This is a technical piece about the meaning of a type of polling. It is not political in favor of or against President Trump. I will remove any political comments.
What are presidential approval polls?
Presidential approval polls are a simple concept to grasp: do you approve or disapprove of President X? Because newspapers and TV channels can always use them for a headline or an on air-segment, they love to commission them. During President Trump's presidency, I counted 16,500 published approval polls.
But what do these polls mean and how should we interpret them? As it turns out, understanding what they're telling us is slippery. I'm going to offer you my guide for understanding what they mean.
My data comes from the ever-wonderful 538 which has a page showing the approval ratings for President Trump. Not only can you download the data from the page, but you can also compare President Trump's approval ratings with many previous presidents' approval ratings.
Example approval results
On 2020-10-29, Fox News ran an approval poll for President Trump. Of the 1,246 people surveyed:
- 46% approved of President Trump
- 54% disapproved of President Trump
which seems fairly conclusive that the majority disapproves. But not so fast. On the same day, Rasmussen Reports/Pulse Opinion Research also ran an approval poll, this time of 1,500 people, their results were:
- 51% approved of President Trump
- 48% disapproved of President Trump.
These were both fairly large surveys. How could they be so different?
Actually, it gets worse because these other surveys were taken on the same day too:
- Gravis Marketing, 1,281 respondents, 52% approve, 47% disapprove
- Morning Consult, 31,920 respondents, 42% approve, 53% disapprove
Let's plot out the data and see what the spread is, but as with everything with polls, this is harder than it seems.
Plotting approval and disapproval over time
Plotting out the results of approval polls seems simple, the x-axis is the day of the poll and the y-axis is the approval or disapproval percentage. But polls are typically conducted over several days and there's uncertainty in the results.
To take a typical example, Global Marketing Research Services conducted a poll over three days 2020-10-23 to 2020-10-27. It's misleading to just plot the last day of the poll; we should plot the results over all the days the poll was conducted.
The actual approval or disapproval number is subject to sampling error. If we assume random sampling (I'm going to come back to this later), we can work out the uncertainty in the results, more formally, we can work out a confidence interval. Here's how this works out in practice. YouGov did a poll over three days (2020-10-25 to 2020-10-27) and recorded 42% approval and 56% disapproval for 1,365 respondents. Using some math I won't explain here, we can write these results as:
- 2020-10-25, approval 42 ± 2.6%, disapproval 56 ± 2.6%, undecided 2 ± 0.7%
- 2020-10-26, approval 42 ± 2.6%, disapproval 56 ± 2.6%, undecided 2 ± 0.7%
- 2020-10-27, approval 42 ± 2.6%, disapproval 56 ± 2.6%, undecided 2 ± 0.7%
We can plot this poll result like this:
Before we get to the plot of all approval ratings, let's do one last thing. If you're plotting large amounts of data, it's helpful to set a transparency level for the points you're plotting (often called alpha). There are 16,500 polls and we'll be plotting approve, disapprove, and undecided, which is a lot of data. By setting the transparency level appropriately, the plot will have the property where the more intense the color is, the more the poll results overlap. With this addition, let's see the plot of approval, disapproval, and undecided over time.
Wow. There's quite a lot going on here. It's hard to get a sense of changes over time. I've added a trend line for approval, disapproval, and undecided so you can get a better sense of the aggregate behavior of the data.
Variation between pollsters
There's wide variation between opinion pollsters. I've picked out just two, Rasmussen Reports/Pulse Opinion Research and Morning Consult. To see the variation more clearly, I'll just show approvals for President Trump and just show these two pollsters and the average for all polls.
To state the obvious, the difference is huge and way above random sampling error. Who's right, Rasmussen Reports or Morning Consult? How can we tell?
To understand what this chart means, we have to know a little bit more about how these polls are conducted.
How might you run an approval poll?
There are two types of approval polls.
- One-off polls. You select your sample of subjects and ask them your questions. You only do it once.
- Tracking polls. Technically, this is also called a longitudinal study. You select your population sample and ask them questions. You then ask the same group the same questions at a later date. The idea is, you can see how opinions change over time using the same group.
Different polling organizations use different methods for population sampling. It's almost never entirely random sampling. Bear in mind, subjects can say no to being involved, and can in principle drop out any time they choose.
It's very, very easy to introduce bias by the people you select, slight differences in selection may give big differences in results. Let's say you're trying to measure President Trump's approval. Some people will approve of everything he does while others will disapprove of everything he does. There's very little point in measuring how either of these groups approves or disapproves over time. If your group includes a big measure of either of these groups, you're not going to see much variation. However, are you selecting for population representation or selecting to measure change over time?
For these reasons, the sampling error in the polls is likely to be larger than random sampling error alone and may have different characteristics.
How accurate are approval polls?
What about averaging?
What about aggregating polls? Even this isn't simple. In your aggregation:
- Do you include tracking polls or all polls?
- Do you weight polls by their size?
- Do you weight polls by accuracy or partisan bias?
- Do you remove 'don't knows'?
- If a poll took place over more than one day, do you average results over each day the poll took place?
I'm sure you could add your own factors. The bottom line is, even aggregation isn't straightforward.
What all this means
Is Rasmussen Reports more accurate than Morning Consult? I can't say. There is no external source of truth for measuring who's more correct.
Even worse, we can see changes in the Rasmussen Reports approval that don't occur in the Morning Consult data (and vice versa). Was the effect Rasmussen Reports saw real and Morning Consult missed it, or was Morning Consult correct? I can't say.
It's not just these two pollsters. The Pew Research Center claims their data, showing a decline in President's Trump approval rating at the end of his presidency, is real. This may well be correct, but what external sources can we use to say for sure?
What can I conclude for President Trump's approval rating?
Here's my takeaway story after all this.
President Trump had an approval rating above 50% from most polling organizations when he took office. Most, but not all, polling organizations reported a drop below 50% soon after the start of his presidency. After that, his approval ratings stayed pretty flat throughout his entire presidency, except for a drop at the very end.
The remarkable story is how steady his approval ratings were. For most presidents, there are ups and downs throughout their presidency, but not so much for President Trump. It seems that people made their minds up very quickly and didn't change their opinions much.
Despite the large number of approval polls, the headline for most of the last four years should have been: "President Trump's approval rating: very little change".
What about President Biden?
At a guess, the polls will start positive and decline. I'm not going to get excited about any one poll. I want to see averages, and I want to see a sustained trend over time. Only then do I think the polls might tell us something worth listening to.
If you liked this post, you might like these ones
- Forecasting the 2020 election: a retrospective
- What do presidential approval polls really tell us?
- Fundamentally wrong? Using economic data as an election predictor - why I distrust forecasting models built on economic and other data
- Can you believe the polls? - fake polls, leading questions, and other sins of opinion polling.
- President Hilary Clinton: what the polls got wrong in 2016 and why they got it wrong - why the polls said Clinton would win and why Trump did.
- Poll-axed: disastrously wrong opinion polls - a brief romp through some disastrously wrong opinion poll results.
- Who will win the election? Election victory probabilities from opinion polls
- Sampling the goods: how opinion polls are made - my experiences working for an opinion polling company as a street interviewer.
- The electoral college for beginners - how the electoral college works
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