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Trump Presidential Job Approval and His Polling for President

May 30, 2020

Since January 1st, 1,131 national polls asked “Do you approve or disapprove of the way Donald Trump is handling his job as president?” The average percent of “Disapprove” for these 1131 surveys is 53.3%.

That virtually every national poll contains this question suggests that it has some significant importance that should effect voters’ political vote choice. But almost all studies suggest otherwise, that is until right before the election.

But I don’t find any academic studies on the effect that a President’s job approval has on their polling percent of the vote. You would expect a high degree of probability between the two variable.

To test this hypothesis, I obtained all 1,131 surveys conducted from January through May 26th, 2020 that contained both the standard job approval rating and the trial ballot question between Biden and Trump in the same survey.

In this time period, Trump had a net positive (approve less disapprove) rating in only four surveys, as shown in the chart below where the net positives are above the horizontal line.

His job rating has been underwater for most of his time in the White House. If Trump’s Job Approval rating were predictive at this point, I would recommend he put a reservation on a moving van for the fall. But as I have pointed out before, this variable has a short shelf-life and only predictive when measure close to the election.

In the Biden/Trump elections question, Trump has a 41.9% average against Biden’s 49.7%, an average lead of 7.8% for all 1,131 surveys.

His Biden/Trump polling is out performing his job approval rating by 1.7%. The chart below shows how his percent of the Biden/Trump poll changes as his disapproval rating changes.

This graph depicts what happens to Trump’s percent of the Biden match-up as more voters say they disapprove. That, of course, means that the people who are least likely to vote for Trump are those who disapprove his job performance.

This shouldn’t be a surprise since people who do not like someone will never vote for him or her, and people who do like him may or may not vote for him. What is surprising is that the “approval” rating is does not effect his polling percent.

I can now calculate the average reduction of Trump’s disapproval rating based on the regression model’s standardized coefficient estimate’s reduction of his percent of the two-party poll percent against Biden. The model coefficients are shown in the table below.

Coefficients
ModelUnstandardized CoefficientsStandardized Coefficientst
BStd. ErrorBeta
1(Constant)68.95010.268 Sig.

6.715
APPROVE.051.124.044.408.684
DISAPPROVE-.547.116-.504-4.715.000

We can calculate Trump’poll percent of the vote against Biden’s with a simple equation: Y = -.547 (x) + Constant (68.95), where x is Trump’s disapproval rating and Y is the Trump’s percent of the vote against Biden. Notice that the significant (Sig.) level for “Approval” is .684, and non-significant at the <.05 standard.

Trump’s average disapproval rating in these surveys is 53%. So our equation is Y = -.547 (53) + 68.95 or Trump percent of vote =40%, 1% less than the actual average of all polls.

What is this analysis suggests is that Trump’s job disapproval rating is far more important than his approval rating in determining his percent of the vote. In fact, the approval rating in this analysis is not significant, meaning it has no impact on his percent of the vote.

Will this apply to the actual election in November? The honest answer is I don’t know. Normally, models that predict election outcomes use past election data (along with other exogenous variables, such the economy).

But the President’s “approval”rating has been shown to predict his re-election when polled near the election. No president since modern polling has won re-election with an approval less than 50% on election day.

Because of the inverse relationship, when the approval number is 50%, the disapproval rating is likely around 46% (excluding the “don’t knows”). As we get near the election, I will revisit this equation again to see if it does predict the winner.

In the mean time, when you see a 2020 poll, check out the disapproval rating. If it is more than 37%, he’s losing…

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Do Mail-in Ballots in Florida give Democrats an Advantage?

May 28, 2020

I’m sure that most of you have heard that President Trump wants to eliminate mail-in ballot voting, particularly in battleground states. His reasoning (I’m using that word in its broadest sense) that mail-in ballots are ripe for election fraud, even though most political scientists say the amount of election fraud is small, mail or otherwise.

I suspect his reasoning is more about his belief that mail-in ballots give Democrats an advantage. Others believe that the President is creating the idea of wide spread fraud as a potential excuse in case he loses the election. But none of this makes any sense to me because in all my campaign experiences, absentee voting has always benefited the Republican candidate.

In general, traditional Republican voters are better educated and consequently, more likely to use this less taxing method. This may not apply as much in the age of the Trump voter, where many are less educated than traditional Republicans and they may rely more on in-person voting. That’s speculative, of course.

