November 5, 2009
One of the key talking points for the stimulus that was passed earlier this year was that it would “save or create” jobs. Lots of jobs. Oodles of jobs. Jobs piled so high, we’ll have to hire people to dig us out of all the jobs we will have.
Or, more specifically, the Obama administration stated that they would “save or create” 4 million jobs.
This led to a great deal of mockery over the “save or create” turn of phrase, but the administration set out to actually measure the number of jobs that were saved or created by having recipients of the stimulus funds fill out a form in which they indicate how many jobs that particular chunk of the stimulus created (that form can be found here).
Now, if you look at recovery.gov, you’ll see that the stimulus has “saved or created” 640,000 jobs. That is only 16% of the promised jobs, but it’s still a pretty big number. I was curious how they got it, so I downloaded the raw data and started sifting through it. This is what I found:
- Over 6,500 of all the “created or saved” jobs are cost-of-living adjustments (COLA), which is really just a raise of about 2% for 6,500 people. That’s not a job saved, no matter how you calculate it.
- Over 6,000 of the jobs are federal work study jobs, which are part time jobs for needy students. As such, they’re not really “jobs” in the sense that most other federal agencies report job statistics (We don’t count full time college students as “unemployed” in the statistics.)
- About half of the jobs (over 300,000) fall under the “State Fiscal Stabilization Fund”, which can be described like so: Your state (perhaps it rhymes with Balicornia) can’t afford all the programs it has running, but when the state government tries to raise taxes, people yell and scream and threaten to move. The federal government comes in with stimulus funds and subsidizes the state programs. Consider this a “reach-around” tax in which the state can’t raise taxes its citizens any more, but the federal government can. So the federal government just gives the state the money to keep running programs they can’t afford on their own.
- There are, scattered hither and non, contracts and grants that state in no unclear language that “This project has no jobs created or retained” but lists dozens, if not hundreds, of jobs that have been “saved or created” by the project. It makes no sense whatsoever.
Finally, there is a statistical problem to the data here that I’ve not heard discussed at all, the problem of job duration.
Because there is no guidance in the forms on the proper way to measure “a job”, recipients are left to themselves to figure out what counts as a job. Some of them fill it out by calculating “man-weeks” and assume one “job-year” to be the measurement of a single job. Others fulfill contracts that only require two weeks, but they count every person they hire for every job to be a separate job created.
As an illustration: Let’s say you have a highway construction project in the Salt Lake City area that takes one month. A foreman is hired for the project and he brings on 20 guys he likes to work with to fill out his crew. That is 21 jobs “saved or created”. While that job is being completed, the funding if being secured for another highway construction project. By the time that funding goes through, the first project is done and they decide to just move the whole crew over to the next project. That is another 21 jobs “saved or created”.
If this happens four more times, on paper it looks like 124 jobs have been “saved or created” when in reality 21 people have been fully employed for six months. But if you judge jobs through a “man-weeks”/”job-years” lens, you have 10.5 jobs.
This is how the Blooming Grove Housing Authority in San Antonio, Texas can run a project titled “Stemules Grant” to create 450 roofing jobs for only $42 per job. My educated guess is that they hired day-laborers, paid them minimum wage or below and only worked them for a single day. Each new day brought new workers which meant more jobs “created”. Either that or they simply lied on the form. (UPDATE: USA Today interviewed the owner here. He says that he used only 5 people on the roofing jobs but that a federal official told him that his original number wasn’t right, so he adjusted it to count the number of hours worked, not the numbers of jobs created.)
Rational people can see that this kind of behavior skews the data upward. How much upward? It’s hard to say, although it is a safe bet that any project that manages to create a job for less than $20,000 is probably telling you some kind of fib.
My ultimate conclusion from looking at the jobs data is that:
- The jobs numbers reported on recovery.gov are heavily exaggerated
- The jobs numbers reported are not subjected to any scrutiny or auditing whatsoever; they are a simple data dump and therefore be seen with heavy skepticism
- The jobs numbers are a laudable transparency effort. I’m impressed that so much work has gone into trying to measure the results of the stimulus funding. Normally, these kinds of numbers would be shrouded in mystery and a normal Joe like myself would be unable to investigate them. Kudos to the Obama administration for implementing this data gathering and display initiative. However, they put too much faith in the data and statements like “The stimulus has saved or created 640,000 jobs” are uttered with a profound ignorance in the nitty-gritty details of what the data actually says.
