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Will the Economy Save Donald Trump?

Will the economy make up for President Trump’s lackluster Job Approval ratings come November 2020?

After you brewed you morning coffee, many of you went on-line to check the latest updates on Washington’s political news. I know this because that’s what I do every morning. (My wife says I need to get a life. And she’s right, but my addiction is too far gone.) In this morning ritual, I undoubtably check Real Clear Politics’ latest polls, but the one I’m most interested in is the daily Trump Job Approval numbers.

In modern American elections, there is no more ubiquitous statistic than the President’s current job approval percent. Almost every day after a Presidential election, at least one polling company releases their latest results. In 1937, George Gallup created this simple question: “Do you approve or disapprove of the way (NAME) is handling his job as president?”

The original concept of the approval question rested on the theory that the president was the CEO of the country and that a simple and easily understood question would best gauge the county’s “impression” of how well the president was running the business of government. Today, most academics refer to the approval rating as a popularity measure and not a specific indication of how voters think the President is running the business of running the country.

Since Donald Trump was elected in 2016, there have been 1,014 surveys that asked the Presidential Job Approval question. His rating has ranged from a low of 32 percent approve, to a high of 57 percent, with an average approval rating of 45.2 percent during his two years and 360 days in office. As of this writing, that means pollsters have completed almost one survey a day since Trump said, “I swear.”

His average Approval Rating of 45.2%, qualifies him as having the lowest average rating of any first term president since Gallup started asking this question, with the exception of Jimmy Carter who had an average first term rating of 45%.

Since World War II, not a single incumbent presidential candidate has won re-election with a job-approval rating below 50 percent.

The Trump campaign understands that his Job Approval rating is a problem for the upcoming 2020 election, but they are hanging their strategy on the economy. The major talking point for Trump and all his supporters is the economy and not the polls.

Conventional wisdom supports the theory that the president is reelected when the economy is good and loses if it’s bad. And some academic studies seem to support this theory in part, that the economy predicts who wins or loses. The important question is what part of the economy matters most in helping Trump offset his lagging Job Approval ratings, if any?

Will the economy make up for President Trump’s lackluster Job Approval ratings come November 2020?

To determine that, we need to find economic measures that have a significant effect on presidential elections. Most political analysts have focused a three important economic measures that effect political outcomes: GDP growth, inflation, and unemployment.

Using linear regression (OLS) we can measure the impact of each economic variable on each Presidential election since 1972, such as the GDP growth rate, on the incumbent’s (or his party) two-party share of the vote .

For those statically inclined, I have included the models coefficients in the Table below. Of the five economic variables only three are statistically significant (denoted by *): Job Approval, nominal GDP growth and per carpita GDP. (GDP growth rate is significant at the <.08 level). When a variable is not significant it means that it has no correlation (no impact) on the dependent variable, which in this case is the two-party share of the vote. A variable is considered significant at the <.05 level. Some researchers include levels <.10, when the sample is small. Consequently, I’ve included GDP growth rate which is <.075.

Model Coefficients

  Unstandardized  Coefficients          B   Standard Error   Beta   Significance
Constant 55.78 12.047   .004*
Job Approval .327 .085 .783 .008*
GDP Growth Rate .-1.3 .623 -.465 .075*
Per Capita GDP -.003 .001 -.485 .025*
Unemployment -.176 -.047 -..039 .816
Inflation -.237 *.149 -.231 .499

In plain terms, unemployment and inflation have no effect (non-significant) on the President’s percent of the two-party vote, even as the he touts the “lowest unemployment figures ever.” No matter how good the unemployment numbers are (and they are), it won’t help him in November.

Consequentially, I have dropped both inflation and unemployment from the model. Without these two non-significant variables included, the Rsq. for the model is .887, or almost 90% of the model variance is explained by the remaining variables. The Beta coefficient shows that the Job Approval rating has far more impact on Trump’s percentage of the two-party vote than any other variable.

Below is a graphic representation the model’s final estimate for each election since 1972.

Each circle above the red line represents an incumbent (or Party’s) victory and, of course, the circles below a defeat. The model’s estimate of all 12 election’s percent of the two party-vote is off by less than three-tenths of a percent.

