Political Math

Archive for the ‘President Obama’ Category

In my last post, I offered an infographic positing that the recent health care reform bill was one of the most partisan pieces of major social legislation we’ve ever seen, comparing it to votes for civil rights (1964), medicare/medicaid (1965), and welfare reform (1996). The infographic was actually originally designed not to indicate partisanship per se, but to rebut the very specific complaint popular among many progressives that Republicans have always opposed major social legislation at the beginning and then come to accept it later on. They then claim that health care reform is no different than those other legislative acts.

As for that latter charge, which was the driving force behind the creation of the infographic, there’s no way around it: looking at the data and maintaining that Republicans have a history of reflexive unthinking opposition to social legislation is simply a denial of reality. Some more thoughtful individuals have tried to maintain the heart of that argument by asserting that ideology was previously spread across party lines in such a way that the ideological equivalent of Republicans in the 1960′s (and, I presume, the 1990s) were opposed to social legislation in a very partisan way.

It is true, my infographic is simplistic and that kind of a story could be lurking in the data. It was designed to debunk the original claim (mission accomplished) and to suggest that, in a “by the numbers” approach, the health care reform bill was not exactly a bipartisan triumph.

The funniest thing to me is that there is absolutely no way to argue that this vote was bipartisan in the strict sense. Disect the word itself. Bi – Two. Partisan – relating to parties (usually political). In order for the bill to be bipartisan, two parties had to vote for it. There was only one party that voted for this bill. It is de facto not bipartisan.

But most of the people who were arguing with me didn’t mean “bipartisan” in a literal sense, they mean it in a “Democrats tried to work with Republicans, but Republicans are jerks who hate President Obama so much that they wouldn’t vote for health care reform no matter what” sort of way.

The way I see it, Republicans who voted against the bill could have had three major reasons for doing so:

1. They’re jerks who want President Obama to fail (the “Party of No” theory)
2. They have principled reasons for opposing the legislation (deficits, scope of the federal government, constitutional concerns, etc)
3. They watched the polls and decided it wasn’t in their best interest

Now, it’s possible that the Party of No theory is correct and that all Republicans simply hate President Obama in an irrational way. However, in order to believe it whole heartedly, one would have to come to come to the conclusion that Republican congressmen are willing to lose their seats for the chance to stick out their tongues at President Obama. Assuming the villainy of one’s political opponents is a game for the young and angry; I’ve no taste for it. And anyone who thinks that politicians are constantly in a “f*** you, even if I lose my seat” mode hasn’t been following politics for very long. Congressmen like their jobs. Even the Republican ones.

In order for the Party of No theory to hold together, its adherents would also need to conclude that there are dozens of Democrats out there who also hate President Obama. While this is also a possibility, I’m starting to say “this is a possibility” in the sense that it is technically possible rather than in any way realistic. It seems far more likely that a number of Democrats were also watching the polls and decided that voting against this bill was in their best electoral interest.

Finally, much noise was made in 2008 by those in favor of a progressive Congress that we just voted in the most progressive congress of the last 30 years. With that in mind, let’s look carefully at the situation: The most progressive (liberal) Congress in the last 30 years passes a piece of legislation by a tiny margin without a single vote from the minority party and with dozens of Democrats voting against it and we are meant to believe that it was as bipartisan as it could have possibly been.

This kind of logic was laughable when Republicans tried it 6 years ago. It was perhaps optimistic of me to assume that Democrats and liberals would rise above such nonsense.

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.

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.

The first part of this post is just an overview of the data I used to make this video, so if you don’t care about that, you can skip over it to the part where I talk about what the budget freeze means.

First, I’ve got a new video up called “What Does The Federal Budget Freeze Look Like?”

Here is the data summary of this video:

I got the budget numbers (budget, discretionary, mandatory) from the overview of the 2010 budget which includes projections for 2011. I did this because the 2011 budget is not available yet (although I understand that those projections are a bit low and the real budget will be bigger than the projection).

That gives us the following numbers:

• 2011 Federal Budget – $3.7 trillion
• Mandatory portion of federal budget – $2.322 trillion
• Discretionary portion of federal budget – $1,380 trillion

I’ve seen it consistently reported that the freeze will affect $447 billion of the budget, although I imagine that number is subject to change. The amount saved from this freeze has been consistently reported as $15 billion in the first year and $250 billion over 10 years.

