West Virginia
61
Wisconsin
41
43
2
-4.6
Wyoming
57
TABLE 2
As the table shows, Trump’s statewide approval rating has increased since the 2017, but not by a lot. The biggest gain is Texas, where his approval rating improved by 9 points and is now at 48%, which at the national level, would theoretically reelect him. His current Texas lead over Biden is now 4%. These two metrics would suggest Texas will go to Trump.
His next highest approval rating is Iowa, at 47%. But Biden now has a narrow lead of just 0.6%. This state is too close to call.
At an approval rating of 45% are both Georgia and Florida. In Georgia, Biden has a 1.2% lead over Trump. Although very close, this state could easily go Democratic this year, if the job approval rating has the same impact it does at the national level.
Now we have the swingiest state in the nation, Florida. Trump’s approval rating is now 45% as well. And Biden has a 1.5% average lead in the state. My gut feeling is that Trump will win the Sunshine State, but at this point the tea leaves give a slight edge to Biden.
In Arizona, Trump’s job approval rating is now 44% and Biden with a 3.2% lead. For now the sate is leaning toward Biden.
Following Arizona we have another close contest in North Carolina, where Trump’s approval rating is 44%, and Biden has a slim poll lead of only 1.5%. Giving weight to the job approval rating, this state looks like it could end up in the Biden column.
And finally, we have the mid-west trifecta of Pennsylvania, Michigan and Wisconsin. All three states have Trump’s approval rating at 43% or less. The average poll lead for Biden in Pennsylvania is now 5.1%, in Michigan it’s 7.8% and Wisconsin at 4.6%. At this point with only 11 days left, all three should deposit their electoral college votes in the Biden column.
I again want to emphasize that this is an experiment to see if the Presidential Job Approval rating has the same predicted capability it does at the national level. Closer to November 3rd, I will update this table.
Feel free to use these tables to place bets with your friends and neighbors. My fee is only 5% on your winnings. I don’t know about you, but I’m excited. Be safe…
I have seen some TV reporting that Republicans are outperforming Democrats in new registrations. This stimulated my interest to see if this was true in Florida and if so, what impact it might have on the Presidential Election occurring in two weeks.
I have assembled Florida registration data from 1972 through 2020 as of this years’ book closing, and compared the differences between the two parties. Let’s start with Florida’s total registration over that 48 year period, as shown in Chart 1 below.
CHART 1
The chart shows how Florida’s total registration has increased exponentially over the past 48 years reflecting the state population growth. In 1972, total registration was 3,487,458 and in 2020 is 14,441,869, a 314% increase.
But the real question is what has been the Democrats advantage over this same period and is it increasing or decreasing over this same period. Chart 2 graphically shows how the Democrats registration advantage has declined significantly since 1972.
A little history can explain some of this change. Florida was a traditional Southern state for most of its existence. Southern states were solidly Democratic after the Civil War. Beginning in the 1970’s, Florida’s population changed as new residents arrived from the Midwest and Northeast changing both the population and the culture of Florida’s Old South traditions. At the same time, many old South Democrats changed their registration to Republican.
As the chart shows, there was a sharp decline in the Democratic registration advantage in the 1980’s, finally leveling off around 2002. But in 2008, when Barack Obama was the Democratic nominee, there as new surge in new Democratic registrants.
But when his second Presidential term came to an end, the decline in the Democratic advantage in registration started again, reaching its current level of 134,242 more Democrats than Republicans, shrinking some 560,000 since 2008.
The obvious question is whether the Democratic registration advantage affects which party’s candidate wins? The common sense assumption is that an increase in a party’s registration would increase the likelihood of victory. In my experience, I have found that common sense has little to do with politics.
If an increase in the Democratic advantage increases it should also increase the Democratic election wins. Consequently, the decline in that advantage should increase the likelihood of a Republican win. That’s common sense.
But that is not the case. As you can see in Table 1 below, from 1972 through 2016
YEAR
PARTY
DEM ADV
2016
REP
330428
2012
DEM
558272
2008
DEM
694147
2004
REP
367884
2000
REP
379086
1996
DEM
430773
1992
DEM
645597
1988
REP
903671
1984
REP
1417136
1980
REP
1657782
1976
DEM
1611972
1972
REP
1419605
AVG
868029
TABLE 1
In this period, Republicans won seven of the 12 Presidential Florida elections, when the average Democratic registration advantage was 868,029 voters. The year when the Democratic advantage was at its highest (1980), the Republicans won the election.
I also performed a correlation analysis using both the number of votes and number of party victories, and none were statistically significant.
I have to say I expected to see some relationship between registration and the election outcome. In writing this post, I called an old friend who has been directly involved in many campaigns and asked what he thought. His immediate response explained it all: “Candidates still matter.”