So to satisfy my curiosity, I researched Florida’s past election data and found some mail-in ballot data with actual mail-in ballots cast by party affiliation in three general election cycles: 2014, 2016 and 2018. These election cycles include two non-presidential elections and one presidential one.

The data is broken down in to four categories, Republican, Democratic, No-Party Affiliation (NPA) and Other voters. Since my purpose is to find if one of the two major parties has some kind of partisan advantage, I have eliminated both NPA and other party mail votes from this analysis.

In 2016, the Republican state-wide mail vote total was 1,108,053 and the Democratic mail votes were 1,049,809, a 58,244 Republican vote advantage in the presidential election, graphically shown below.

In 2016, the Republican candidate (Trump) should have had a 2.8% vote advantage if both Democrats and Republicans voted the party line and NPA’s and other non-partisan voters split evenly between the two candidates. If you may recall, Trump beat Clinton by only 1.2% in Florida.

In the 2014 general election, the number of Republican mail ballots cast was 833,420, and by Democrats 705,752, a 127,668 more Republican mail votes, as shown below.

In this year, the Republican candidates could have had 8% more partisan support based on the Republican mail ballots. And finally, we have the 2018 general election when both the Florida Senate and House were on the ballot.

The Republican mail vote advantage here was the smallest of the three election cycles since it featured only state House and Senate races. Republican mail ballots cast were 1,080,808 versus 1,026,600 Democratic ballots, or 54,208 ballot difference, but still a 4% advantage.

This short analysis of three election cycles clearly demonstrates that Florida Democrats have no advantage when mail ballots are employed. Actually, the opposite is true. Republican candidates should benefit from an aggressive mail-in ballot campaign.

Florida maybe the most important state in the country. In fact since 1928, no Republican presidential candidate has won the presidency without winning Florida. Even Trump himself may have won Florida based on the partisan mail votes alone.

So why is he complaining about mail ballots when obviously the facts, at least in Florida, don’t support that Democrats benefit from this voting option?

It is possible his campaign found that mail ballots benefit the Democrats in other swing states. It is also possible the campaign hasn’t done any research on this subject at all. Or, that Donald Trump just believes this idea that Democrats benefit more from mail-in ballots and, God forbid, no one should contradict him.

If you have an idea, please post it in the comments section and I’ll share it with all readers. Be safe…

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The Canary in the Coal Mine is Beginning to Sing

May 26, 2020

Regular viewers of this site may recall that one of my original posts was showing our Covid-19 model for both Florida and the US. The model was a non-linear (cubic) estimate of the direction of the virus that accurately predicted when the virus’s new cases began to decline in both Florida and the Nation.

Unfortunately, as the data points descended, they slowed down and eventually began backing up, causing a traffic jam of data points. New Covid-19 cases would on one day go down and the next go back up and so on and on. In addition, the up and down changes weren’t uniform.

To correct for this up and down pattern, I went to my old calculus tool box and applied a logarithmic data transformation called a natural log (ln). In this case, the transformation is from daily new cases to percentage change. So instead of watching cases move up an down we now plot the percent change from each data point. In addition, this log transformation makes the data far more interpretable.

Using a polynomial equation (cubic), I can now attempt to predict the direction of Florida’s new Covid cases by using the transformed (ln) data. I want to emphasize that this effort is experimental and could easily predict nothing except that I was wrong, but in theory it should work. The chart below plots the expected path.

The red line shows the predictive path of new cases. The small circles show the actual cases after transformed into percentage change. The blue lateral line shows the flattened ceiling of the data.

For example, the virus percentage change peaked around the 37th day and began to decline until about the 70th day when the cases (percentage change) began to rise again.

From that point, the red line bends upward. This is the model’s predicted path, which suggests a rise in new cases. In other words, the Florida Covid-19 pandemic is increasing and no longer stabilized! If this trend is correct, it strongly suggests that the loosening of restrictions has allowed the virus to expand.

I will post this graph on a regular basis or when significant changes occur. I have mixed emotions about the success of this experiment. Like all of us, I want this virus to disappear sooner than later. It is very possible that the prediction line will shift downward and show a decline in new cases. For me, that’s a win-win. Be safe in any case…

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Are Florida Covid-19 New Cases Going Up, Down or Sideways?

