Wednesday, 21 May 2025

Try this: Songs about economics

Time for a spot of leisure? Looking for something to listen to while unwinding? Try this Spotify playlist by John Hawkins (University of Canberra), titled "Songs about economics".

It has some obvious classics like "(I Can't Get No) Satisfaction" by The Rolling Stones, "Money, Money, Money" by ABBA, and "Money" by Pink Floyd. It even has some more contemporary songs like "Price Tag" by Jessie J., "Bills" by LunchMoney Lewis, and "7 Rings" by Ariana Grande. And a few songs that are quite obscure (at least, to me, since I had never heard them before), like "Offshore Banking Business" by The Members, and "Capitalism" by South Korean rapper Jvcki Wai.

Given the breadth of songs on the playlist though, there's some notable admissions. Why not include "Mo Money, Mo Problems" by The Notorious B.I.G.? Or "Money Trees" by Kendrick Lamar? Or even more obviously, "Minimum Wage" by They Might Be Giants? Or, given that Hawkins is Australian, "Blue Sky Mine" by Midnight Oil?

As a bonus, you should listen to this song, "There is No Depression in New Zealand" by Blam Blam Blam:


Enjoy!

[HT: John Hawkins, in this article in The Conversation about Spotify]

Tuesday, 20 May 2025

Black Mirror Season 7 illustrates the ultimate version of customer lock-in

[This post contains spoilers. You have been warned.]

I love the TV show Black Mirror. Charlie Brooker (the writer of almost all episodes of the show) is an evil genius. Nearly every episode depicts some dystopian near-future that is just plausible enough to make you both worry, and think. The first episode of the latest (seventh) season, titled Common People, is a perfect illustration of this. It is also a perfect illustration of customer lock-in, albeit at an extreme level. From the Wikipedia description of the episode:

Welder Mike Waters (Chris O'Dowd) and schoolteacher Amanda (Rashida Jones) have been married for three years and are trying to conceive a baby. One day while teaching, Amanda collapses, and doctors discover she has an inoperable brain tumor. Mike is introduced to Gaynor (Tracee Ellis Ross), a representative from tech startup Rivermind Technologies. Gaynor explains that Rivermind can remove the tumor and replace her excised brain tissue with synthetic tissue powered by their servers. While the surgery is free, the couple agree to pay a monthly subscription fee to give Amanda a chance at living a normal life again.

Initially the service seems to help Amanda, but as time passes they find that it has several limitations which can only be bypassed by subscribing to the costlier "Plus" tier, as opposed to their current "Common" tier. Unbeknownst to Amanda, she begins interjecting brief advertisements into her daily speech.

As I describe in my ECONS101 class, customer lock-in occurs when consumers find it difficult to change once they have started purchasing a particular good or service. High switching costs (the cost of switching from one good or service to another, or from one provider to another) are likely to generate customer lock-in, because a high cost of switching can prevent customers from changing to substitute products. High switching costs could also, in some cases, prevent consumers from stopping buying the good or service - that is, the switching cost causes the consumers to keep buying the good even if they would want to stop (if there was no switching cost). This is the case for subscriptions, for example (see here or here or here).

In this case, Rivermind appears to have discovered the ultimate form of customer lock-in. The switching cost that Mike and Amanda face if they try to cancel their Rivermind subscription is that Amanda dies (or becomes comatose - the episode is somewhat unclear on this point). That switching cost is obviously very high and provides a strong incentive for Mike and Amanda to keep their subscription going. They are locked into the subscription, which is quite expensive.

Rivermind doesn't just profit from Mike and Amanda through their subscription. Rivermind also engages in a form of multi-period pricing. Typically, firms engage in multi-period pricing by starting new consumers with a low price, and then raising the price once those consumers are locked in. This is what utility firms are trying to do when they offer a discounted rate for electricity or broadband for new customers (for a limited time!). The price is initially low, and then when the new customers are locked in, the price increases (because the discount ends).