The stimulus funds as reported by recovery.gov at the time of this post are:

That leaves:

• $195 billion in tax cuts that have not been applied
• $202 billion in contracts, grants and loans that haven’t been spent
• $121 billion in entitlements (what a creepy name) that haven’t been spent

If we left the tax cuts in place, but canceled the rest of the spending, we’d save $323 billion… which is a shade less than what I said in the video. Apparently, that is the result of some rounding errors in my spreadsheet, but the $4 billion comes out to about one and a half teaspoons, which isn’t enough to make a difference in the visualization.

As for the water part of it… If we assume that the budget is 192 ounces of water that we’ve split into 4 oz cups, then all the math in the video works out. I actually under-counted the unspent stimulus (it would be 17 ounces instead of 16). I measured my ice cube tray and found that each ice cube was 1.5 ounces and I used 1 and a half tablespoons of water to measure out the .75 ounces that would be equivalent to $15 billion.

<End of Boring Math Things>

OK… now to comment on what I think about the budget freeze to anyone who cares what I actually think.

First of all, I hate the “we’re saving $250 billion over 10 years” line. It is a piece of crass political rhetoric and I’m disappointed that the administration would use it. If they actually implement a three year freeze on the portion of the budget they’re talking about (which is a big if, but let’s assume the best), why measure the effects in the space of 10 years?

The answer is “To make the freeze look bigger”. They’re basically just basing the extended savings off of projected interest payments and “savings” due to the fact that the baseline on that portion of the budget hasn’t moved. It is setting a dangerous data precedent where politicians realize that all they have to do is calculate a projection out as far as they need in order to get the numbers they want. It would be like giving an employee a $5,000 bonus, but saying that you gave them a $8,000 bonus based on a 5% return of that investment over the course of 10 years.  They might as well say that they’re saving a trillion dollars over the next 25 years or a hundred trillion over the next 300 years. It is a data statement designed to trick people.

Second, I hate the “We’re saving all this money by not spending it” line because it is similarly political. If a future politician wants to play this stupid numbers game, all they have to do is “project” that they will spend like a crazy person next year and when the next year comes, they decided to spend like a half crazy person. Then they can claim that they have “saved” all this money because they “reduced” their projected spending.

As a slapdash example, a politician could project that they will increase spending by 5% next year and then decide at the last moment to increase it by 3%. They could then spin that decision to increase by a smaller amount as a decision to “cut” their spending (which wasn’t real spending, only projected spending) by 2%.

Last, my attempt to visualize the scale of the budget freeze does not mean I don’t support it. I really like to see cuts to the budget and I personally think this is not an insignificant one.I think it is worth our energy to do exactly what the Obama administration seems to be doing…freezing increases and looking around for crappy programs to cut.

Keep in mind the hypocrisy on both sides of the aisle. The Republicans are hypocrites for claiming that this is a totally inconsequential budget cut. In 2005, George W. Bush proposed a 1% cut (not a freeze, a cut) in discretionary spending that wasn’t Department of Defense or Homeland Security. Translated to today, Bush’s cuts would have “saved” $33 billion using the calculation metric for the current freeze; more than twice the amount that this freeze would save us. At the time, John McCain called it a “very austere budget” and Dick Cheney went out pushing their credentials as cost cutters. I find it strange that they were ecstatic about saving the equivalent of $33 billion but think that $15 billion is a drop in a bucket.

Of course the Democrats blasted Bush’s cuts as a gimmick too small to make a difference, but seem to have lost much of their skepticism over these new, smaller “cuts”.

Overall, it looks like both sides are more interested in political gain than in having a frank discussion about the numbers and what they mean. This should surprise no one, but I confess to finding myself somewhat dismayed that the Obama administration, for all their hype about being pro-science and pro-data, has no problem spinning the numbers in a way that decreases clear comprehension in order to increase message potency.

You may have seen the Paul Krugman post “How Big is $9 Trillion” in which he attempts to defend the Obama administration’s recent announcement that they expect that their policies will increase the national debt by $9 trillion. His tack is to “explain” that $9 trillion isn’t really all that much when you understand it in context.

it’s being treated as an inconceivable sum, far beyond anything that could possibly be handled. And it isn’t.