May 24, 2020

I don’t know about you, but I’m having trouble of whether Florida’s new virus cases are rising, declining or just plain stuck in second gear. On television, some news stations tell us that Florida’s new cases are stabilized, and another reports it’s declining and and some newspapers that they are rising.

The problem is that in Florida the pattern of new cases is not obvious. Some days the state health department reports 1,200 new cases and the next day 650.That’s, of course, not their fault because this virus can’t decide if it’s coming or going. So the data pattern is often up and down each day.

Contributing to the problem is how most media outlets and the Health Department display the daily counts using the linear format of the ubiquitous bar chart like the one below.

This bar chart tracks the actual daily number of cases since the first recorded cases in March. As you can see, the general pattern since the first peak around the 35th day, is downward until around the 40th day, when a series of up and down cases began to appear, interrupted only by occasional spikes.

Many times you will see a moving average line through the bars which is at least better than just the bars alone. The problem with moving averages, is how many days do you apply to make the average. Some use a seven-day average, or a three day or even a 30 day average. And besides smoothing the data, what does a moving average represent? How many days you apply effects the slope of the line and the more days used the flatter the line.

I have always opposed using linear graphs for data that isn’t linear. But the “up and down” pattern is hard for almost all graphic representations. The only way to solve this problem is to transform the data points into a form that moves in some systematic way and still accurately represents the data.

In calculus, log transformations are common in helping understand the data. In general, one of the main purposes of log transformations is to make the data better interpretable and graphs easier to understand.

Mathematicians, engineers and economists are the principal users of log transformations. For economists, the natural log (ln) is the preferred choice since it measures the percent change from data point to data point.

In other words, instead of raw data of new cases that go up and down, we can transform it into the percent change which can be graphed and understood. Below is a graph of the same data shown in the bar chart above, but with the data transformed into natural log (ln) values.

With the data transformed into percentage change, we can easily see that in the early days of the infections, the percentage change of new cases rose exponentially and then around the 30th day leveled off and has remained relatively flat since then.

You could interpret this chart as a good news-bad news story. The good news is that Florida’s new Covid cases have not continued to increase (as represented by percentage change). The bad news is that they haven’t declined yet either.

I will be using log transformations from time to time or when needed for you to understand graphs easier, without compromising the analysis. Some of my posts at times may be difficult to understand but feel free to ask me a question or leave me a comment and I will gladly reply. Be safe…

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HAS THE COVID-19 VIRUS HURT TRUMP’S POLL NUMBERS?

May 22, 2020

In early April, I statistically demonstrated that the coronavirus had no effect on Donald Trump’s Job Approval ratings (Has the Coronavirus Hurt Donald Trump’s Reelection Chances?). That post showed that pre-virus period approval ratings were not statistically different than the virus period.

Now I read and hear that Trump’s polling numbers against Biden are being hurt by his handling of the Covid crisis. If you google that phrase you will find dozens of articles making this observation.

“Perhaps more worrying for Trump are his dwindling numbers in a match-up against Joe Biden.” The Guardian

Admittedly, polls on how well Trump is handling the Covid-19 crisis have been largely negative. The internet site 538 has polling that shows that 51% disapprove of his handling of the coronavirus crisis. Consequently, it has to be hurting his polling numbers.

This assumption requires that the two concepts are identical. But a person chooses a candidate for many different reasons and is not always dependent on one issue alone. In other words, you could agree he has mishandled the covid crisis and still vote for him.

To test this hypothesis, I collected 80 different independent surveys that included the Biden vs. Trump trial ballot question, from September 2, 2019 to May 19, 2020. This time line allowed me to equally divide the polls into two groups: pre-virus period and the virus period.

Among all 80 polls, Biden averaged 49% and Trump 43%, a six point lead for Biden. When I divided the polls into two groups, Biden’s and Trump’s pre-virus average was 50.2% and 43.8% respectively, or a 6.4% difference.

Among the virus period polls, Biden’s poll average was 48.4% and Trump was 42.7%, or a 5.7% lead for Biden. That’s a lead difference of 0.7% between the two virus periods.

