Archive for unemployment

Romney, Obama, and Executive Job Records

This is one of the Goose/Gander Visualization Series.

Recently President Obama’s team has felt that attacking Romney’s jobs record in Massachusetts tests well in the sample group.

These attacks got me thinking about executive job records.  “Where” I asked myself  “would President Obama place in a ranking of US Presidents in terms of job creation?”

Job Gains By Presidential Tenure Medium

You can also download a larger version of the chart. I find it difficult to create visualizations that work well in both blog form and Facebook-sharing form. This was my attempt at a compromise.

Is this a fair comparison? Yes and no. Part of the Goose/Gander series is that I create a provocative visual and then explain in more details what is fair and isn’t fair about it.

This Isn’t Fair

President Obama hasn’t had a full term yet

This puts him at a distinct disadvantage to everyone else (except John F Kennedy) because he hasn’t had the same amount of time to grow jobs. However it also seems pretty obvious that he’s not going to get out of last place before January 2013. That would require 300K new jobs per month every month from now until then.

President Obama came into office in the middle of a recession

In fact, he came in the middle of a recession that was worse in terms of job loss than anything any other president in this chart had to deal with. Now, he did split those job losses about half-and-half with George W Bush, so it’s not as bad as it could have been for him.

Presidents only have a certain amount of control over job growth

Actually presidents (and executives in general) only have a certain amount of control over the economy, so this entire exercise is kind of tainted by that fact. But this is the part where we point out that Obama did start this by attacking Mitt Romney’s job record in a similar way.

This Is Fair

The data Is Unassailable

I’m using the Employment table from the BLS A Tables. This is not the one that most Obama proponents prefer to use. They prefer using the BLS B Tables because they give numbers that are kinder to Obama. But the B Tables undercount employment (they only count payrolls) and everyone knows this.

I counted January-January (or whenever the president left office) for each president. I did this not because it was particularly fair but because I wanted to match how Obama has assigned himself and Romney jobs responsibility. I’m following his lead to show that, if we take him at his word, he doesn’t stand up to his own standard.

If we’re going to play the presidential job visuals game…

… this is a totally fair visual to keep in mind. Depending on the metric, Obama talks about jobs in different ways. When talking raw numbers, he likes to talk about the “last 22 months” or however gets us to the low point in the recession. When talking about month-to-month change, he likes to talk about when he came into office which was the worst point of job loss in the recession, so everything else looks good in comparison.

Fairly or unfairly, Presidents and jobs are commonly linked. It’s only fair to give a proper representation of that information.

Is the Labor Force Shrinking Due to Boomer Retirement? (Not Mostly)

Every month when the BLS releases the employment report, I dig into the data and tweet about it at length using the hashtag #BLSFriday. (Follow me on Twitter to catch this incredibly exciting data dive. The next one is on June 1st.)

If you’ve been following the job numbers closely, you’ll know that this recession we’ve seen a particularly sharp drop in labor force participation. Labor force participation measures how many people either have a job or are looking for a job as a percentage of the population. As of March 2012 labor force participation has dropped to 63.6%, the lowest point since December 1981.

Because the unemployment rate doesn’t measure people who aren’t in the Labor Force, many (especially conservatives) have noted that the unemployment rate is “artificially” low and that many have left the labor force, basically giving up even looking for a job.

One Twitter friend, @rizzuhjj, pointed out that the Chicago Fed has a paper that claims that half of the post-1999 decline in the labor force is due to long-term demographic trends, specifically, Baby Boomers aging.

Here is a chart of the labor force participation rate since it the last time it was this low. You can see that we’re at the point where Boomers are starting to retire, so surely that would be driving the massive drop in labor force participation and not due to the recession, right?

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To test this, I decided to sift through the employment data by age, as provided by the BLS. In January 2008, the participation rate by age looked like this (click to enlarge).

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(The outline is a rough approximation of where Baby Boomers land in the data. Which is OK because the Baby Boomers are an approximate age group anyway.)

You can see that the boomers are largely entering the age ranges where participation in the labor force drops off significantly. So, on the surface, this explanation makes sense.