What you have to bear in mind is that the economy — and hence the federal tax base — is enormous, too. Right now GDP is around $14 trillion. If economic growth averages 2.5% a year, which has been the norm, and inflation is 2% a year, which is the target (and which the bond market seems to believe), GDP will be around $22 trillion a decade from now. So we’re talking about adding debt that’s equal to around 40% of GDP.

Right now, federal debt is about 50% of GDP. So even if we do run these deficits, federal debt as a share of GDP will be substantially less than it was at the end of World War II.

I defer to Paul Krugman on a lot of things because he is transparently smarter than I am. But it is precisely because of this fact that I know he is conscious of the obvious reasons his analysis is hogwash.

First of all, the national debt in WWII was initiated by an existential threat to the very continuation of our country. Mr. Krugman does not make even attempt to make the case that we have a similar crisis that justifies this kind of debt.

Second, implicit in his observation is the concept that since we did fine after WWII, we’ll do fine now. But the years after WWII saw drastic reductions in the inflation-adjusted debt driven by drastic reductions in spending. Mr. Krugman points to no similar possibility in the post-Obama world.

Third, we have something now that we didn’t have in the 1940′s. Back in the 1945, at the height of the spending that saw our national debt rise so dramatically, entitlement spending and interest on the national debt made up a meager 5% of our total budget.

By the end of President Obama’s term (if he runs two terms) we’ll be looking at a federal budget that is 70% mandatory spending. (I assume for the purposes of consistency that mandatory spending includes interest on the national debt because we don’t really have a choice in not paying it.)

Here’s a quick visual of the difference in the budgets in 1945 and 2016. (Ugly, because I did it fast… I’m on vacation.)

If you look at the 1945 budget with the single question “How are we going to reduce our debt?” you can identify the major problem. It’s the defense budget, which is almost 90% of the budget. Interestingly, reducing the defense budget is exactly what we did in order to reduce the debt, cutting it over 80% in 3 years (it helped that we won the war).

As a contrast, President Obama’s solution to reducing overall spending is… well, I don’t think he really has a plan. His projected budget in 2016 has reduced the defense budget as a percentage of the overall budget from 20% to 14%, but military spending isn’t what is killing us. The president has no plans to reduce mandatory spending whatsoever. In fact, his only change to entitlement spending is to increase it.

My problem with Mr. Krugman’s “How big is $9 trillion?” is that he is aware of all the problems I pointed out. He didn’t explain how much $9 trillion is; he obfuscated it. By comparing the debt load in the heart of a world-shaking war to a debt load that was accumulated in (relative) peacetime, he has misled his readers to the real significance of the data.

(By the way… if you would like to blame the debt load on the Iraq war, you should know that those costs have raised our debt by 5% of the GDP. Comparing this to WWII, which raised our debt by 70% of the GDP, is a pretty weak argument.)

[youtube=http://www.youtube.com/watch?v=AqD-nMpsYAY&hl=en&fs=1&]

The next couple weeks are insane for me, but I’ve been sitting on this idea for some time and I figure its time to let it loose into the wild, spelling errors and all.

First, my sources.

• Wait time data – Merrit Hawkins and Associates 2009 Survey of Physician Appointment Wait Times
• Cost of Insurance Premiums – AHIP Center for Policy and Research Individual Health Insurance 2006-2007: A Comprehensive Survey of Premiums, Availability, and Benefits

Now for the caveats.

Wait times data are for routine checkups and does not count emergency care or diagnostic testing.

Phyllis Shlafly repeated the line that “The average wait is… the second trimester of pregnancy to see an obstetrician-gynecologist.” It looks like she is using the same documents that I’m using and if that is the case, that statements is absolutely false.

First of all, these wait times apply only to routine checkups (as stated above) and the OB/GYN checkups are “well woman” check-ups. Someone correct me if I’m wrong, but I don’t think that a pregnant woman falls into that category.

Second, the average wait time in that category is 70 days, which is really only the second trimester if you count the “Wait a second, I’m pregnant!” realiziation time, which might be OK if she mentioned that to he readers.

Now for the insurance cost data. This was a statistic I struggled with for quite some time. The reason is because the latest comprehensive data available was collected at the end of 2006 and beginning of 2007. This was so soon after the passage of the Massachusetts health care reform that it is very unlikely that it accurately reflects the results of that reform (which is something the study authors freely admit).