It should be obvious at this point that the two-time frame polls were on average almost identical. That, however, doesn’t necessarily mean that the two groups, pre-virus and virus periods, aren’t different. Our interest here is Donald Trump’s polling and not Biden’s.

To prove that Trump’s two group means (virus and pre-virus) are different or the same, we need to test the observed variance in this variable and partitioned into components attributable to different sources of variation, which in this case is the handling of the Covid-19 crisis.

To do this, I’ll use a statistical technique called analysis of the variance (ANOVA), to determine if we have two different data means or basically both are the same. If the virus crisis has hurt Donald Trump, we would expect the two groups (pre-virus and virus periods) to differ. If the groups are the same, the variation would be nearly identical.

Our null hypothesis is that there is no statistical difference between the two groups. The table below shows the output from the ANOVA comparison of the two groups. The only value you need to note, is the significance level (Sig.) which is .606 which is not significant.

ANOVA
TRUMP.PRE.VIRUS
Sum of SquaresdfMean SquareFSig.
Between Groups84.083810.510.802.606
Within Groups406.3173113.107  
Total490.40039   

Since it is not significant (at the <.05 level) we can conclude that the null hypothesis is correct: there is no difference between the two groups and consequently, his handling of the crisis has not effected his polling against Biden.

A graphic representation of the two time periods and Donald Trump’s percent of the trial ballot question is shown below.


This graph tracks Trump’s virus and pre-virus percent in polls matched against Biden. His pre-virus average percent is 43.8% and during the virus period is 42.7%, a difference of 1.1%. Since the average margin of error for all surveys is +/-3.0%, this difference is just random noise.

So why do so many analysts believe the Covid virus is hurting his polling numbers? First, as I pointed out, many are relying on the single polling question of the voter’s rating of how well he is handling the crisis, which have been generally negative and automatically making the assumption it is hurting his Biden vs. Trump poll numbers.

In addition, there is tendency for people to focus on one or more survey results that show his numbers decl

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Florida, the Grand Grand Poobah of American Politics

May 20, 2020

From the state that brought you hanging chads, and elections so close that it sometimes takes days to find out who won, now comes the 2020 Presidential election mired in a pandemic using virtual campaign events with voters who don’t know what “virtual” means.

So starts another “Florid-Duh” spectacle between one candidate who now claims to live in Florida and another hold up in his basement in Delaware vying for the state’s 29 electoral votes.

So how close are Florida’s Presidential elections? In the last six elections, Republicans have won two elections, the Democrats have won two, and one race was a tie (Bush/Gore). The average percentage difference was 0.5%. No other state in the Union has ever achieved such a distinction. But that’s Florida.

With this in mind, let’s look at the latest state-wide polls. I have collected 11 independent surveys from January through May 12th. The average percentage difference of these polls is 3.09% to Biden’s favor. Seven of the eleven survey’s had Biden leading and Trump led in three. One was, of course, a tie.

It’s important to note, that the last poll that was conducted in this series, May 9th-12th, showed Biden with a six point lead. But remember, that one poll with this great of a difference requires confirmation and, until then, I wouldn’t take it as a trend.

MAY JANUARY

A better way to visually look at how the polls have fluctuated during the past five months is displayed above. The minus numbers reflect the percent lead that Biden has at the time period.

For example, Biden led Trump by 9 points in the middle of January. (Negative values show Trump losing.) But by the end of January, Trump led by 4 points. But as the polls moved toward May, the Biden’s lead continued to decline, until the last three surveys showed he led by 4, 3 and 6 percent.

Although he is still leading Trump, the difference is declining as we go through time. Even with the last survey’s 6 point lead, the trend in Biden’s lead narrows over time, at least for now.

In you don’t remember, Donald Trump in 2016 carried Florida by a whopping 1.2%, nearly a land-side in Florida election terms. Out of 67 counties, Trump won 59 of them. Clinton carried all the urban counties with the exception of a small county with a large African-American population.

Just to compare how similar or dissimilar these polls are to 2016, I have found 15 independent 2016 Florida polls, completed in the same time frame (January thru May).

The candidates, of course, were Donald Trump and Hillary Clinton. During this time period Trump’s polling average was 43.6% and for Clinton 45.1%, or a 1.5% lead for her, which is 1.6% less than Biden’s current average poll lead over Trump during the same time period. Below is a graphical representation of surveys in 2016 and 2020 over the same time period.

