Ask And You Shall Receive, Economic Superhero Edition…

I obviously know that correlation doesn’t imply causation, but sometimes I see a sequence of events and I’m like COME ON…case in point:

And lo and behold, less than 12 hours later (focus your attention on the hovertext)…

See what I’m saying?????? Hey world, I, uh, want a pony next. Here’s the full comic:

Not surprisingly, I have some thoughts here (because ruining jokes is one of my favorite hobbies). First, this comic presupposes that higher compensation will result in our economic superhero working more…but one thing that I’ve noticed about superheroes, specifically those who technically have no superpowers (looking at you, Batman and Iron Man), is that they’re really rich. If our econ superhero follows this pattern (sidenote: HAHAHAHAHAHAHAHA), I’m not convinced she’d be particularly motivated by monetary compensation- even worse, she could be on the backward bending part of the labor supply curve, in which case higher compensation could result in her doing less superheroing rather than more!

Second, I kind of want to applaud our super-economist for only charging a 50 percent commission, thereby leaving the lady with a decent amount of consumer surplus. Third, well…wouldn’t Captain Surge create competition in the superhero market and thus lower rather than raise prices? Shouldn’t Captain Surge be going to places where there’s s superhero shortage, not just show up to places that already have superheros and create a superhero glut? I guess what I’m saying is, like my feelings regarding much other surge pricing implementation, I am largely unimpressed by Captain Surge (but do find him pretty realistic).

I guess it’s also a good time to remind you that this exists:

You’re welcome.

On the Revival of the “Quarterly Capitalism” Discussion

Ok, I’m a little late with this, but, um, he might kind of have a point…

That said, he’s gonna be so mad when he finds out who took up the cause first…

In any case, let’s discuss…

Currently, publicly traded companies (“public companies,” though importantly distinct from being a government entity) are required to report their business performance once a quarter. This seems helpful from a transparency perspective, but it also has the unintended consequence of companies being obsessed with “hitting their numbers” every 90 days or so. This doesn’t *have* to be a problem, but it’s entirely likely that focusing on short-term profits comes at the expense of maximizing long-run profitability.

This phenomenon, sometimes referred to as “quarterly capitalism,” isn’t simply the result of companies trying to show off every time they have to release earnings numbers. Instead, they’re mainly responding to market incentives- stock prices tend to respond strongly to quarterly earnings, and the perceived performance of company managers is closely tied to stock performance. This basically creates the corporate equivalent of being judged on your weight-loss progress on a weekly basis, and, just like such reporting can lead to unsustainable binge dieting, quarterly financial reporting can lead companies to engage in analogous, say, inefficient cost-cutting measures.

Do I really think that moving to six-month reporting requirements would solve the quarterly capitalism problem? No, mainly since most useful long-term projects have timelines of far more than six months. (I also do worry about the decrease in transparency nowadays.) But I like that the conversation is being had, since it forces discussion of what is referred to by behavioral economists as “myopic loss aversion.”

“Myopia,” taken literally, means near sighted, and, in a decision-making context, means short sighted, or overly focused on the short run. Loss aversion is the phenomenon where people hate losses more than they like equivalent gains. Myopic loss aversion is thought to lead to irrational choices, or choices that are out of line with maximizing long-term returns (or, somewhat equivalently, happiness.). In a personal investing sense, one of the best pieces of advice I can give is to not look at your stock portfolio every day, since you’ll probably get obsessed with short-term ups and downs and start buying and selling in unproductive ways. In a similar sense, professional investors would often be well served to take the quarterly reports and put them in the desk drawer rather than poring over them…or at least focusing on the information that pertains to long-term plans rather than short-term results. (I’m of course making the assumption that the professional investors are working on behalf of clients who are taking a long-term view of their returns.)

Hopefully this makes sense as a logical matter, but unfortunately it’s harder to act on than it might seem. First, just knowing that they’re doing something unproductive doesn’t always make people able to stop doing the unproductive thing. (The dieting analogy keeps working here I suppose, albeit for different reasons!) In addition, it’s harder to stop being myopic when others involved in a market are still committed to the myopic behavior, and it’s extra hard to convince a whole bunch of people to change their thought processes at the same time. Nevertheless, well…glad we had this talk at least. Baby steps…

This post originally appeared on Medium.

