## Debunking the “Republican Congress Creates Jobs” Chart Or “How To Make Numbers Say Anything You Want”

This is a companion piece to the previous post, so please read both of them. Here I’m going to lay out the script I had written for debunking the chart I created that asked the question “Does a Republican Congress Create More Jobs?” and then implied with a chart that this was indeed the case. I’ll walk through some process for creating charts and then talk about why I would create a chart that I was just going to debunk.

I apologize for the similarity to the post where I debunk the Obama stimulus chart. These two scripts were meant to be together.

<Start Script>

## How to Make Number Say Anything You Want

Do you want to convince people that your side is right with only the flimsiest proof? Does the idea of tricking people with numbers make you all happy inside? Then come join us as we walk through “How To Use Charts To Say Anything”

### Step 1: Massaging the Data

The first step is to grab the data that makes your point the best. Let’s use it to prove that a Democratic Congress is bad for jobs.

“How can we do such a thing” you ask?

In the first case, the raw jobs data looks like this

but the final chart looks like this.

How did they do that? Was it magic?

Nope, we simply smoothed the data. The raw data is a little too chaotic and has too many data point to tell the straightforward story that we want. So instead, we’ll average the monthly data so that we have quarterly data. There… now we have some nice smooth straightforward data

### Step 2: Pick colors that make you look good

Next, we pick some colors. Let’s make the Democrats blue dark and bold, give it a bit of an angry feel to it. This is our way of getting the audience to look at the democrats in a harsh way. We could try to soften up on the Republicans more, but too soft of a red would look pink and we don’t want that.

Let’s compare our colors to the Excel defaults:

### Step 3: Do NOT give any context!

Finally, and this is the most important part, only give information that is helpful.

Let everyone know that we saw 8 million jobs added to the economy while the Republicans were in charge and make a point to show that we lost 8 million jobs while the Democrats were in charge. But don’t mention that the Republicans took Congress only a year after 9/11 at a time when the job market was particularly low. Otherwise people will think it’s a “Well, they can’t fall off the floor” thing.

And make sure you don’t mention anything about the real estate market and how the bubble drove the labor market in a way that was clearly unsustainable. We don’t want the viewers to be confused with all these relevant details. We want them to say “Republicans good, Democrats bad”.

<End Script>

Everyone here was incredibly kind to put up with my bullshit chart for as long as I left it up without explanation. I’d like to say unequivocally: My chart is propaganda… just like the Obama administration’s chart. I was trying to use my chart as a visual talking point that said:

### If you have no ethical qualms, data visualizations can be manipulated to say exactly what you want them to say.

My chart implies that the Republicans were responsible for the jobs growth between 2003 and 2007 and that Democrats were responsible for the drastic decline from 2007 to the present. Let me state plainly, I do not think that is the case.

But if we just play around with the data the right way, we get what seems to be a clear picture that portrays a correlation and gets on its hands and knees and begs us to draw causation from it. Most people will do exactly that.

I can spend hours walking patiently through what is wrong with the Obama administration’s chart. Let me recap the high points here:

• If you look at the data with the context of what President Obama’s team was hoping the stimulus would do, the power of the chart disappears.
• If you look at the data with the understanding that they’re charting a first derivative, you realize that we haven’t gained jobs, we’re just losing them more slowly and the power of the chart disappears.
• If you look at the data with the understanding that they didn’t even start spending the stimulus until the job loss had started slowing down, the power of the chart disappears.
• If you look at the data in the context of other recessions, you’ll realize that, far from showing a drastic improvement, the numbers represent a devastatingly slow jobs recovery compared to other recoveries and the power of the chart disappears.

But this kind of explanatory rebuttal would interest those already convinced. The chart I made had a power that an calm explanatory video wouldn’t have. Quite frankly, I hate that this is the case. Like President Obama’s chart, my chart doesn’t teach people anything about economics or lead people to learn important things about unemployment.

The only valuable thing my chart teaches is that charts can portray accurate data and still be manipulated to coach people along to poor conclusions. The only reason I even put my chart up is because it is the graphical equivalent of drawing out the Obama administration’s argument to its logical conclusion. My chart works with the same data, the same assumptions, and the same implications. And it leads to a completely different conclusion.

I’ve heard people describe President Obama’s chart as “powerful” and “brilliant”. The popular information visualization blog Flowing Data even tossed it up for public discussion among info viz professionals.

My point here is that it isn’t brilliant. It’s juvenile. It’s the chart equivalent of a crass political cartoon with a Snidely Whiplash mustache drawn on the bad guys. It’s a design trick imagined by cynical, self-congratulatory children fresh out of graduate school who pat themselves on the back for their ability to fool people who they think are too stupid to know the difference. They think they are special because they can get powerful people to flatter them for their ability to lie.

But they aren’t special. I can play that same childish game in my free time. The difference if that I want people to know that it’s a trick. They would rather see people fooled.

## Debunking the Obama Stimulus Chart Or “How To Make Numbers Say Anything You Want”

I’ve been trying to find the time to make a video for this, but the fact of the matter is that I’m simply too slammed with all my work (I have a huge conference in two days). And I’m really kind of sick of my chart that I put up with basically no explanation. I basically created my chart as a rebuttal to this chart put out by the Obama administration. In this post, I debunk the Obama chart. In the next one, I debunk my own.

I’m basically just going to dump the script that I had written. Imagine my voice with some happy visuals that I don’t have time to make. I’ll add some additional comments at the end. Imagine a sing-song snake-oil salesman. That was what I was going for.