The blue line represents Clinton/Trump 2016 polls. The orange line tracks the 2020 polls for Biden and Trump. Since I subtracted Clinton’s poll results from Trump’s, it means that negative values are positives for Clinton. The same is true for the Biden vs. Trump, where negative values means the Democrat is leading. If the blue or red lines are below the zero line, it means the Democrat is leading in those surveys.

For example, looking at the Clinton/Trump blue line we see that in the first survey in January 2016 (11), she was running ahead of Trump by four (4) points. She increased her lead in the next survey, but at the end of April she fell behind him by seven (7) percent. But she bounced back in the very next poll. Overall, Trump led Clinton in five of these polls to Clinton’s seven.

What is interesting is how similar the two patterns (with a couple exceptions) are in the graph. This is especially true in the last three surveys for both Biden and Clinton. At this point in time (May) both Democrats’ polls are a mirror images of each other and their leads over Trump had narrowed considerably by May.

That Trump closed the gap over Clinton by the election shows that any lead Biden has now, could easily evaporate by November.

Although Florida has changed in the last four years, the percentage increase in Democratic registration since the 2016 is 5%. For Republicans it’s 6%. But that still gives the Democrats a plurality of 280,886 registered voters. (I’m ignoring independents in this analysis.)

Although this difference does not necessarily reflect changes in actual voters, it does show that Republicans now have slight advantage compared to 2016, if we assume that Republicans and Democrats will vote proportionally as they did in 2016.

The uniqueness of Florida for Republicans is highlighted by the fact that since 1928, no Republican presidential candidate has won the presidency without winning Florida. For Democrats, only two were victorious without Florida during that same time period.

In 2016, Hillary Clinton put considerable effort and money to defeat Donald Trump in Florida, but lost. Ironically, Trump still would have won the Electoral College if he had lost Florida. Go figure…

Doctor Politics Diagnosis: it’s too early to call and that advice will probably be the same on Election Day.

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Is Florida ready to open up the entire state?

May 15, 2020

On Monday, all of Florida will open its doors to the public on a limited phased approach. If the opening doesn’t lead to a spike in new Covid-19 cases, further reductions on restrictions are likely.

But is Florida ready for this experiment? According to most epidemiologists, there are three critical elements that are recommended for a state to open safely: substantial testing, extensive contact tracing, and a sustained reduction in daily new cases.

Let’s start with testing, since that is the most talked about requirement. On March 5th, Florida began a state-wide testing program. As of May, Florida has conducted a total of 561,057 tests or 2.6% of the state population (per capita). That equates to about 8,700 tests per day average. Some experts say that testing for Florida’s population should be closer to 32,000 tests per day.

But the number of tests maybe the wrong metric. The World Health Organization (WHO) says it’s not the number of tests that are key, but the percentage of new positive cases that matter. The WHO recommends that if a country has a positive test rate that is 10% or lower, they are conducting enough tests. If positive tests are over 10%, you aren’t testing enough.

This 10% rule is considered many epidemiologists the standard. So how does Florida look when we apply that WHO recommendation? The graph below shows that Florida is actually doing quite well.

This graph tracks the percent of new positive cases by date. The black line is the 10% level and when the red line drops below it, the number of positive cases has reached acceptable levels, which occurred around mid-April. As you can see, the red line has continued to drop. The last reading was at 7.3%.

In other words, the state is testing enough. That doesn’t mean the state can ease up, but it does mean it’s doing an acceptable job.

The most important measure for determining whether a state is ready to reduce restrictions is the daily number of new Covid-19 cases. The President’s Corona virus task force and the CDC recommended a 14 day continuous decline in new cases

Without this continuous reduction of new cases, the state has not yet contained the virus. Remember the virus spreads exponentially from person to person. This rate of spread is called the R0 (R Naught).

An a R0 number less than 1 means that an infected person is no longer spreading the virus and eventually the virus will die out. That’s what happened to the MERS virus, it just disappeared. There are multiple estimates for the R0 transmission rate, ranging from 1.9 to 3.5.

An R0 rate of 2.0 means every infected person can infect two other individuals. And those infected folks can infect another two people and so on. This creates an aggressive rise in the spread of the virus.