P.S. In case you find myopic loss aversion interesting, here’s a paper that suggests it could even explain the equity premium puzzle.

Here are the Victims of Insider Trading, Hope I Didn’t Keep You Waiting Too Long…

We’ve officially gotten to the “actually insider trading is kind of fine” stage of the universe…

Opinion | Show me the victims of insider trading. I’ll wait.

Opinion | Show me the victims of insider trading. I’ll wait.

Meanwhile, take an honest look at the ways the institutions you belong to manage to hoard the best benefits for people like you.


Spoiler alert: it’s not fine, and here’s why:

Here are the Victims of Insider Trading, Hope I Didn’t Keep You Waiting Too Long

Here are the Victims of Insider Trading, Hope I Didn’t Keep You Waiting Too Long

The way 2018 is going, it should not shock you too much that we’ve gotten to the “a little insider trading never hurt anyone” phase of the…


Since I’m guessing that I have a more knowledgeable than average audience here, I’ll elaborate on one point from the original article that is basically correct. Technically speaking, the efficient markets hypothesis (EMH) comes in three flavors:

  • weak form: can’t systematically profit using past price information
  • semi-strong form: can’t systematically profit using public information
  • strong form: can’t systematically profit using even material nonpublic information

Not surprisingly, the strong form of the EMH can’t really hold without substantial insider trading in a market, so in a very specific way insider trading can make markets satisfy a stronger form of efficiency. That said, this observation once again highlights the fact that there is generally a tension rather than a correspondence between efficiency and fairness. In addition, these definitions of efficiency don’t take into account the potential inefficiencies generated by asymmetric information, which we generally put under the heading of market failure.

Oh, wait, one other thing…while McArdle is correct in that random people probably shouldn’t try to pick individual stocks, she leaves out that many people absolutely *should* hold a diversified portfolio that includes stocks (generally via index funds or other low-fee products). Unfortunately, the insider/outsider divide isn’t between individual and professional investors, and there’s no reason to think that asset managers and the like wouldn’t also find themselves on the losing end of insider trading, so “don’t hold individual stocks” isn’t really relevant to the discussion at hand or a solution to the insider trader problem.

My Interest In The New Goldman Sachs CEO Goes Pretty Much Exactly As You Would Expect…

In learning about the music industry, I often think about how what behavioral experiments I would want to run if I had the proper resources/infrastructure/etc. Along these lines, one thing I’m curious about is how people’s willingness to pay for music is affected by the financial situation of the people creating the music- in other words, are people more willing to pay for music (as opposed to download illegally, stream, whatever) when they know the money matters to the musicians? I’ve actually brainstormed with people about how to implement such a thing, and…it’s harder than you might think. See, one feature of economic experiments is that we’re not supposed to use deception- in this case, it means I would actually have to find musicians with differing levels of income rather than just tell hypothetical background stories. Obviously such people exist, but I’m going to go out on a limb and hypothesize that the music created by the high-income musicians is different from the music created by the low-income musicians in a way that is related to willingness to pay.

In a perfect world, I guess I would find a band where the members have day jobs that differ widely in income, since then I could present the same music with different backstories without having to make anything up. (If you know any such unicorn bands please do drop me a line!) I guess something like this would be a decent backup plan:

Goldman Sachs’ president has gigs as a DJ around the world

Goldman Sachs’ president has gigs as a DJ around the world

His Fleetwood Mac remix was recently featured on SiriusXM.


I like this on principle, since I feel pretty strongly that people should have hobbies and interests and whatnot, but I also can’t help but think “hmmm, now if I find an equivalently popular DJ who isn’t a CEO as my control group”…

Turns out the story gets more interesting…apparently the Sirius exposure that D-Sol (yep, that’s David Solomon’s stage name) get ended up getting him a spot on the Billboard charts:

I mean come on, this is #goals…in case you can’t see the chart itself, here’s the description:

Dance/Mix Show Airplay

This week’s most popular current songs ranked by total weekly plays on full-time dance-formatted stations as well as mix show plays on mainstream top 40 and select rhythmic and adult top 40 stations that have submitted their hours of mix show programming, as monitored by Nielsen Music, to Billboard. Songs are defined as current if they are newly-released titles, or songs receiving widespread airplay and/or sales activity for the first time.