For more interesting stimulus jobs data, you can see Paul Krugman getting angry about it here and Greg Mankiw responding to that anger here and Brad DeLong calling Allan Meltzer a shameless partisan hack about the topic over here and a story of how $900 worth of boots became 9 jobs over here. Or you can just download the jobs data and look through it yourself. There’s lots of interesting stories in there.
What The September Unemployment Rate Tells Us (Or, How I Learned To Start Worrying and Hate the BLS Data)
October 5, 2009
Latest unemployment data has come out and the people who were claiming “ah, but job losses are slowing” were smacked down and sent to the corner to think about what they’ve done.
The unemployment rate was up .1%, from 9.7% to 9.8%. That’s not so bad, right?
To speak frankly, the unemployment rate tells so little of the story at this point that it’s hardly a useful metric. If you’re looking for a useful metric, start looking at the raw unemployment numbers.
The problem with the unemployment rate is that it doesn’t compare the employed with the unemployed. Instead, it compares people who are employed with those who don’t have jobs, but have looked for a job in the last 4 weeks”. This make a certain kind of sense; we don’t want to count stay-at-home dads or retired individuals as unemployed.
However, this means that an exodus from the workforce could mask the severity of the job situation. To illustrate, I’ve created a visual:
Let’s say we have 20 people in the workforce and 2 of them fit the technical definition for unemployed, which means that they’re actively looking for work. That gives us an unemployment rate of 10%.
Now, let’s say one of the unemployed people got tired of being unemployed and decided to go back to school. She has now removed herself from the labor force, so we don’t count her when we count unemployed people. Let’s also say that one of the employed people lost his job and instead of looking for a new one, he decided to simply retire.
As you can see we haven’t added any jobs… in fact we have fewer jobs than we did before. But we took a higher percentage of people out of the “unemployed” group than we did out of the “employed” group. It’s now 1 person unemployed and 17 people employed. We’ve “slashed” the unemployment rate to 5.5%.
This current job report is actually a perfect example of this. We lost 785,000 jobs this past month. That makes it the biggest month of job losses since March. But the number of people in the unemployed group rose only 214,000. This is because we saw over twice that number simply leave the work force altogether.
If we took employment numbers for this month compared it to the labor force for last month, we would have an unemployment rate of 10.2%… almost a half a percent higher than the one we have!
I try to be an optimist, but it is hard to see this report as anything but a disaster. Furthermore, we are so far into the implementation of the stimulus, that I have a hard time seeing it as anything but a huge failure. I understand that only about 10% of the stimulus has actually been spent, but part of the point of the stimulus was to get money out into the economy in order to inject a little cash flow into the situation. That means that a huge part of the success of the stimulus relied on getting the money out in a timely manner.
I know that defenders of stimulus theory would object that it takes time to spend $800 billion and that you can’t spend that much very quickly without massive fraud. To which I reply: “Well, duh.” I think that’s a great argument against the stimulus and I wish they had brought that up back in February and March instead of bashing people like me for bringing that up back in February and March.
Back to the point, we have seen job growth in only one month out of the last 17. We need to stop focusing on the unemployment rate and start looking at raw jobs data. Only when we see the raw number of jobs start rising consistently can we be confident of economic recovery.
Note: To be fair, jobs tend to be a lagging indicator, but outside the stock market increases, I’m seeing little reason to be optimistic. And, quite honestly, the stock market seems to be very excited about absolutely nothing. It’s like they’re throwing a champagne party because the world hasn’t ended, neglecting the fact that it is still on fire.
September 5, 2009
Robert Stacy McCain (who is totally hilarious, even if you vehemently disagree with him) has a post on an FHA bailout he believes is heading our way. I have no opinion on the matter one way or another because I haven’t really looked into it and I try to have some idea of what is going on before I open my big mouth.