This was my test: Take the participation rates for post-Baby Boomers (16-49 year old) and multiply them for the corresponding populations for those ages. That way we’ve isolated just the post-Baby Boomer labor force and can see if it is smaller now than it was 3 years ago. This is what I found.

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Or, to make it a little clearer, this is the change in labor force participation by age since January 2008.

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Apply the January 2008 participation rates to current population and this means we are missing 3.4 million post-Baby Boom workers from the labor force. These post-Boomers account for 68% of the “missing” work force.

If labor force participation was dropping only due to Baby Boomer retirement, the rate should have dropped from 66.2% in January 2008 to 64.8% today. Instead, it is 63.6%. There is certainly a good deal of room for improvement to get younger people back into the labor force. We shouldn’t simply push the problem off to being Boomer retirement or we risk ignoring a whole generation that is unemployed and flying under the radar.

How To Read Unemployment Reports

Every time a national unemployment report comes out, I tweet the many details from @politicalmath. Frequently I get a lot of the same questions, so I thought I’d jot down a quick summary on unemployment reports and numbers and where they come from.

There are 2 kinds of employment numbers, summarized here:

  1. Establishment Data (Current Employment Statistics or CES) – this survey covers 400,000 businesses and counts the number of payroll positions that are filled.
  2. Household Data (Current Population Survey or CPS) – this survey covers 60,000 households and counts the number of people who are employed and unemployed.

When an employment report comes out from the Bureau of Labor Statistics (BLS), they usually report:

  1. The unemployment rate, which is calculated using household data
  2. The number of jobs added, which comes from the establishment data

Sometimes this data can seem contradictory. For example, between March and  June 2011, we gained 290,000 jobs but the unemployment rate went up .4% (from 8.8% to 9.2%).

There can be a couple reasons for this. The first one is that, the “jobs added” number comes from subtracting last month’s establishment jobs number from this month’s establishment jobs number, but we never use either of those numbers to calculate the unemployment data.

Why?

Because the essence of the establishment jobs number is asking employers: “How many people work for you?” It gives a nice accurate number, but it doesn’t tell us anything about how many people don’t work for them. We don’t have any number on the unemployed, only a number for jobs.

For unemployment, we have to go to individuals and ask them: “Are you employed or unemployed?” Then we take the unemployed number and divide it by the total number of people who are in the labor force, which counts both the employed and the unemployed.

But even the differences between the establishment jobs number and the household jobs number can be big. According to the household jobs number (which is supposed to exclude farm workers and the self-employed), we had 139.6 million jobs in August 2011. According to the establishment jobs number, we had 131.1 million.

That’s a difference of 8.5 million jobs, and that kind pf spread is pretty normal. The variation changes a little month-to-month, but we could get a report of  jobs created from the household number and jobs lost from the establishment number. In fact, we saw something similar in August where the household number said we gained 331,000 jobs, but the establishment number said we gained 0.

So why is the establishment number reported?

Because the establishment survey is so much larger, more reliable and gives more consistent results. In the graph below , we can see that even though the establishment data counts fewer jobs, it is a less erratic count.

So… that is a quick explanation of the employment report. I dig into this data once a month, so I’m pretty familiar and I’m delighted to answer questions or explain in greater detail in the comments.

Rick Perry And Texas Job Numbers

Full disclosure: I don’t like Rick Perry for our next president. I have my reasons that aren’t worth going into here. However, when I was watching the GOP debate and pro-Perry people started bringing up Rick Perry’s job numbers as a cudgel against other candidates, I looked into the BLS data on Texas jobs. Having familiarized myself with the data, I started noticing claims on the Texas jobs data that started popping up that directly contradicted what I was seeing in the data. So I wanted to clear up a couple of these common misconceptions.

Note: If you are going to comment and you want to introduce some new objection to the Texas job numbers, you MUST provide original data. I spent about 4 hours digging through raw data to write this post. I don’t want you to point to some pundit or blog post and take it on their authority, because I’ve already researched several idiot pundits who are talking directly out of their asses when it comes to the data. I want you to point to the raw data that I can examine for myself. This means links. I refuse to waste any more of my time on speculative bullshit or “Well, I’ll wager that the Texas jobs don’t really count because…” If you’re willing to wager, take that money and put it towards finding the actual data. In short, put up or shut up.

