I got an email from Steve Landsburg with the subject line "krugman, me and you." I can't decide whether that counts as the sort of threesome I've always dreamt about...
I get daily emails from The Chronicle of Higher Education newsletter. Today's headline: "Academe Today: Professor Says His University Cares Little About Teaching." I had to stop for a second and confirm that I wasn't in fact reading The Onion.
Earlier this year, the Massachusetts Council for Economic Education hosted its annual High School Economics Challenge, which brought students from all over the state to the Federal Reserve of Boston to compete to see which students are the biggest ner…er, which students know the most economics. The two main divisions- the David Ricardo division for regular economics students and the Adam Smith division for advanced placement economics students (apparently the council likes its economists to be of a certain age)- consist of an individual exam and then a quiz bowl round where the two top-scoring schools on the exam go head to head to decide a winner. The winner in each division is then eligible for the National Economics Challenge sponsored by the Council for Economic Education and to be held this weekend in New York. This year, Lexington High School, the Massachusetts winner in the David Ricardo division, scored high enough to qualify for the finals, so I will be watching the livestream of the finals on Sunday at 3pm on the Council for Economic Education Facebook page. I watched last year and Belmont High School won in the Adam Smith division, so clearly I am a good-luck charm. (See also: correlation versus causation.)
In addition to the quiz bowl rounds, the Massachusetts Economics Challenge introduced a new round this year, named the (continuing the trend) Alfred Marshall round, where students consider a case study and then make and defend policy recommendations based on the scenario described. The inaugural case was about the recent economic troubles in Ireland, and I had the pleasure of not only judging the written proposals (ever see high-school students try to use the word sequester properly?) but also asking follow-up questions to the two teams that we chose as finalists and then choosing a winner. (Just know that I have ALL the power.) The President of the council was nice enough to send along some pictures from the judging:
(Guess who knew the camera was there? Me and the guy in the bow tie, apparently.)
(The other judge is the economics department head at UMass Lowell. I swear that we were both taking our jobs equally seriously. Also, for the record, it was really hard to pick a winner because both of the finalist teams were pretty impressive.)
If you are a high-school student or teacher, I highly recommend looking into having your school participate in your state’s economics challenge. (You can see a list of state coordinators here.) I also recommend checking out my study materials to help you prepare.
I should have known that sending that sending Zach Weiner that copy of Mankiw would come back to bite me in the ass…
Given how the most widely cited unemployment rate is calculated, the cartoon is technically correct. On one hand, not counting people who are not in the labor force as unemployed makes sense- we generally see unemployment as a problem to be fixed, yet I doubt that the stay-at-home mom or the lottery winner sitting on a pile of cash rather than working is anyone’s policy target, so it makes sense to leave such people out of the discussion. That said, the way that unemployment statisticians ask the labor force question (“Have you looked for a job in the last four weeks?”) causes them to catch people who would want to work but have given up on finding a job in their out-of-the-labor-force net.
In order to overcome some of the misleading features of the typical unemployment rate, the Bureau of Labor Statistics also publishes a few other statistics that pertain to working versus not working. One is the labor force participation rate, which shows what percentage of people are either employed or looking for a job:
(Note that the scale of the vertical axis is a little misleading.) With these numbers, we can better understand whether changes in the unemployment rate were more due to people getting and losing jobs or people entering and exiting the labor force. (The labor force participation numbers also explain how we can see increases in both employment and unemployment or vice versa.) This historical data shows that labor-force participation has been declining a bit since recession hit in 2007 or so, which is consistent with the notion that people get discouraged and drop out of the labor force if they can’t find work for a long time.
A close cousin to the unemployment rate and labor force participation rate is the employment to population ratio (it’s exactly what its name implies), which the Bureau of Labor Statistics is also kind enough to publish:
Unlike the labor-force participation numbers, the employment to population ratio shows a sharp decline during the recession rather than a steady decrease over a number of years. Therefore, while it is true that the U.S. unemployment rate is rebounding, it appears to be settling at a place were a smaller portion of the U.S. population is working than before.