(Although I occasionally fail at even that simple task.)
But one of McCain’s statements made me pretty skeptical (emphasized below):
The FHA is on the hook for lots of “underwater” loans, taken out by low-income homeowners who got special low down-payment deals and — in case you didn’t notice — unemployment hit a 26-year high in August, with no prospect the 9.7% jobless rate will go down any time this year.
Really? No prospect at all? Not even an itsy-bitsy prospect?
I know it is something of a debate as to whether we’re currently seeing a real recovery or something more akin to an extended dead cat bounce. I personally kind of oscillate between the two views and I think there is a good deal of evidence supporting either side.
But I tend to think we’re definately seeing a slowdown in unemployment and I wouldn’t be at all surprised to see it go down by the end of the year.
So, Mr. McCain, I’m watching you. One of the greatest things about the internet is normal people can go back and see how right or wrong someone was in the past, using this information to judge their future claims.
If unemployment dips below 9.7% by the end of the year, I will make a point that your enormous confidence in the suckiness of the economy was misplaced.
If it does not, I will write a humble post begging your forgiveness. I’m curious to see how this goes.
August 27, 2009
You may have seen the recent headline “Real US unemployment rate at 16 pct: Fed official. A snippet:
“If one considers the people who would like a job but have stopped looking — so-called discouraged workers — and those who are working fewer hours than they want, the unemployment rate would move from the official 9.4 percent to 16 percent, said Atlanta Fed chief Dennis Lockhart.
UPDATE: Commentor Tom M. takes note that Mr. Lockhart is probably refering to the U6 numbers and this fact was simply not reported appropriately. He says:
When economists, such as myself, talk about the “real” unemployment rate, we are usually referring to the U6 unemployment figure, which is the U3 rate (the published/official rate) plus people that are “part time for economic reasons” among other groups.
If that is the case, it makes most of the rest of what I have to say pretty much void, but I’ll leave it up anyway. Thanks Tom!
A little while back, I called “discouraged workers” the “despair numbers” (basically, they say they want a job, but they aren’t looking for one).
My conclusion was that we’ve always had despair or discouraged workers, so suddenly adding them in now seems like a dishonest tactic to artificially inflate unemployment to some scary level. In good times, we saw unemployment at about 4-5%, so we’re used to thinking about that range as being good. But if you add the “discouraged workers” in those good times, you’re looking at a “good” unemployment rate of about 7-8%.
As for the “wants to work more hours” crowd, I’m open to considering that group in some way, shape or form, but I don’t know how to add them in a way that is honest. Frankly, as a small business owner and contractor, I don’t work as many hours as I would like. But I don’t go around calling myself “unemployed” or even “underemployed”.
If you look at the Bureau of Labor’s stats on part time workers, you can see that the number has jumped about 3 million in the past year. If we add those workers plus the increase in the “discouraged workers” (about 1 million), we get a rate a little over 12%.
But the problem in my mind is that you can’t simply add part time workers to the “unemployed” list to get any kind of meaningful data. Maybe, for the sake of argumentation, you could could cast an involuntary part time worker as half a worker. Then the unemployment rate is a shade over 11%. This is, I think, a not-unreasonable number to use, given that it shaves off the standard number of “discouraged workers” and uses a dampening variable to account for the fact that part-time workers aren’t really “unemployed”, but “underemployed”.
But I could be easily convinced that crunching the numbers in a new and interesting way is basically statistical cheating and we should just use the standard definitions.
Overall, I’m really uncomfortable with the whole “let’s crunch the numbers so the situation look really terrible” methodology because all it does is try to cast the current situation in a bad light by changing the metric. But you can’t use one metric in the good times and another metric in the bad times.
As such, I think the 16% number is really more of a scare tactic than anything else.
August 7, 2009
Today the unemployment rate for July 2009 was released by the Bureau of Labor Statistics. The rate dropped from 9.5% in June to 9.4% in July.
Before I explain why this might not be as awesome as it looks, let me just say “hooray!” for what seems like a slowing in the rise of the unemployment rate. I am ecstatic to see that the economy is not accelerating downward.