I’m not cranky, I swear.

Anyway, let’s deal with the complaints in no particular order:

“Texas has an unemployment rate of 8.2%. That’s hardly exceptional.”

See… that’s what I thought when I started looking at the data. I knew that Utah had a lower unemployment rate than Texas and I kept hearing that Texas was go great at jobs, blah, blah, blah, so I looked up the unemployment rate.

Nothing special.

So I was going to drive my point home that Texas was nothing special by looking at their raw employment numbers and reporting on those. That’s when I saw this:

This may not look like anything special, but I’ve been looking closely at employment data for a couple years now and I’ve become very accustomed to seeing data that looks like this.

In a “normal” employment data set, we can easily look at it and say “Yep, that’s where the recession happened. Sucks to be us.” But not with Texas. With Texas, we say “Damn. Looks like they’ve recovered already.”

(To get to this data, go to this link http://data.bls.gov/cgi-bin/dsrv?la then select the state or states you want, the select “Statewide”, then select the states again, then select the metrics you want to see.)

But if Texas has so many jobs, why do they have such a high unemployment rate? Let’s take a closer look at that data.

As a percentage of the number of pre-recession jobs, here is a chart of the growth of a selection of states. (For clarity, in this chart I selected a number of the largest states and tried to focus on states that have relatively good economic reputations. I did not chart all 50 states b/c it would have taken me too long.)

We can see that Texas has grown the fastest, having increased jobs by 2.2% since the recession started. I want to take a moment and point out that second place is held by North Dakota. I added North Dakota to my list of states  to show something very important. North Dakota currently has the lowest unemployment rate of any state at 3.2%. And yet Texas is adding jobs at a faster rate than North Dakota. How can this be?

The reason is that people are flocking to Texas in massive numbers. Starting at the beginning of the recession (December 2007), let’s look at how this set of states have grown in their labor force.

As you can see, Texas isn’t just the fastest growing… it’s growing over twice as fast as the second fastest state and three times as fast as the third. Given that Texas is (to borrow a technical term) f***ing huge, this growth is incredible.

People are flocking to Texas in massive numbers. This is speculative, but it *seems* that people are moving to Texas looking for jobs rather than moving to Texas for a job they already have lined up. This would explain why Texas is adding jobs faster than any other state but still has a relatively high unemployment rate.

“Sure, Texas has lots of jobs, but they’re mostly low-paying/minimum wage jobs”

Let’s look at the data. Here’s a link: Occupational Employment and Wage Estimates

Texas median hourly wage is $15.14…  almost exactly in the middle of the pack (28th out of 51 regions). Given that they’ve seen exceptional job growth (and these other states have not) this does not seem exceptionally low.

But the implication here is that the new jobs in Texas, the jobs that Texas seems to stand alone in creating at such a remarkable pace, are low paying jobs and don’t really count.

If this were true, all these new low-paying jobs should be dragging down the wages data, right? But if we look at the wages data since the beginning of the recession (click to enlarge, states are listed alphabetically)

And it turns out that the opposite is true. Since the recession started hourly wages in Texas have increased at a 6th fastest pace in the nation.

As a side note, the only blue state that has faster growing wages is Hawaii. Just thought I’d get that jab in since so many people have been making snarky “Yeah, I could get a job in Texas is I wanted to flip burgers!” comments at me on Twitter.

“Texas is oil country and the recent energy boom is responsible for the incredible jobs increase.”

In identifying “energy jobs” I cast as wide a net as possible. If you want to replicate my findings, go to this link: http://www.bls.gov/sae/data.htm, click on “One-Screen Data Search”, then select “Texas”, then select “Statewide”, then in Supersectors select “Mining and Logging”, “Non-Durable Goods” and “Transportation and Utilities” and then in Industries select “Mining and Logging”, “Natural Gas Distribution”, “Electric Power Generation” and “Petroleum and Coal Products Manufacturing”.

Tedious, I know, but transparency is important and this is how you get the data.

When we finally get the data, we discover that energy isn’t really the biggest part of the Texas economy. Increases in jobs in the energy sector (or closely related to it) account for about 25% of the job increases in the last year. Since the energy sector only makes up 3% of all employment, there is some truth to this claim.