Obviously I’m curious as to the effect that such airplay has on streaming and sales behavior…unfortunately, I don’t have data on streaming, but here’s the sales trajectory:

Let’s unpack this, since the chart timing is a little complicated…the Billboard chart date is July 28, 2018, which means it was published on July 24 and covers the period July 16-22. The song didn’t remain on the chart the next week (boo), so we can think of this as the period over which the song got the bulk of its airplay attention. That’s a little weird but interesting, since it suggests a couple of things: one, that the sales interest preceded the airplay interest rather than the other way around, and two, that the airplay and chart recognition didn’t lead to a huge spike in sales. (Granted, we don’t know that we wouldn’t have seen more of a decline if the airplay hadn’t happened, but the magnitude of the effect is still limited by the fact that sales couldn’t have been less than zero in the “counterfactual” situation.)

As a related matter, I have an idea…so I’m going to make a song, and enough of you are going to buy it so that I can get on the Billboard charts, since from what I can tell the bar is a lot lower than it used to be. (The chart above is an airplay chart, so the sales data I showed here doesn’t speak to this point directly, but this is the pattern that I see more generally.) Wait, now I’m wondering if David Solomon just had 1,000 of his closest friends do him a solid… 🙂

In case you’re curious, here’s the song in question (there’s also an extended version if you’re super into it):

Since you’ve read this far, I figured I’d pass along another relevant item I came across in my research:

Yes, I’m trying to not be annoyed by the misspelling because it’s just too funny. I’m also trying to not take issue with the following headline:

Calvin Harris Tops the ‘Forbes’ Highest-Paid DJ List For Sixth Straight Year

Calvin Harris Tops the ‘Forbes’ Highest-Paid DJ List For Sixth Straight Year

Calvin Harris has been named Forbes’ highest-paid DJ in the world for a sixth year in a row. Check the full list of Forbes’ top 15 paid DJs here.


I mean, technically…though looking at the numbers, I think the article might actually be correct as stated, at least for the top spot for the time being.

What The Brady Bunch Can Tell Us About Housing Market Dynamics…

I got bored so I looked up some numbers…

What The Brady Bunch Can Tell Us About Housing Market Dynamics

What The Brady Bunch Can Tell Us About Housing Market Dynamics

So I have a new dream purchase, since I learned this week that the Brady Bunch house is up for sale. I’m still kinda pissed that I missed…


Personally, I like the visual that I used here, namely “index everything to 100 at the start and then see how things grow differently over time,” but I can’t tell if the approach is intuitive to everyone. Also, it’s kind of crowded, but here’s most of the numbers in one picture:

In case you haven’t seen it before, the income lines collectively give the picture for the increasing income inequality that we talk about so much. (Note, however, that inflation isn’t controlled for in these numbers, so they overstate increases in living standards but are appropriate to compare to unadjusted house prices.)

Causal Friday: The Dumbest Differences-in-Differences Ever, Viral Video Edition…

It’s causal Friday, so I’m poking around in some data trying to make a case for cause and effect. More specifically, I’m drowning in a differences-in-differences analysis trying to construct a proper control group. (In this case, identifying a control group isn’t conceptually difficult, it’s just really annoying to pull the data.)

So what is a differences-in-differences analysis? It’s…well, pretty much exactly what it sounds like- it’s kind of nice when that happens. Here’s a little thing I wrote up a while ago for my team at work (who had more of a data science than social science background), or you can consult Wikipedia. (note: you will never convince me it’s “difference-in-differences” and not “differences-in-differences”) The general principle behind differences-in-differences is that you can’t just do a before-after comparison to identify the effect of an event, since you’d also need to know what the before-afters look like for stuff that wasn’t subjected to the event. For example, consider the following hypothetical question:

Fairlife milk initiated a new marketing campaign at the beginning of 2018, and so far sales of Fairlife milk are 5 percent higher than for the same portion of 2017. Should the marketing campaign be considered a success?