Rivermind's approach is somewhat different to the standard case of multi-period pricing. Instead of directly raising the price of the service that Mike and Amanda receive, Rivermind degrades the quality of that service (by introducing advertising). Rivermind then introduces an advertising-free tier that is more expensive (which Mike and Amanda are invited to 'upgrade' to, even though tit is really just a more expensive price for the service they started with). Rivermind then also introduces more tiers of subscription with greater coverage and more perks (and even higher prices).

The Black Mirror episode focuses on the increasingly desperate ways in which Mike tries to keep the subscription going. However, my takeaway is that it illustrates how firms can lock consumers in with switching costs that are non-monetary, and then profit from those locked in consumers. Thanks Charlie Brooker - now you've given me something else to worry about in the dystopian near-future.

Read more:

Monday, 19 May 2025

The impact of Nobel Prizes and MacArthur Fellowships on the winners

What happens to the research productivity of winners of top research awards? On the one hand, a research award like a top fellowship or a Nobel Prize might increase a researcher's impact, as other researchers follow the path they have laid down. On the other hand, maybe there is some 'mean reversion', where a previously high-flying researcher simply returns to a less stellar research trajectory (which would look like a decrease in productivity). Or, perhaps a top research award grants a researcher the freedom to explore new, higher-risk areas of research, which could lead to much higher, or much lower, productivity overall?

The question of what happens to researchers after winning a top research award is addressed in this 2023 article by Andrew Nepomuceno, Hilary Bayer, and John Ioannidis (all Stanford University), published in the journal Royal Society Open Science (open access). They looked at the pre- and post-award citation counts for all 72 winners of the Nobel Prize in chemistry, medicine, or physics over the period from 2004 to 2013, and 119 of the 238 McArthur Fellows (only including those in STEM or social science fields) over the same years. Specifically, they compared publications published in two periods of three years: (1) the two years before the award and the year of the award; and (2) the three years after that. They counted citations for the pre-award period up to 2015, and the post-award period up to 2019 (so that both the pre-award and post-award periods had the same number of observed years of citations).

In their main results, Nepomuceno et al. report that:

Nobel Laureates and MacArthur Fellows received fewer citations for post-award work than for pre-award work... The difference was driven predominantly by Nobel Laureates while there was little difference, on average, for pre- versus post-award citation impact for MacArthur Fellows. The median decrease was 80.5 citations among Nobel Laureates and 2 among MacArthur Fellows. For Nobel Laureates, the decrease reached statistical significance (Wilcoxon signed-rank test p = 0.004), whereas for MacArthur Fellows the decrease was not statistically significant (Wilcoxon signed-rank test p = 0.857)...

Post-award citation impact was lower than the pre-award citation impact for 45 of 72 (62.5%) Nobel Laureates and for 63 of the 119 (52.9%) MacArthur Fellows.

Both Nobel Laureates and MacArthur Fellows suffered a reduction in the citation count per-publication after receiving their award, but for different reasons. The Nobel Laureates published the same number of papers in the period after the award as they did before the award. But their lower citations mean that the citation count per-publication was lower. In contrast, the MacArthur Fellows published more papers after the award than they did before the award, but with no change in total citations (again, meaning that the citation count per-publication was lower).

One major difference between the two groups is age - Nobel Laureates are much older than MacArthur Fellows. So, Nepomuceno et al. conducted further analyses stratified by age (in three groups: under 42 years old, 42-57 years old, and over 57 years old), and found that:

...the declining citations pattern was seen only for researchers who were 42 or older at the time of the award, while an opposite pattern was seen for early career researchers who were given an award (especially MacArthur award) at an age of 41 or younger.

However, looking at Table 2 in the paper, it is clear that the negative impact on total citations is largest for the youngest Nobel Prize winners (those aged under 42 years), but is negative for all three age groups. In contrast, there is a positive impact on citations for the youngest McArthur Fellows, and a negative impact for McArthur Fellows aged over 42 years.