But wait- this is the part where I totally blow your mind…as it turns out, the Bureau of Labor statistics publishes a whole smorgasbord of unemployment rates in addition to the typical one. Check out the options:
U-1: Persons unemployed 15 weeks or longer, as a percent of the civilian labor force
U-2: Job losers and persons who completed temporary jobs, as a percent of the civilian labor force
U-3: Total unemployed, as a percent of the civilian labor force (official unemployment rate)
U-4: Total unemployed plus discouraged workers, as a percent of the civilian labor force plus discouraged workers
U-5: Total unemployed, plus discouraged workers, plus all other persons marginally attached to the labor force, as a percent of the civilian labor force plus all persons marginally attached to the labor force
U-6: Total unemployed, plus all persons marginally attached to the labor force, plus total employed part time for economic reasons, as a percent of the civilian labor force plus all persons marginally attached to the labor force
(I am obviously wrong, but I would like to believe that this is what Bono was thinking of when he named his band.) No one of these measures of unemployment is perfect on its on, but, taken together, they paint a pretty decent picture of what the labor market landscape looks like.
I’ve been hesitant to write about this, since every time I try I just end up with phrases like “AN EXCEL ERROR ROFL!!!!” on the page, and I don’t feel like that entirely embodies what I would like to convey regarding the Reinhart-Rogoff situation. So I gave it the old college try on About.com instead. Some highlights:
Harvard economists Carmen Reinhart and Ken Rogoff wrote a short piece in the (non peer-reviewed) American Economic Review Papers and Proceedings entitled “Growth in a Time of Debt.”
Said piece asserted that debt to GDP ratios of over 90 percent are associated with negative average economic growth, whereas lower levels are all associated with positive average growth. (Interestingly, however, the 90 percent debt ratio is correlated with positive median economic growth, which suggests the negative result is being driven by outliers to some degree.) In the piece, the authors were careful to give the “correlation does not imply causation” disclaimer- in this case, that it’s possible that slow economic growth causes high debt ratios rather than the other way around. In other words, their data analysis looks like this:
(Sidenote: I know hindsight is 20-20 and all, but wouldn’t you at least be a little suspicious about the presence of a calculation error when you get a result that is that different from the others?)
Advocates of economic austerity apparently understand neither the correlation versus causation issue nor the concept of peer review and basically nutted themselves over this finding.
Said austerity supporters started inviting Carmen and Ken (though mostly Ken, as I understand it) to fancy policy discussions. In addition, Carmen and Ken wrote a few op-eds where they were much more prescriptive and less careful about highlighting the lack of established causality.
UMass Amherst graduate student Thomas Herndon became suspicious when he couldn’t replicate Reinhart and Rogoff’s result using data they provided to complement their 2009 book. (Fun fact: I suggested that my senior seminar students use this data to write their research papers and they all ignored me.) Herndon then got Reinhart and Rogoff to share their calculations and found that their most noteworthy finding was the result of a sloppy Excel formula. (Sidenote: ROFL!!!! Not even Matlab? Stata? It’s not the most relevant issue, but the JV nature of the analysis is hilarious to me.)
Herndon and two professors published a rebuttal to the Reinhart-Rogoff paper in which they pointed out the Excel error and also challenged some of the other methodology in the original study. (Sidenote: I find it funny that a 6-page non-peer-reviewed paper got a 26-page presumably non-peer-reviewed rebuttal.)
Hold up…I’ll pause here because Stephen Colbert tells is so much better:
Colbert even invited Herndon on the show, which not only made me incredibly jealous but also caused me to send a “neener-neener” email to my students for not taking me up on my paper advice:
Okay, so let’s continue…
Reinhart and Rogoff issued what I will loosely call an apology via NYT op-ed. The general gist of the piece is “yeah, we made a calculation error, but it’s not that important for the end result. Besides, we warned you against interpreting the findings as causal anyway.”
To be fair, the difference between the numbers is the result of all of Herndon et al’s criticisms, not just the spreadsheet error. That said, the spreadsheet error is the difference between negative and positive growth for the 90 percent and over group.
So what do we take from this? I guess it’s a matter of opinion whether the amended result (together with the causality issues) is an argument for austerity. Therefore, I feel that the takeaways from this debacle are a bit more general:
Basing major policy decisions on short, non-peer-reviewed studies might not be the best idea anyone’s ever had. In related news, it’s important to be aware that confirmation bias- the tendency to only pay attention to evidence that supports one’s existing hypothesis- is a powerful force.
It’s just as important to be a good consumer of research as it is to be a good researcher. Betsey Stevenson and Justin Wolfers have some good advice on the subject. I would add to this that, if you are in a position to actually use a set of findings, it’s worth doing a little digging to see how well-vetted the findings are.