Hopefully it’s at least somewhat intuitive that the answer should be “I dunno, how do the sales of non-Fairlife milk compare to last year?” If milk sales more generally are, say, also up 5 percent, it’s not particularly likely that the marketing campaign is doing much. On the other hand, if sales for the milk industry were generally down compared to last year, the marketing campaign should be viewed much more favorably.

So this is what I was trying to do, but with music sales. Remember this?

Is this the best way ever to quit your job? Marina Shifrin resigns with Kanye West dance video

Is this the best way ever to quit your job? Marina Shifrin resigns with Kanye West dance video

Ever wanted to quit your job? Why don’t you take a leaf out of video producer Marina Shifrin’s book and do it through the medium of “interpretive dance”?


For context, I’m using this as a motivating example for a larger analysis on music sampling. So I dutifully went through and identified two other songs from the same Kanye album that were about as popular as ‘Gone” before the video above went viral, and then I looked up the sales of all three songs (this is way more annoying than you’d think it should be) before and after the video’s posting date so I could do a very careful and nuanced analysis. Clearly I didn’t think things through, since, well…

This is only for the song used in the viral video, so I don’t technically have a comparison group (yet), but I mean COME ON…nonetheless, I persisted and added my control group:

(I changed the scale of the graph so it looked just wonky rather than useless.) You’ll be pleased to know that my confidence in the video causing a sales bump has not decreased…but let’s calculate some differences in differences anyway (it’s not really possible to run a regression here). So here are the numbers for 4 weeks before and 4 weeks after:

These numbers are pretty easy to interpret- an effect is positive if the differences-in-differences numbers are positive and vice versa. (An effect is nonexistent if the difference is close to zero.) Now I guess technically I should run a test to see whether the differences are *statistically* different from zero, but 1. that’s kind of hard with 3 data points, and 2. I mean come on.

The real punch line in all of this is the fact that the video has been taken down on copyright grounds…I’m, um, not sure you’re doing it right, record label…

Experimental Pitfalls Are Generally Dumber Than We Imagine, Now With More Dogs

Ok, story time, so go grab your blankie and a beverage…

A number of years ago, I taught an econ tutorial entitled “Sex, Drugs, and Rock & Roll”…it was a neat class- as the name would suggest, we looked at papers on birth control, drug legalization, the music industry, and so on. For reasons I’m still not sure I understand, it was a somewhat peculiar group of students- basically the football team, the kid who as far as I could tell tutored the football team, and a female transfer from Tulane (because of hurricane Katrina). (I actually confirmed with her beforehand that she was ok with the gender ratio, given the subject matter…turns out she wasn’t easily fazed and later explained to everyone how to make meth.)

Anyway, I digress…the first paper I assigned was authored by a combination of friends and classmates- it wasn’t so much directly relevant to the subject matter but it has “Sex, Drugs, and Rock & Roll” in the title so I figured it would be a good place to start getting students used to reading academic research. The discussion…well, didn’t go as I expected.

Basically, the football team came in and explained that it was funny to read the paper because they participated in the experiment. So, PSA: if you use the CLER Lab at Harvard your subject pool is the Harvard football team I guess. (I don’t mean to imply this is positive or negative, just that it might affect generalizability.) Given this information, I found it far more interesting to have them talk about their experience than to jump right into talking about the results of the paper. The main thing I wanted to know was essentially “did you take the task seriously and think things through?”