In the graph below, the red line tracks the daily number of new cases on a logarithmic scale, in this case the base 10. The data used here are the actual daily new cases (a linear scale), but transformed into a log10 value, that shows the rate of change of new cases which makes it much clearer because the rate of change rate is constant. Most importantly, for visual purposes it “smothes” out the data points.

The green line in the middle, is a reference line indicating the end of March when the number of new cases began to flatten out. From this point forward, the number of new cases bounced around, but in a slight downward movement.

The zig-zag movement indicates that in general the cases are going up and down at regular pace. In the graph below, the blue line with dots shows how up and down the new cases have been over the last nine days.

The first segment shows that the new cases declining for four days and then rising in the next four days. And the last case is down by only 6 cases. As I’m writing this, CNN is showing a map that has Florida’s new cases are declining. It hasn’t happened yet!

This pattern has been going on for several weeks. In other words, the state has not even come close to meeting the Federal guidelines. Florida is not alone in not having 14 consecutive days. Only a few have met this requirement.

Why does it matter? In general, it shows that Florida does not have control over the virus’s spread. Opening up at this point, could create a spike in new cases. Each new case can spread to two or more people and they can then spread it four more people and so on. This is called exponential growth and it doesn’t take long for it to get our of control.

So enjoy your new found freedom on Monday, but remember to wear your mask at all times and wash your hands as much as you can. Be safe…

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Pennsylvania has a long history of close elections. Will 2020 be an exception?

Most folks who aren’t American historians, don’t know that Thomas Jefferson beat George Washington in 1796 with 50.6% of the vote. And so began Pennsylvania’s long history of close presidential elections. Since 1980, the average winning percentage was 50.4%. Now that’s close!

Since 1980, six Democratic and four Republican presidential candidates have carried the state. Currently, all statewide elected officer are Democrats.

In 2016, Donald Trump won Pennsylvania over Hillary Clinton by 0.17% of the vote. By any way you look at it, Pennsylvania is a certified swing state.

So how does Joe Biden currently measure up to Donald Trump in the Keystone state? In 14 recent independent polls carried out since February, he as an average lead of 3.7%. Below is a graph of all 14 surveys over four months.

The blue line represents Biden’s poll percent (blue dot) and the red, of course, Donald Trump’s. There are only two surveys, both in March within a week of each other, that have Trump leading Biden during this period. And it’s only by 2% (italicized), as shown in the table below.

   BIDENTRUMP
4943
4747
5144
4237
4842
5042
4640
4547
4547
4341
4640
4445
4742
4645
5042

In addition, a Civiqs’ survey in Pennsylvania has Trump’s job approval at 44.4%. And all the Pennsylvania election polls in April, have Biden leading by an average of 5.4%, which is higher than his average for all 14 surveys by 1.7%.

So to recap, Pennsylvania elected state officers are all Democrats, Trump’s current job approval rating is a net negative of 7%, and Trump trails Biden by an average of 3.7%.

All that would suggest Biden has a significant edge in the state except for one thing: Pennsylvania historically is the Mother of all close elections.

Doctor Politics Diagnosis: History says it’s too close to call.

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Can Biden win back Wisconsin?

Since the mid-20th century, Wisconsin has had a reputation for leaning toward Democratic presidential candidates. Since 1984, when Ronald Reagan won every state but Minnesota, the state has voted Democratic until Donald Trump’s 2016 victory over Hillary Clinton by less than .8%.

But the Democratic advantage at the Federal level, is starting to show it’s age. In both 2000 and 2004, Al Gore and John Kerry’s victory’s were quite close, but Barack Obama seemed to bring it back to life with a 56% win over John McCain.

Currently, the state’s all five executive offices are Democrats, and all but one were elected since the 2016 Presidential election.

Today, Wisconsin is the poster boy for swing states. So how will Joe Biden do against Donald Trump in 2020? In any attempt to predict the future you need to look at the immediate past. In the chart below, I’ve traced the two candidates percent in each of the 18 polls since January through April 2020.

This is a terrible chart for displaying election results, but it emphasizes how entangled the poll results have been in such a short period of time. (Note: the dates start on the left side of the chart).

Biden (blue) starts out with a lead but soon loses it to Trump. Then Biden pulls ahead and Trump falls back. And so on and so on…The Chart below is a better visual display of how close this race was during the last four months.