However, take the energy sector completely out of the equation and Texas is still growing faster than any other state. This indicates to us that the energy sector is not a single sector saving Texas from the same economic fate as the rest of the states. It’s not hurting, but Texas would still be growing like a weed without it.

“Texas has 100,000 unsustainable public sector jobs that inflate the growth numbers.”

I’m not sure where this one comes from, but the numbers are these (and can be found by selecting government employment from the data wizard at this link http://www.bls.gov/sae/data.htm):

Counting from the beginning of the recession (December 2007) the Texas public sector has grown 3.8%, or a little under 70,000 employees. This is faster than normal employment, but it’s not off the charts.

Given that the Texas economy has grown so much and private sector jobs have grown so much, that doesn’t strike me as an unsustainable growth in the public sector.

But, just in case you’re really worried about it, you can lay your fears to rest because in the last year the Texas public sector has shrunk by 26,000 jobs. In the last 12 months, Texas lost 31,300 federal employees, trimmed 3,800 state jobs, and increased local government jobs by 8,400 jobs.

(To be fair, this was partially driven by the role Texas employees played in the census, which inflated federal job numbers this time last year. Since the census numbers stabilized, federal employment has been at about break-even.)

As you can see, we’re nowhere near the “100,000 unsustainable jobs” number.

My Personal Favorite Chart

I’ll leave you with my personal favorite chart. I mentioned at the beginning that Texas is seeing high unemployment in a large part because they’re growing so damn fast. The problem with this from a charts and graphs perspective is that it leaves worse states off the hook, making them look better than they actually are. Looking at unemployment alone, we would conclude that Wisconsin has a better economy than Texas. But Wisconsin is still 120K short of it’s pre-recession numbers. The only reason they look better than Texas is because 32,000 people fled the state.

During that time, 739,000 people fled into Texas. Anyone who takes that data and pretends that this is somehow bad news for Texas is simply not being honest. At the worst, I’d call it a good problem to have.

So, to give something of a better feeling for the economic situation across states, this chart takes the population of the states I selected above and judges the current job situation against the population as it stood at the beginning of the recession.

Using that metric, Texas would have a very low unemployment rate of 2.3%. But the fact that unemployment in the United States is fluid means that the unemployed flock to a place where there are jobs, which inflates its unemployment rate (at least in the short term). It’s not a bad thing for Texas… it just looks bad when dealing with the isolated “unemployment %” statistic.

UPDATE: @francisgagnon on Twitter felt that this chart was dishonest because it charts Texas as having 2.3% unemployment and (in his words so I don’t get him wrong): “It assumes immigrants create no jobs. But more people = more consumers = more jobs.”

He is absolutely right about this. I tried to be clear above that this chart doesn’t account for the fluid nature of an economy with immigration and departures of hundreds of thousands of people, but I don’t want to leave anyone with the wrong impression. So here it is: This chart doesn’t account for the fluid nature of an economy with immigrations and departures of hundreds of thousands of people. The point of this chart is not to say “Texas should have 2.3% unemployment if only things were fair.” Instead, it is an attempt to chart job growth in such a way that controls for people leaving one job market to enter another. To say “Wisconsin has a better job market than Texas because its unemployment rate is 0.6% lower” is a wholly untrue statement even though it cites accurate numbers. What this chart is meant to do is not posit a counter-factual, but to give a visual representation of the employment reality that is obscured by the way we calculate unemployment numbers.

END UPDATE

And… that’s it.

You may have noticed that I don’t mention Rick Perry very much here. That is because Rick Perry is, in my opinion, ancillary to this entire discussion. He was governor while these these numbers happened, so good for him. Maybe that means these jobs they are his “fault”. Maybe the job situation is the result of his policies. Or maybe Texas is simply the least bad option in a search for a favorable economic climate.

That is not an argument I’m having at this exact moment. My point is to show that most of the “excuses” you will hear about Texas’ job statistics are based in nothing more than a hope that Rick Perry had nothing to do with them and not on a sound understanding of the data.

My advice to anti-Perry advocates is this: Give up talking about Texas jobs. Texas is an incredible outlier among the states when it comes to jobs. Not only are they creating them, they’re creating ones with higher wages.