The responses were “meh” at best, from what I remember. I pushed back, asking something along the lines of “but you get paid more if you performed better at the task, did that not serve as an incentive?” The response was basically this:

Again, I’m not criticizing the students- I completely believe that effort isn’t costless even when a person doesn’t have anything better to do, so it’s entirely possible that the kids were in fact maximizing their utility. But it gave me something interesting to think about regarding experimental design and how to interpret experimental results. In general, economists are wary of asking hypothetical questions about preferences and behaviors, since there’s good evidence that what people say they would do or what they think they would do doesn’t always coincide with the choices that they actually make. To mitigate this problem, experimental economists try to give subjects tasks where payoffs depend on behavior (usually in addition to giving a payment for showing up), since this supposedly gives the subjects proper incentives to treat the task as though it’s real. Economists have even been known to do their experiments in developing countries, since that enables the research budgets to create stakes that are more real than trivial.

The discussion with my students makes me think that we need to be more critical regarding whether our experiments give sufficient incentives to elicit true behaviors and preferences. In addition, economists could probably do more to assess both during and after the experiments how seriously the subjects took their assigned task. In any case, the bottom line is that the success of an experiment depends crucially on subjects taking the task seriously and behaving as expected in a logistical sense, and these characteristics can’t be taken for granted.

Or, put more succinctly, here’s a helpful warning:

I’ve been watching this all day and I can’t stop laughing. (probably related: Gizmo looks a little worried at the moment) For context, there’s this thing going around Twitter where people try to see whether their dogs understand object permanence by holding up a sheet and then running away as it falls. I mean, what could possibly go wrong with this clearly rock solid experimental design?

Update: There’s a point brought up in one of the comments below that I think warrants discussion…I certainly didn’t intend for the takeaway from this post to be “experiments are bad, burn them,” but I see how it could be taken that way. If anything, I’m suggesting the opposite, so allow me to explain. If subjects aren’t fully engaged in an experiment, this probably biases the experiment towards “no effect” rather than creating effects where none exist. In the dog scenario, for example, maybe the chihuahua does in fact understand object permanence, but we can’t document the phenomenon because the dog’s behavior caused the experiment to be garbage. Therefore, I’m not advocating for questioning results so much as questioning “non results.” We talk about a “replication crisis” in economics, where a surprisingly large percentage of documented effects can’t be re-documented in subsequent experiments. These numbers are general used to call the initial findings into questions, and I guess I’m suggesting that we should go easier on this suspicion until we can confirm that such lack of replicability isn’t driven by the sorts of issues I describe above. I guess I’m also trying to help researchers make their budgets go further, since publication bias means that non results often just get shoved in the file drawer, never to see the light of day.

How Monopsonies Work, Now With More Numbers…

You guys, I love monopsonies…for starters, it’s a fun word to say, and it makes people do a double take when they initially think you said “monopoly.” Definitionally, a monopsony is a market with only one buyer- basically the economic counterpart to a monopoly, which is a market with only one seller. Not surprisingly, the buyer in a monopsony has all of the market power in much the same way that the seller in a monopoly does, and largely for a mathematically analogous reason.

Economists have been talking about monopsonies more than usual as of late, most often in the context of labor markets. In labor markets, companies are the buyers (or, perhaps more accurately given the 13th amendment, the renters) and people are the sellers of labor. When the number of employers in an area competing for workers is small, firms are generally thought to have “monopsony power.” This is a little different from literally being a monopsony, but you can think of monopsony power as the ability to act like a monopsony but to a lesser degree.

So what’s interesting about monopsonies in labor markets? Here’s a quick summary:

  • In competitive markets, i.e. markets with large numbers of companies and workers, minimum wages are thought to decrease employment.
  • If a labor market is a monopsony (or if employers have monopsony power), minimum wages could actually increase rather than decrease employment.

This distinction is obviously important from a policy perspective, since minimum wages look way more appealing if they don’t cause people to get laid off. Now, I could try to explain to you why minimum wages work this way using some fun graphs and whatnot, but I’ve come to learn that not everyone’s brain wants to operate at an abstract conceptual level, so let’s work through a simple example instead.

Ready? I’m gonna try to do this without using any econ-specific terms (they’re not as fun to say as monopsony), and we’re going to talk about a company that makes widgets- yes, I know this is a tired econ thing, but Widget is the name of my mom’s cat so I’m asserting it’s fair game.