Stupid Moralizing (skip if you don’t care)
Some people seem to almost be cheering the decline of the economy for political purposes. Before last November, those people were mostly liberals. After January, those people were mostly conservatives. It is an activity I find creepy and slimy.
The decline of the economy means people losing their jobs, losing businesses that they’ve spent years trying to painstakingly build. This can be devastating on every level, personal and professional. The pain it brings is almost unspeakable. When someone cheers or hopes for a decline in the economy simply so that their political team can come out ahead, they reveal themselves to be without the basic human emotion of sympathy.
I don’t give a crap who is in office… I prefer to have a reduction in human misery if possible.
End of Stupid Moralizing
So… now that I’ve gotten all self-righteous and morally irritating, let’s talk about the numbers. (If you get bored by this discussion, feel free to skip to “The Point” at the bottom)
The unemployment rate is… well, it’s exactly what it says it is: a rate, a percentage based on two numbers. Your average non-economic American might think that the two numbers are as simple as “people employed vs. people unemployed”. Under this definition, you might think that a lower unemployment rate means that there are more jobs.
Sadly, you would be wrong.
The numbers actually start with the US population*. From that number, we take out children under 16, prisoners, those in mental institutions, those who require nursing care and the military and we get the “civilian non-institutional population”. From that number, we take out those who, for whatever reason have not tried to find work for 4 weeks. This is important because you don’t want to count housewives and high school seniors in the unemployment numbers. Remember that, because it’s going to be important in a second.
That brings us to the “civilian labor force”, which consists of the employed and the unemployed. It is from the civilian labor force that we calculate the unemployment rate. Therefore, there is a good way and a bad way to reduce the unemployment rate.
- Increase the employment number (good)
- Decrease the number of people in the labor force (bad)
The reason decreasing the number of people in the labor force is bad is that it means that people are extracting themselves from the labor force by:
- getting arrested in alarmingly huge numbers (unlikely)
- joining the army in alarmingly huge numbers (unlikely)
- getting younger in alarmingly huge numbers (that would be awesome)
- deciding that they’re just not going to look for a job anymore
And among the people in section 4, there are several options:
- deciding to stay home due to a lifestyle change (staying home with the kids)
- going to school to train for a new job
So, let’s cut to the chase. We’re not seeing new jobs. The employment number in July continued to decline (though at a much slower rate than it did in June). What we saw instead was a decrease in the labor force. More and more people are just not looking for jobs anymore.
On the surface the unemployment rate going down seems good, but when you dig into the numbers, we can see that it has nothing to do with an increase in the number of jobs and everything to do with the fact that the labor force is shrinking.
Is this good or bad? I tend to think bad, but the economy also tends to be really complex, so I could be misreading something or I could be just plain old ignorant. I’m not an economist, so I won’t make a pronouncement on that issue. All I can do is show the numbers and wonder what the hell is going on.
@D_B_Inman on Twitter pointed out that I was looking at the unadjusted numbers in my analysis and that the unemployment rate is based on the adjusted numbers. When taking that into account, my charts and extra analysis are strikingly ignorant. This is actually comforting, because it means things aren’t as out-of-whack as I thought they were. I’ve adjusted my “Point” accordingly.
* The Bureau of Labor Statistics lays this all out in more detail, if you want to check it out for yourself.
** There is something a little weird in this because the historical data at BLS doesn’t match up with their current press releases. According to their historical data, we saw an increase in the labor force in the last couple months. But according to their historical data, the current unemployment rate is 9.7%, which is not the number being currently reported. I took the numbers from their current press release and I substituted them into the historical data, since I’m assuming that their current press release is more accurate. If you think I’m wrong, please let me know why.
June 7, 2009
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:
|Unemployment Rate||Unemployed Population|
|Predicted Unemployment without the Stimulus||8.7%||13,492,000|
|Predicted Unemployment with the Stimulus||7.9%||12,251,000|
|Actual Unemployment with the Stimulus||9.4%||14,511,000|
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.
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.
May 18, 2009
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?”