After 18 different independent polls, the margin of between the two candidates is just 1%. The average percent for Biden is 45.6% and 44.6% for Trump. I have seen many close polls in my career, but never have I seen 18 different surveys with so little difference.

That said, the last five surveys, all completed in April have Biden leading by an average of 3%.

An additional metric is the presidential job approval rating. According to Civiqs latest survey, Donald Trump’s Wisconsin approval rating is 46% and disapprove is 51%. Morning Consult had Trump upside down by 10%.

So this is what we have in Wisconsin: the latest statewide elections all went Democratic, Trump’s approval rating is terrible, Trump has the edge on incumbency and finally, we have 18 recent independent surveys showing it is a virtual tie. This should be an easy decision, right?

Let’s break it down. Partisan statewide elections are not a particularly good indicator for Presidential elections. Job approval ratings are only good at predicting winning or losing when measured right before the election. And finally, polls become more accurate as we near the election date. That the last five surveys that have Biden leading, could possibly be a harbinger of polls ahead. We will have to wait to see.

Doctor Politics’ Diagnosis: Too close to call for now. We will have to wait for the early summer polls to make a call on this very close race. Stay tuned.

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The Battle for the Big Four: Michigan, Pennsylvania, Wisconsin and Florida

We have about six months before the nation faces one of the most consequential elections since the Great Depression. With a country politically polarized, an pandemic killing thousands of Americans, and an economy on the brink of collapse, this election will decide how the nation will face this crisis over the next four years.

“All States are equal, but some States are more equal than others.” (Apologies to George Orwell)

Political scientists and political commentators seem to have settled on thirteen states that they classify as a swing states: WisconsinPennsylvaniaNew HampshireMinnesotaArizonaGeorgiaVirginiaFloridaMichiganNevadaColoradoNorth Carolina, and Maine.

This post is the first of a series on key presidential swing states. In this post, I will look at Michigan and follow up with analysis on Pennsylvania, Wisconsin and Florida.

These four states combined account for 75 Electoral votes and have a history of close elections and a tendency for voting both Democratic and Republican Presidential candidates.

Michigan

In 2016, Donald Trump won Michigan’s 16 Electoral votes with 47.25% to Hillary Clinton’s 47.03%. In the past six election cycles the state has chosen two Republicans and six Democrats. It’s clearly an equal opportunity state for both Biden and Trump.

I have collected 14 independent Michigan polls from January through April of this year that included the presidential match up between Biden and Trump. On average of all the polls, Biden leads Trump 47.3% to 42.5%, with an average lead of 4.8%.

In the graph above, two lines represent the percent for each candidate over this 14 poll period. The blue line is Biden’s percent and the red line Trump. Notice that in the beginning of the year, Biden started out ahead, but his lead dropped and eventually recovered. All poll results are listed below.

BIDENTRUMP
5042
4943
4941
4536
4638
5041
4646
4845
5044
4742
4441
4446
4541
4841
4446
4343
4743
4743
5044
5144
5043

Only one survey during this period gave Trump a plurality and it was only by 2% (italicized). Using multiple surveys allows for averaging out the statistical error. Almost as important, is having multiple surveys from different pollsters which helps eliminate bias. If you want a good idea of who is leading, in polling more is always better.

Another way to measure Biden’s advantage in Michigan is subtracting one poll question from another. This is called the lead difference. In the chart below, Biden’s net percent average lead was 4.8%.

In the first poll (1.07), Biden started out with a 7% advantage, but after that his lead started to deteriorate until the March 7th survey shows Trump had was leading by 2%.

But surprisingly, after this point Biden’s poll numbers started to improve in almost every other survey there after. So what happened? The only explanation I have (with no empirical evidence) is Covid-19.

Notice that beginning on March 16th, Trump’s begins to loose ground and Biden has bigger gains. It was in the beginning of March that the Covid cases began to explode. And Trump’s percent of the survey vote, deteriorated quickly. Unfortunately, I can’t confirm this hypothesis at this point because I don’t have Michigan Covid case data as of yet. But I will soon.

Politic’s Doctor Verdict: Biden likely win. Trump won the state in 2016 by the slimmest of margins but this years polling shows he has consistently fallen behind Biden. With the campaigns frozen in time, he will need a lot of help from Biden to win the state again.