First, here are some numbers on how many widgets workers can produce:

You’ll note that the “incremental widgets” numbers are decreasing as more workers are added- this is generally reasonable, since most production faces a diminishing returns or “too many cooks in the kitchen” problem. Now let’s say that the company can sell as many widgets as it wants at a price of $10 each- now we can see how much each worker would add to the company’s revenue (does revenue count as an econ term?)

If we want to figure out how many workers the company wants to hire, we need to know how much the workers cost. The thing about workers is that some of them will work more cheaply than others (even if they’re of equivalent quality), and this is relevant for a monopsony, since they’re not so small that they can increase their hiring without pushing up the going market wage. (In fact, this feature is the crux of why monopsonies look different from competitive labor markets!) Let’s assume the wage required to get each worker to work looks like this: (you can think of everything in per hour terms, per day, whatever, it doesn’t really matter)

We can now calculate how much it would cost to hire 1 worker, 2 workers, etc., and we can also calculate the incremental cost of each additional worker:

I feel like this requires some explanation since it’s not really intuitive…if you want to hire the first worker, things are pretty simple, but if you want to hire the second worker, you not only have to pay the second worker the $20 to get him to work, but you also have to pay the first guy $20 rather than $10- there are a number of reasons for this, but you can just imagine that the first guy will get really pissed if he makes less money than second guy for doing the same job. This means that the incremental cost of hiring an additional worker includes not only his wage but also the additional compensation that has to be given to everyone who came before. (This is seriously the most important point so keep staring at it until it sinks in. I’ll wait.)

So take a look at the relevant numbers so far- how many workers does the company want to hire?

Does the company want to hire the first worker? Sure, since that worker brings in $120 and only costs $10. (just assume that labor is the only cost of production) Does the company want to hire the second worker? Sure, since the second worker brings in an additional $100 but only adds $30 to the company’s costs. If we keep analyzing in this way, we can conclude that the company will want to stop hiring after it hires 3 workers. (and will pay a wage of $30)

Now how do things change if a minimum wage is imposed? Let’s assume that a minimum wage of $40 is set. (Now I look real generous to those people who interpreted the numbers as being per hour.)

Workers 1, 2, 3, and 4 are happy to work for the minimum wage, so the company can hire up to 4 workers at $40 each. After 4 workers are hired, however, things change dramatically- in order to hire the 5th guy, the company not only has to pay him $50 but also has to pay each of the 4 other workers $50 rather than $40. How many workers does the company want to hire now? (This is the last set of numbers, I swear.)

Now the company would find it profitable to hire the first 4 workers but not the 5th worker. BOOM- I just showed you a case where a minimum wage would increase rather than decrease the number of workers hired.

So why did this happen? Put simply, the minimum wage took away the “well if I hire you I have to pay everyone else more too” feature of the company’s analysis, at least for the first 4 workers. That said, the minimum wage still creates somewhat of a double-edged sword in terms of employment, since it also made it incrementally more expensive to hire the 5th guy than it was before. As a result, minimum wages placed on monopsonistic markets can both encourage companies to hire more workers and discourage companies from setting wages just above the minimum wage. (This is relevant for companies that pay just above what would be the minimum wage, since it could actually cause them to decrease wages!)

I’m not trying to convince you that minimum wages are good, I’m just walking you through some numbers so that you don’t do the “I took one econ class once and models of competitive markets are always applicable” thing that causes economists to call you an ass clown behind your back. One last thing- in case you (understandably) have the follow-up question of “how prevalent is monopsony power in labor markets?”, here’s some reading material for you to peruse. Spoiler alert: the answer is “too prevalent to ignore.”

Update: You can see a version of this story on Medium if you prefer.

Economist Beverages Just Got A Major Upgrade…

Every Friday at about 5pm or so, Justin Wolfers declares it beer o’clock on Twitter:

This is nice and all (and, honestly, a helpful reminder to maybe stop working even though I generally ignore it), but I’ve always felt like we could do better with the econ-associated beverages. And it turns out we can…

Maybe, as a behavioral economist, I’m biased, but this is just so good. Also, here’s the reference in case you’re not familiar, so you even get some weekend reading material with your weekend booze suggestions.