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.
The AEA has launched a new site to register randomized control trials (RCTs). The AEA encourages all investigators to register new and existing RCTs. Registration is entirely voluntary and is not currently linked to or required for submission and publication in the AEA journals.
On this site, you can register your forthcoming, ongoing, or even completed RCTs, with as little or as many details as you wish. The site will also permit you to store and make publicly-available additional information on your RCTs (reports, articles, data, and code). We believe that this will prove to be a very valuable resource for investigators to share their work and the site will be widely used by those who wish to find out about on-going and completed studies.
The registry is characterized by:
1) Simplicity and flexibility: Registering a trial is straightforward with only a minimal number of required fields. There is considerable flexibility to provide additional material at the time of registration or at any point in the life of the study. Materials can also be hidden from public view until completion of the study, or be made accessible only with the permission of the PI.
2) Adjustability and memory: Any registry entry can be amended by the PI at any point, but the registry keeps track of all versions.
3) Ability to work as a research portal for your RCTs: The registry can serve as an access point for collaborators, other scholars, students, and the general public providing links to data sets, survey instruments, experimental findings, and experimental protocols.
To register a trial, the PI simply needs to enter the following information: PI name, project title, study location, project status, keyword(s), abstract, trial start and end dates, intervention start and end dates, proposed outcome(s), experimental design, whether the treatment is clustered, planned number of clusters, planned number of observations, and IRB information. Optional fields allowing the PI to customize and enhance the information made available include details on sponsors and partners, survey instruments, an analysis plan, and other supporting documents. Help is available if the PI encounters any problem.
The AEA registry system will provide the PI with reminders to update the registration of an RCT at appropriate points in the trial’s lifecycle. For example, the submitted end date will trigger an email asking the PI to enter post-trial information. If the trial has been extended, the PI can update the trial with the new end date.
We encourage you to explore the registry and to register your RCTs.
The committee on the registry for social experiments
Larry Katz (chair)
So why is this important? I think this pretty much sums it up:
I’ve written about this before- in general, a finding is only considered statistically significant if there is less than a 5 percent chance that the observed result would have happened by random chance. (Hence the use of the 0.05 value in the cartoon.) But think this through a bit- if something has a 5 percent chance of happening randomly, then, on average, that result will be observed one time out of 20 even if there is nothing systematic going on. Therefore, it doesn’t mean a whole lot to see one result that has less than a 5 percent probability of occurring by random chance unless you know that there aren’t a whole bunch of studies out there that tried the same thing and didn’t get the observed result.
This registry is a fantastic development since, if used properly, it will keep track of all of those non-result studies that would otherwise be hidden in researchers’ desk drawers or on their hard drives and therefore be unobservable to someone trying to determine the validity of the research that is actually published. I say “if used properly,” since it’s only helpful to the degree that we can be confident that everyone is actually registering their experiments. Given this, I’m somewhat surprised that the architects of the system didn’t make pre-experiment registration a prerequisite for publishing in an AEA journal, but I’d be willing to bet that that will be coming eventually. Baby steps, I suppose.
If you still want to think more about publication bias and the reliability of the scientific results that you see, check out the following:
(You should know that I spent about 30 minutes figuring out how to disable the annoying autoplay feature. You’re welcome. You can also see the video directly here, especially since I can’t seem to get the sizing to work properly…but consider yourself forewarned about the autoplay issue.) Granted, the conclusions in the video depend heavily on the number used for the proportion of hypotheses that are actually true as well as the assumed rate of false negatives, but the concept is still worth pondering.
This video goes through an example of producing versus shutting down in the short run and shows how to apply the shut-down condition. It also shows how to determine whether a firm would want to exit an industry in the long run The problem is taken from Principles of Microeconomics by Dirk Mateer and Lee Coppock, and is Ch. 9 problem #10.
I apparently have the approximate maturity level of a 12-year-old boy, since I cannot stop laughing at this:
I think part of my amusement comes from the fact that Tyler Cowen took up the cause of overthinking Zach’s cartoons, and there are some choice comments on that post. In case you don’t have time to read them all, just know that the best ones focus on the demand for $2 bills by strip club owners and a perfectly reasonable, in my opinion, speculation regarding the degree to which Canadian strippers jingle, and there are plenty of bad puns involving concepts such as “convexity” and “sticky wages.” (In related news, I’m a tad bitter than I didn’t think of the puns first.)
Tyler’s overall point is that strippers may actually prefer inflation:
Let’s say the standard tip is a dollar, and price inflation lowers the real value of that dollar. A lot of customers won’t substitute into stuffing $1.43 into the stripper’s garments. They might do two or three singles, but strippers will be shortchanged at various points going up the price pole. There is something about handing out a single bill that is easier and more transparent, or so it seems.
Say inflation gets high, or runs on for a long time for a large cumulative effect. At some point the customers switch to giving $5 bills.
Does it help strippers if the Fed issues lots of $2 bills? Well, the leap up to the larger tip comes more quickly, but the customers also stay at the $2 tip level a long time before moving up to $5.
At some margins inflation is bad for current strippers, but good for some set of future strippers. If the economy is close to the margin where individuals upgrade from a $1 tip to a $5 tip, then inflation is good for current strippers but bad for future strippers (for a while).
I think now is an excellent time for a discussion on nominal versus real wages. Nominal wages, which are what most of us are used to thinking about, are just the actual nominal-currency-denominated wages that a worker receives. Real wages, on the other hand, are wages that are denominated in terms of the amount of stuff that the worker can buy with the compensation. Put a bit more simply, real wages are inflation-adjusted wages. In order for the situation illustrated above to actually occur (and in order for Tyler’s argument to make sense), the consumers in the stripper market must have an interest in keeping strippers’ effective real wages stable in the face of inflation.