However, I’ve search high and low and cannot find any indication that the premiums have decreased at all. To the best of my knowledge, they have increased faster than the country average.

If this is true,  then the average individual health insurance premium in Massachusetts is somewhere around $830 per month.

But I figured I might as well underestimate in order to flush out people who might complain, so I used the non-specific and drastically reduced number of $600+ per month.

Finally, the most important question:

How close to the Massachusetts health reform is the Obama health reform plan?

Because, honestly, if they weren’t anything like each other, there would be no point in comparing them, would there?

The sad fact of the matter is that the Massachusetts model provides the closest real life approximation to the Obama plan that there is available.

They both have a government agency for providing health care exchanges. They both require business over a certain size to provide insurance for their employees or face penalties. They both require individuals to purchase insurance or face tax penalties.

Like it or not, I think we can look to Massachusetts as a miniature crystal ball to provide a glimpse into the future of health care in the US if the Obama health care plan is passed.

I’ve been pretty quiet recently because 1) I’m on vacation and 2) I’m trying to wrap my head around the health care issue before I talk about it at length.

But today I saw something on healthreform.gov that bothered me:

Here’s the thing, Mr. President. There is such a thing as visual lying. That is when you show a graph and you show the numbers but the two things are not in any way related to one another.

That is the problem here. If someone looks at this graph, they see that the sky is falling because the bars have increased so dramatically. On the left, your team has represented a 30% increase with a graphic that shows a 966% increase. On the right, your team has represented a 63% increase with a graphic that shows a 308% increase.

And are the two sets bars related in any way? You might think so, given that they show up next to each other and are supposed to measure the same thing. But from a data perspective, they are not even remotely close to being right.

It is possible to use graphs and numbers in such a way that is honest. That’s an important part of transparency. So, I fixed your graph for you.

You’re welcome.

UPDATE: In the comments section, James quickly identified the problem… the graph starts the y-axis at 1000 instead of 0. I double checked and it looks like he is spot on. Thanks!

With that in mind, the graph is more of a rookie mistake than a conscious attempt to deceive. I’ve edited my post to reflect that (I left my original comments in so everyone can see what a smart-ass I tend to be).

[youtube=http://www.youtube.com/watch?v=CJu0DgpiK8c&hl=en&fs=1&]

In this video, I take a look at the economic predictions that President Obama made in February regarding the stimulus plan and how those predictions are corresponding to reality.

The answer is: Not well.

But first, some references.

• I got all my data from one extremely boring source, the Bureau of Labor Statistics. At the moment, all the data is in the economic summary, but I assume that will change as the weeks go on, so you can also check the historical unemployment tables.
• The chart that President Obama used is in this document on how the stimulus will effect the economy.
• Special thanks to Geoff at Innocent Bystanders. Last month, he started charting how the numbers Obama used to sell the stimulus were matching to the actual numbers. So I can’t claim the idea as my own.

OK… now into the math. The chart that everyone is using does not have a corresponding table with hard number (at least no table that I could find), so I had to guess-timate what they were predicting the unemployment rates would be in May. I assumed that, because their graph divergence began immediately after the Q1, 2009 line, that that line represented the beginning of Q1 2009 (as opposed to the middle). So I estimated that the May would be just a shade before Q3, which is about the same place that Geoff put his May data.

Based on that, I estimated the points on the line like so:

Now… here is the problem. In order to make our data symmetrical, we would have to have another row… a row called “Actual Unemployment without the Stimulus”. This, of course, is a row we cannot have because we sadly live in a space-time of collapsed quantum possibilities. We can never know what that row would hold.

This is where I start getting a little less analytical and a little more irritated. The president’s predictions have been shown to be completely off the mark… almost laughably so. And yet he acts as if he alone knows what would have happened if we hadn’t passed the stimulus because he keeps making statements like “we’ve saved 150,000 jobs“.

It is clear that, if he is referring to the chart we were presented with above, such a claim is absurd. What the president is doing is ignoring the fact that his predictions in the past were horribly inaccurate and simply moving ahead with new predictions. The big difference is that his new predictions can’t be judged against any set of objective reality. He is pitting the actual universe in which the stimulus bill passed against the imaginary universe in which it did not pass. Not surprisingly, the imaginary universe is worse that the real universe and the result is that the President is a hero for saving us from that imaginary universe.