One can argue that Perry had very little to do with the job situation in Texas, but such a person should be probably prepare themselves for the consequences of that line of reasoning. If Rick Perry had nothing to do with creating jobs in Texas, than why does Obama have something to do with creating jobs anywhere? And why would someone advocate any sort of “job creating” policies if policies don’t seem to matter when it comes to the decade long governor of Texas? In short, it seems to me that this line of reasoning, in addition to sounding desperate and partisan, hogties its adherents into a position where they are simultaneously saying that government doesn’t create jobs while arguing for a set of policies where government will create jobs.

Or, to an uncharitable eye, it seem they are saying “Policies create jobs when they are policies I like. They don’t create jobs when they are policies I dislike.”

People will continue to argue about the data. But hopefully this will be helpful in sorting out reality from wishful and desperate thinking. I mentioned on Twitter that the Texas jobs situation was nothing short of miraculous. This is why I said that and why I’m standing by that statement.

Current Recovery “Faster & Stronger” According to CNN Money’s Chris Isidor

A recent CNN Money piece was titled “7.9 Million Jobs Lost Forever” by senior writer Chris Isidore. First, let’s set aside the idea that anything is really “forever” or the idea the we have a totally inelastic work force that, being filled entirely with idiots, never adjusts to the economic realities that confront us. Let us unstead focus on his statement:

“Excluding temporary Census workers, the economy has added fewer than 100,000 jobs a month this year — a much faster and stronger jobs recovery than occurred following the last two recessions in 2001 and 1991.”

Let’s go ahead and check that statement. Let’s take the job number at the end of the recession (as defined by this Wikipedia piece on recessions) and see how each recession did with jobs from the end of the recession onward, which we’ll define as “the jobs recovery”. The below chart shows the number of jobs in the months following the end of each recession.

image

As you can see, following the end of the recession, this “recovery” is vastly worse on the jobs recovery than previous recoveries. Now, it could be that what Mr. Chris Isidore meant to say is that “in the last 6 months, we’ve seen jobs growth much faster than the last two recessions”. That is the same as saying “See the growth between the two red arrows?”

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“It’s awesome. I would like you to infer that, based on this very limited view of jobs growth, President Obama is doing awesome on the jobs front.”

First of all, that kind of statement is why people think that reporters (even reporters who work for CNN Money) can’t do simple addition. Either Mr. Isidore is an idiot or he is deliberately mis-reporting the data.

Speaking of which, why would Mr. Isidore only use the last two recessions as an example? Let’s look at the last three recessions instead of the last two.

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As you can see, in a similar time frame, the improvement in jobs in the early 1980’s recession was heads and shoulders above any of the other recessions. In fact, in a comparable period, the early 1980’s jobs recovery was at a rate 4 times faster than this current one. And yet Mr. Isidore cherry picks a specific section of time within a specific set of recessions in order to make the claim that the jobs growth we’ve seen is “faster and stronger.”

Current Recovery “Faster & Stronger” According to CNN Money’s Chris Isidor

A recent CNN Money piece was titled “7.9 Million Jobs Lost Forever” by senior writer Chris Isidore. First, let’s set aside the idea that anything is really “forever” or the idea the we have a totally inelastic work force that, being filled entirely with idiots, never adjusts to the economic realities that confront us. Let us unstead focus on his statement:

“Excluding temporary Census workers, the economy has added fewer than 100,000 jobs a month this year — a much faster and stronger jobs recovery than occurred following the last two recessions in 2001 and 1991.”

Let’s go ahead and check that statement. Let’s take the job number at the end of the recession (as defined by this Wikipedia piece on recessions) and see how each recession did with jobs from the end of the recession onward, which we’ll define as “the jobs recovery”. The below chart shows the number of jobs in the months following the end of each recession.

image

As you can see, following the end of the recession, this “recovery” is vastly worse on the jobs recovery than previous recoveries. Now, it could be that what Mr. Chris Isidore meant to say is that “in the last 6 months, we’ve seen jobs growth much faster than the last two recessions”. That is the same as saying “See the growth between the two red arrows?”

image

“It’s awesome. I would like you to infer that, based on this very limited view of jobs growth, President Obama is doing awesome on the jobs front.”