One reason that consumers might make strippers’ wages keep up with inflation is because they are worried that there will be fewer (or lower quality) strippers if real wages decrease. Of course, this line of reasoning requires the employment choices of strippers to be based on real as opposed to nominal wages. I have no data on whether strippers are more or less rational than the average person, but I do know that people are generally subject to money illusion, which causes their decisions to be biased by nominal as opposed to real values. For example, consider the following experiment:
(I couldn’t easily find an electronic version of the paper, so you get a photo of the hard copy, complete with my chicken scratch from when I was studying for my qualifying exams. Forgive my comment for being slightly idiotic in retrospect.) People seem to understand real versus nominal wages to some degree when specifically asked about them, but they aren’t good at using the real quantities when thinking about happiness or choices. This is, in part, why economists sometimes claim that a society can inflate its way out of a recession- if nominal wages don’t change and inflation is present, real wages decrease…but, if nominal wages don’t decrease, people likely won’t stop working. If businesses are better at thinking in real terms (not entirely convinced that they would be, since companies are made up of people, but go with me here), then they will be more willing to hire and produce more when inflation is present because real wages are lower and the price of the firm’s output is increasing. (The context of this discussion gives a whole new connotation to inflation having a stimulative effect.) By this logic, strippers likely should be wary of inflation, not for the reason illustrated above but due to the fact that it may instead lower their real wages. On the up side for some, however, lower real wages generally mean that will be more employment opportunities for strippers.*
In related news, the Consumerist proposes a savings strategy that is likely to be problematic for strippers…until Tyler’s hypothesized effect of inflation transpire at least.
* Technically, strippers are usually independent contractors who pay a commission to the club for use of the stage. And yes, this probably means that your favorite stripper knows more about business than you do.
This is a conversation that I had yesterday with a friend:
Friend: documentary on ESPN right now that’s all you
Me: I only see SportsCenter…what am I missing?
Friend: ESPN 2
high school coach
agh you just missed it
Me: um, I was writing about that 5 minutes ago
Friend: someday i’ll tell you something you don’t know
but not today
Friend: until then
go *redacted* y’self
I never know whether to pretend that I haven’t seen things before, since I do worry that people will stop sending interesting things my way if they think I already know everything. (Far from it, in reality, so keep the links coming just in case.) It is nice to know, though, that my yelling at the television just about whenever a team punts on fourth down hasn’t gone unnoticed. (In case it’s not immediately obvious that I’m talking about football, there is a fairly nerdy description of the relevant rules in the appendix to the paper referenced below. Also, I recommend getting out more- even Sheldon Cooper knows the basic rules of football.) Why do I do such a thing, you may ask? Because of this:
This paper examines a single, narrow decision—the choice on fourth down in the National Football League between kicking and trying for a first down—as a case study of the standard view that competition in the goods, capital, and labor markets leads firms to make maximizing choices. Play-by-play data and dynamic programming are used to estimate the average payoffs to kicking and trying for a first down under different circumstances. Examination of teams’ actual decisions shows systematic, clear-cut, and overwhelmingly statistically significant departures from the decisions that would maximize teams’ chances of winning. Possible reasons for the departures are considered.
Who knew that David Romer did things that are cooler than writing graduate macroeconomics textbooks? (In fairness, I suppose that marrying Christina Romer is also cooler than writing a graduate macro textbook.) Anyway, the normal person translation of the above abstract is something along the lines of “football teams punt on fourth down far more than they should if their objective is to win football games.”
Recent history has shown that other sports (talking to you, baseball) have embraced the notion of using data analysis to guide decision making, so why haven’t Romer’s findings caught on? Do football coaches know something that he doesn’t? What would happen if Romer’s findings were to be put into practice?
(You can read more on the subject here.) Hey, who would’ve thought that numbers don’t always lie and can actually tell us useful things and help us make better decisions? Given this, why do so many teams blindly punt on fourth down? (Post hoc ergo propter hoc fallacy not withstanding, I find it of particular note that the coach stopped punting in 2005, the same year as the date on the Romer paper.) Interestingly enough, the explanation is almost virtually identical to that for herding behavior among mutual fund managers- namely, that people (probably correctly) think they are less likely to get fired if they make mistakes that everyone else makes than they are if they make their own mistakes:
Coaches are afraid. No one wants to be the guy who gets fired because he stopped punting. And the same fans and analysts who clamor for innovation are actually fueling that fear. The mob nearly tarred and feathered Falcons coach Mike Smith when he went for it on fourth-and-inches in overtime against the Saints in 2011. Bill Belichick almost lost his hoodie-wearing privileges after going for it on fourth-and-2 from his own 28 against the Colts in 2009. San Diego State coach Rocky Long announced before the 2012 season that he might stop punting, then had to field so many questions about it on a weekly basis that he began refusing to discuss his fourth-down plays with the media.
In other words, football doesn’t have a Billy Beane who is basically forced to do something unconventional due to a lack of other options. (Think about it- would we be talking about “moneyball” strategies if the Oakland A’s weren’t cash poor?) Good thing David Romer is a macroeconomist, since that way at least he’s used to organizations not taking his policy advice. =P
This video explains how to think about the difference between accounting profit and economic profit and shows how to calculate each. The problem is taken from Economics by Dean Karlan and Jonathan Morduch, and is Ch. 12 problem #8.
I liked this video, but not necessarily enough to subscribe to get the whole thing. Kahneman seems pretty optimistic that people can stop being irrational if they know that they are making suboptimal choices.