As a corollary to the above, it would probably be helpful for academic publications to make it more obvious when work is and is not peer reviewed. I’m not sure exactly why I know that the American Economic Review’s “Papers and Proceedings” are not peer reviewed, so I wouldn’t expect that to be common knowledge.
ALWAYS, ALWAYS check your calculations. Better yet, use a real statistical/math program like Stata or Matlab where you can execute calculations via scripts so that your work is far more auditable.
You may have noticed that I post a decent number of comics from Saturday Morning Breakfast Cereal. While I do know Zach, it wasn’t until recently that I started meddling in the cartoon-generating process. In general, it’s more amusing to see what non-economists come up with on their own, but sometimes I just can’t help myself. So here goes…
The original question:
Econ question: If I wrote a program wherein I and another person constantly traded $1 for nothing, back and forth, does GDP go to infinity?
(For the record, Scott Adams, the creator of Dilbert, actually has a degree in economics, yet I am far more impressed by the issues posed by thoughtful non-economist cartoonists.) Of course this sounds absurd, but there are plenty of things in macroeconomics that sound absurd, so I figured this was worth thinking about for a second. Or an hour. Here’s what I came up with:
I think the part that is most relevant to the question at hand is the notion of “produced.” So, used goods don’t count in GDP unless there is some value-added service associated with selling them, and even then it’s only the value-added part that counts in GDP. If I modified your scenario slightly so say that two people kept paying each other a dollar for a widget of some sort, that widget would only count in GDP the first time it was sold to an end user consumer. Your scenario is a bit more complicated I think, however (perhaps unintentionally). If the dollar going back and forth is exchanged just because, then it would be considered a repeated gift or transfer and not included in GDP because nothing was actually produced. If, on the other hand, the dollar is each time exchanged for some intangible service (a smile, wink, nod, etc.), then there is in fact a dollar of GDP generated with every transaction, since the service is new each time rather then the reselling of a used service. (I’m not even sure what a used service would be exactly, but it sounds kind of dirty.)
Your twitter commenter is right that digging a hole and then filling the hole back in would add to GDP with no net change in the state of the world, and one could make two arguments about this. One argument is that this is a shortcoming in the notion of GDP, similar to the broken window fallacy, which you can read about here: http://economics.about.com/od/output-inc…
Another argument is that, because people were willing to pay both to have the hole dug and filled in, that both activities must have had worth to people. Unfortunately, there is likely also a negative externality imposed on the guy who wanted the hole dug when the hole is filled back in and vice versa, which would counteract the value that is counted in GDP to some degree.
I read a thing a few days ago that I can’t seem to find but is very relevant to this situation. Suppose guy 1 pays $50 to punch guy 2 in the face. Suppose further that guy 2 pays guy 1 $50 to then punch him in the face. The article or whatever’s conclusion was that both guys had no more money than before but had black eyes, so they were worse off but $100 of GDP was created. It’s a cute example, but it isn’t quite correct because it ignores the warm fuzzies or whatever that the guys got from doing the punching, which they had to have gotten since they were willing to pay $50 to do it. When this is taken into account, each guy got a service that they valued at at least $50 plus a black eye. Because both men were willing to accept $50 to get punched, it must be the case that the cost of getting punched was less than $50 to both men. Therefore, both men were made better off on net by this set of transactions, but not by the full $100 of GDP that was created. The reason is that GDP doesn’t take into account wealth destruction, whether it be black eyes or loss of buildings due to earthquakes and the like.
In other words, GDP calculations can be a little absurd on the surface but aren’t totally absurd once you think a little. So apparently this is why Zach was asking his question:
He had actually shared the storyline with me earlier, and I made the following point:
I suppose that the motion of electrons counts as a different service each time, and the nerds are willingly giving the money each time, so as much as I want to say that this doesn’t count as GDP, I’m leaning towards allowing it. You could also just have the computer make a trivial beeping noise or something to count as the service rendered. The important part is that it has to be clear that nerd 2 is actually providing the service worth $1 to nerd 1 and vice versa, otherwise you’re just describing paypal with a zero commission, and it’s the paypal fees that count in GDP, not the money transferred itself. Perhaps describe the scenario as nerd 1 and nerd 2 each installing a program on the machine to accept the dollar in return for a beep?
After this exchange, I sent Zach a copy of Greg Mankiw’s favorite textbook, though I’m not sure how much it helped, since this is well outside of textbook and into thought exercise territory. In other words, it would make a great exam question if you want to give your students ulcers.