Using this simple equation, we can estimate what President Trump’s percentage of the two party vote using his current Job Approval rating, GDP growth rate and a per capita GDP, if the election were today.

Can Donald Trump Win?

The equation is simple: Vote Percent = Constant + Job Approval + GDP percent growth. When we insert Trump’s current Job Approval (45%), and latest GDP growth rate (1.6%) and GDP per capita we get the final equation:

(1) 50.2 + .372 (Job Approval) + (-1.4) x (GDP Growth rate)+ -.003 (Per Capita GDP)

(2) 50.1 + (16.74) +(-2.3) + -16.4 = 48.01%

Simply put, if the election were today, with the President’s current Job Approval of 45% and a GDP growth rate of 1.6% and a per capita GDP of $5463,Trump’s share of the two party vote would be 48%. In other words, today’s economy improves Trump’s vote by about 3%.

If President Trump can raise his Job Approval rating to 48%, his percentage of the two-party vote would 49.3%, increasing by only 1.3%. As his approval rating rises, the economic impact on the popular vote decreases as well, until he reaches 50%, when good economic numbers no longer effects his percentage of the two-party vote. In other words, a 50% approval rating is his Holy Grail.

How Accurate is this Election Model?

We can’t, obviously, measure the actual accuracy of the model’s estimates until after the 2020 election (which I will). But we can test the model’s accuracy against the past 12 presidential elections. When we do, the model estimates the actual percentage of all 12 elections cycles within an average difference of only .19%, which is graphically shown in Chart 9.

Chart 9

The two lines represent the actual vote percent (Blue) and the Model’s estimate (Red). The two images are nearly a mirror image of each other. As visually shown in the chart, the model is a very good fit for the data.

Professor Ray Fair’s January presidential model predicts Trump will win with 54.4% of the two-party vote. Fair’s model relies only on economic data and does not include Trump’s job approval rating in his equation. It also incorporates data back to 1918. His economic models have a good track record, but in 2016 his estimate was off by 5.4%.

Its important to note that the Job Approval rating has short shelf life, and predictions based on it more than two months prior to the election are less likely to accurately measure the two-party vote, even when controlling for the economy.

In addition, this model only applies to the popular vote and not the Electoral College. In modern times, the Electoral College usually mirrors the popular vote. But in the last two decades the popular vote deviated from the Electoral College vote in two key elections: George W. Bush in 2000 and Donald J. Trump in 2016.

I will address the Electoral College vote in a future post. This model, however, does not predict the Electoral College vote.

This Model also predicts the outcome without the the challenging Democratic candidate or the campaign each wages. (There is some evidence that candidate quality does effect the outcome somewhat.)

Political scientists have been predicting presidential outcomes for years with mixed success. After teaching graduate level political science courses for many years, I believe campaigns still matter, but not as much as pundits would have you believe. Each campaign takes place in an environment that is predicated on the political and economic environment.

But there are fundamental elements that shape every election that campaigns and candidates cannot change. Some candidates and campaigns are doomed from the start, as Jimmy Carter can attest to. But many presidential election campaigns can and do have some impact on the outcome. But an incumbent facing a recession headwind, knows the odds of winning are small.

So the question we started with: can the economy put Trump over the finish line even with a Job Approval rating below 50%? The answer is probably not. There is a reason why no incumbent President since World War 2 has never won re-election without an approval rating 50% or higher.

But even with a lagging approval rating this race is likely to be very close. Close enough for a replay of 2016, where Donald Trump carried the Electoral College while losing the popular vote. I will address this possibility in a future post.

When election day arrives, do what mother taught me: vote early and often!

One reply on “Will the Economy Save Donald Trump?”

In my opinion, the typical polls/surveys/theories that have been used in the past for political predictions are flawed when using same for Trump. I believe the flaw is due to not factoring in the demographic value of the Trump supporters that, as a large group, do not respond to surveys or polls, they simply know that they will vote for Trump. Sometimes, human nature is so simple that it is overlooked, as a society, we seem to analyze the models, make predictions based on the science of intense graphs and ignore the obvious which is…the same people that participated in the surveys and polls of 2016 (and we see how well that went), are very likely the same folks responding to the surveys and polls for 2020.

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