I am not a very anti-Obama person. Predicting the future is tricky business and I think his team should get some leeway on this.

However…

Their predictions were not just kinda wrong. They were horrifically, disasterously wrong. If President Obama is going to use statistics and charts to push nearly $800 billion in spending, I think we should be able to expect his numbers to at least kinda match the reality that comes out of his policies.

At the very least, I’d like to know how his team got those numbers. More importantly, I’d like to know how they have changed their method of prediction. President Obama is fond of saying that we tried tax cuts and they didn’t work, so we should try something else. In that same vein, his team tried predicting the effect of the stimulus and that didn’t work. So I would like to know if they are using the same failed methods they used before or if they are doing something different.

Today the Obama administraion launched Data.gov, a new website designed to make governmental data easily accessible to normal people (who love looking at data) and in formats that allow software developers to mine the data.

This is an excellent step towards transparency in government. The ultimate utility will matter on how many databases they allow us access to and how often they are updated, but it looks like the new go-to site for government data.

Just at a glance, we’ve got extensive data for:

• USA Spending Contracts and Purchases (searchable database)
• Benefits Data from the Benefits and Earning (Social Security Benefits)
• Patent Application Bibliographic Data (2009)
• Graphical Database of Tornados (1950-2006)
• Rain, Hail and Snow Observations
• Energy Consumption Survey (RECS) Files (1978-2005)
• Migratory Bird Flyways for the Continental United States

Lots of government gathered scientific data and a couple things that look like they might have some actual “responsible government” implications. I’d love to see more of this.

Very well done.

This graph has been going around a good deal in the last week. (Source)

Basically, the light blue line is the unemployement rate the Obama administration predicted would happen if we didn’t pass the stimulus bill back in . The dark blue line is the unemployment rate the Obama administration predicted would happen if we did pass the stimulus bill. (Here’s the raw document.) And the red triangles are the actual unemployment rate as it has panned out. Not only are they worse than the Obama adminstration expected, they’re worse than what they expected even if we didn’t pass the stimulus bill.

I think it is fair to say that the stimulus bill has not been as stimulating as they told us it would be.  Now, it could certainly be the case that the unemployment rate would be even higher than this if we hadn’t passed the stimulus bill, but that is about as non-falsifiable a statement as you can get. 

(UPDATE: The author of this graph explains why he thinks there has been little effect … we’ve spent almost none of the stimulus money yet. I’m trying to figure out where he’s getting his data because I don’t see any infrastructure projects on there. I’m certain that there is infrastructure spending going on right now because there is a stimulus project not 3 miles from my house causing daily traffic jams.

UPDATE 2: Here’s the best I could find on stimulus money currently being spent.)

 I don’t really feel like dogpiling on the adminstration on this particular issue, so I want to hit a broader topic here… the administration’s use of numbers. This graph tells us some simple things that are scary and a complex thing that is scarier. 

The simple thing it tells us is that the Obama administration was completely unable to predict the economic conditions four months into the future. They thought we would be at about 8.0% unemployment if the stimulus bill passed and at 8.5% unemployment if we sat on our hands.

As it turns out, we passed the stimulus bill and we’re at 8.9%. The easy lesson is that they didn’t get that one right. But, as Robert Strom Petersen said, “It’s tough making predictions, especially about the future.” And I probably couldn’t have done any better.

But no one is hanging the weight of hundreds of billions of dollars around my neck, which makes it more OK that I can’t project the future economic conditions. It seems fair to demand a slightly higher level of predictive accuracy from an administration that is using their predictions to push trillion dollar policies. 

The complex thing that this graph tells us is that the Obama administration is comfortable using graphs that don’t really have a basis in reality in order to bolster support for  their decisions. Graphs make us think that something is scientific and studied and therefore more reliable. But reliability is something that has to be earned. The team that put this graph together should be questioned on what they got wrong and what they would do next time to get it right.

Basically, the next time the president uses projected figures to push his policies, I would like to see someone ask the following question:

“Mr President, the last number predictions you threw at us turned out to be pretty far off the mark. What assurances do we have that these new numbers are accurate?”