First of all, that kind of statement is why people think that reporters (even reporters who work for CNN Money) can’t do simple addition. Either Mr. Isidore is an idiot or he is deliberately mis-reporting the data.

Speaking of which, why would Mr. Isidore only use the last two recessions as an example? Let’s look at the last three recessions instead of the last two.

image

As you can see, in a similar time frame, the improvement in jobs in the early 1980’s recession was heads and shoulders above any of the other recessions. In fact, in a comparable period, the early 1980’s jobs recovery was at a rate 4 times faster than this current one. And yet Mr. Isidore cherry picks a specific section of time within a specific set of recessions in order to make the claim that the jobs growth we’ve seen is “faster and stronger.”

Dean Baker Completely Unaware How BLS Calculates Unemployment Rate

Holy crap, how did Dean Baker from the Center for Economic and Policy Research get a job writing about economics?

Check out this line of his report on the recent unemployment numbers:

The unemployment rate fell to 9.7 percent in May, primarily as a result of 411,000 temporary Census jobs.

Mr. Baker is apparently unaware of how we calculate the un2employment rate. Let’s help him out here.

First we take the number of people who have jobs. This is not the “non-farm payrolls” number, which increased by 431,000. It is the “Employed, 16 years and over” number which decreased 35,000 (from 139.455 million to 139.420 million). Mr. Baker seems to have those two numbers confused, so I thought I’d clarify.

Then we take the number of people who are looking for jobs but can’t find them. This is where we get the “unemployed” number, which decreased from 15.260 million to 14.973 million.

Then we add the employed number to the unemployed number and you get the Labor Force number. In order to calculate the unemployment rate, we divide the number of people unemployed from the labor force.

139,420,000 + 14,973,000 = 154,393,000 people in the labor force

14,973,000 / 154,393,000 = 9.7% Unemployment rate

Let’s try to prove Mr. Baker’s statement that the unemployment rate dropped to 9.7% “primarily” due to the 411,000 census jobs. We’ll subtract 411,000 from the “employed” number.

139,009,000 + 14,973,000 = 153,982,000 people in the labor force

14,973,000 / 153,982,000 = 9.7% Unemployment rate

We get the exact same unemployment rate with or without the census jobs. That is because unemployment rate dropped due to people leaving the labor force. And most of the people who left the labor force came from the “unemployed” category. Otherwise known as “discouraged workers”.

This is part of the reason that economic understanding is so dismal among the general public. An economic reporter should be able to get the simple facts right about a job report.

What Happens to Unemployment Tomorrow?

Just thought I’d post this. I’ve always been a little fascinated by the number of people needed to pull off something as huge as a the census. And next month we should see the peak of the census employment burst. Observe:

This was done in about 20 minutes, so it might need some explanation.

Basically, I start with with the June before the census and mark that number (somewhat arbitrarily) as my base federal employment point. Then I checked the employment numbers moving forward from that point as a percentage of that number.

As you can see, if this census year follows the path of the last census year (which it seems to be doing so far) the May employment number coming out tomorrow should add around 300-350 thousand jobs due to the census alone.

How big is a 300-350 thousand job increase? Well, the increase in employment as a whole between March and April was about 250 thousand. So, if the recovery continues as it has been, we should see an increase of something along the lines of 500-600 thousand jobs tomorrow.

Take note, I’m doing really simple guesswork here. I’m pretty sure that geoff over at Innocent Bystanders will have more intelligent things to say on the matter tomorrow.

Visualizing Unemployment By State

I worked on this for a talk on visualization that I gave last week and I thought it was something that would be enjoyed here.

This is basically just a visualization of unemployment by state since we started collecting the data. With the play button, you can watch the whole thing from 1976 to 2009 in about a minute or you can drag along the timeline to a specific month. The size of the circle indicates the number of people unemployed in a given state and the color of the circle indicates the rate of unemployment in the state. Move you mouse over one of the circles to see the raw data.


Get Microsoft Silverlight

If you’re interested in looking at this project in more detail, I talk about it at my professional site, Designer Silverlight.

You can copy the code to embed this with the text below:

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.