<Start Script>

## How To Use Charts To Say Anything

Do you want to convince people that your side is right with only the flimsiest proof? Does the idea of tricking people with numbers make you all happy inside? Then come join us as we walk through “How To Use Charts To Say Anything”.

### Step 1: Massaging the Data

The first step is to grab the data that makes your point the best. Let’s use it to prove that a Democratic president is good for jobs.

“How can we do such a thing” you ask?

Let’s grab some raw jobs data. We’re going to take this data

and make it look like this:

How did we do that? Was it magic?

Nope, it’s called the first derivative. It works like this. Instead of worrying about how high the line is, we’re only going to worry about how steep the line is. That way, the number will look good even if we keep losing jobs. Instead of charting how many jobs there are, we’re charting how many jobs we’re still losing.

That turns the first chart (which looks bad) into the second chart (which looks good).

### Step 2: Pick colors that make you look good

Next, we pick some colors. We could pick the default colors that Excel gives us when we chart two different kinds of numbers. But that’s too neutral. By way of comparison:

As you can see, we’ve taken the default red (for George Bush) and made it darker and richer. This is like drawing a Snidely Whiplash mustache on him so that we know he’s the bad guy. Then, we’ll make the President Obama blue lighter and softer so we know he’s the good guy.

### Step 3: Do NOT give any context!

Finally, and this is the most important part, only give information that is helpful. And by helpful, I mean favorable to your side.

It’s OK to mention that President Obama signed the stimulus bill into law in the first quarter of 2009.

It’s not OK to mention that the initial stimulus reports from the first and second quarter were totally blank, which means that they didn’t really start spending the money until July.

Also, you should forget to mention that as of December, we’ve only spent 10% of the stimulus money.

If you give all of this unhelpful information, people might draw the conclusion that the stimulus didn’t really help very much.

Remember, we’re not interested in helping people understand the complexities of the economy. We just want them to look at the chart and say, “Bush bad. Obama good.”

<End Script>

I got my numbers for the last part of this from the stimulus reports on recovery.gov. Since I started looking at the data back in late 2009, they’ve changed the way they organize the data. Until a little over a month ago, the reports for 2009, Q1 and 2009, Q2 were blank. Zero data. Nothing. In the 2009 Q3 data they reported giving out about 4% of the stimulus money. By the end of 2009 Q4, they had reported giving out 10% of the simulus money.

Since then, they took the empty Q1, Q2 and the actual Q3 data and relabeled the file so that the Q3 data now says “February 17 – September 30, 2009”. There is no way to tell for certain when the money was sent out, but the amount of money marked as “recieved” ran on a curve that was about 4 months off. (Example: Most of the money that was marked as “recieved” was applied for in March, April and May. Very few places that applied for money after May marked it as recieved by the end of September. So…we see job losses slowing even before the money was making it out the door.

OK. Now to talk about my rebuttal chart and a well deserved explanation. I have the greatest readers of all time and many of you have pointed out that my rebuttal chart (seen here) commits many of the same fallacies that the Obama chart has.

My response to that would be “Yes it does. It was meant to.” I created that chart as the visual equivalent of saying “If your logic is correct, than you would be forced to accept this other conclusion as well since it uses the same logic.”

Both charts use jobs data taken from the same place, displayed the same way, stripped of context and used to push an ideological point using an implicit “correlation mean causation” line of argumentation.

Let me be clear: I do not think that a Republican Congress is the driving factor behind 8 million jobs created and I would NEVER say that. But I would say “Your chart implies that Obama is responsible for the slowing of job loss. If that is your argument, I would like to use the same chart logic to say that we need a Republican Congress to regain those jobs. By your own argument, you should be voting Republican this November.” I meant my chart to be a sort of visual rhetorical trick to be played in the context of the Obama stimulus chart to show that the numbers can be spun in either direction.

## President Obama, I Fixed Your Chart For You

You may have recently seen the new chart put out by the Obama administration pushing the idea that the President’s policies are responsible for the decrease in newly unemployed. It looks something exactly like this:

Now… as a piece of visual political propaganda, this is brilliant. The colors draw sharp contrast, the symmetry is appealing. And the numbers are right.

But keep in mind how carefully I phrased the units being used “decrease in newly unemployed”. This isn’t an increase in jobs or a decrease in unemployment. It just means that we’re losing jobs slower that we were before.

Make no mistake… this is good news. And we can bicker back and forth as to whether President Obama’s policies are responsible for this slowdown in newly lost jobs. He would say yes and point to the stimulus.

But in order to point effectively to the stimulus, we would have to take a look at the expectations of the stimulus. Everyone expected that we would come out of the recession eventually and that job loss would slow. The question was how quickly that would happen.

To help us visualize the expectations of the stimulus against the reality of it, I’ve added that piece of context to the graph. See if you can spot it.

I got these numbers by multiplying the labor force by the expected unemployment rate with the stimulus (per this chart) and then subtracting that number from the labor force times the actual unemployment rate.

One may say that this is unfair. I would actually kind of agree. Economic predictions are pretty hard to make. But the original chart is similarly unfair. Keep in mind that it took a few months to get the stimulus money out the door. In fact, they didn’t even release any data on the stimulus funds for second quarter 2009 (the first stimulus report was for third quarter 2009).

Side Note: This data has actually been scrubbed from the website. They’ve re-compiled the data into new categories. But I’m wary about trusting the data since it looks like, according to the official data, about \$12 billion of the stimulus was spent before the stimulus was signed with projects being approved as early as 2000.

So the first several months of decline don’t even reflect the impact of the stimulus. The decline in new job losses seems to be just a happy coincidence that looks good on a chart.