Overall, Nepomuceno et al. conclude that:

Although the MacArthur Fellowship and Nobel Prize selection committees share a stated goal of assisting winners in realizing their potential more fully, in terms of citation counts neither the MacArthur Fellowship nor the Nobel Prize heralded increased research impact for the subsequent work and for Nobel Laureates there was even a significant decline.

It is tempting, then, to conclude that these awards are not a good idea. I'm not so sure. I think the research highlights different impacts of the two awards, and I think we learn something potentially important from this. Nobel Laureates may tend to rest on their laurels (pun intended), or may suffer from mean reversion. Or, perhaps they use the profile accorded by their new status as Nobel Laureates to try and have greater policy or political influence, with an opportunity cost of lower research influence. That suggests that it is better to award Nobel Prizes to end-career academics, lest younger academics be diverted from important and path-breaking research. The recent trend in awarding Nobel Prizes to younger recipients (definitely noticeable in economics) may therefore have a negative unintended consequence. In contrast, because there is a positive citation impact for young recipients, the MacArthur Fellowships should be targeted in greater proportion to younger researchers. There is less to be gained from awarding those Fellowships to end-career academics.

To be fair, that is more-or-less how those two awards have historically been allocated: Nobel Prizes to end-career academics, and MacArthur Fellowships ('genius grants') to young stars. This research suggests that might be an important practice to continue.

[HT: Marginal Revolution, back in 2023]

Saturday, 17 May 2025

The characteristics of the 'young stars' in economics

The top young 'star' economists represent the future leaders of the discipline. Understanding where they are coming from, what they are studying, and where they are going to, is therefore important. This 2019 article by Kevin Bryan (University of Toronto), published in the journal Economic Inquiry (ungated version here), provides a look at the 'young stars' in economics over the period from 2013 to 2018 (who are mostly likely to be newly tenured professors now, in 2025). [*]

Bryan focuses his sample of top economists, defined by those who received multiple 'flyouts' for academic job interviews at top universities, between 2013 and 2018. As he explains:

While applications and interviews are largely nonpublic, flyouts are often publicly posted on department seminar lists, and accepted offers are of course publicly viewable on the hired student’s vita... This suggests two possible definitions of a “star”: those who accept top offers, and those who are flown out to top places. The problem with the former is that one of the questions we would like to answer is where top students take jobs, and using the job accepted as a definition begs the question.

For this reason, our definition of a star is any economist within 8 years of beginning their PhD, who has never had a permanent job after graduating, and who has received a sufficiently large number of high quality flyouts... We begin with a list of the top 25 U.S. economics PhD programs in the U.S. News 2013 rankings, then add eight top business schools which frequently hire economists in nonfinance positions, Harvard Kennedy’s policy program, and 10 European and Canadian programs which regularly fly out top junior candidates.6 For each of these 44 programs, we gathered flyout lists from departmental seminar websites each year between 2013 and 2018, and augmented these with e-mail requests to departments which do not post flyouts publicly... We then assign consistent weights to a flyout at each program, with more prestigious flyouts receiving more weight, and consider a star any student who receives sufficiently many weighted flyouts...

This results in a sample of 226 'young stars' in economics, and Bryan summarises where those students are from, what they have been doing, and where they ultimately went to, using data collected from the students' CVs, job market papers, and LinkedIn. First, in terms of background, Bryan reports that:

The 226 star students come from 40 countries, of which 35% are American, 35.4% are European, and the remainder are from the rest of the world.

Notably, there was one student from New Zealand in Bryan's sample. I wish I knew who it was, but honestly, I have no idea! Then, in terms of where they graduated, Bryan notes that:

While the national origins of star students are diverse... the PhD program diversity of students is less so. Totally 47% of star students come from only five PhD programs, and 84.5% came from only 11 universities, including students from all programs at those schools. Only 9.3% of stars—21 total—did their PhD outside the United States.

Those top five PhD programmes were MIT (31 students out of 226), Harvard (25), Princeton (18), Yale (16), and Stanford (15). The highest non-US institution is London School of Economics, with eight students. Turning to gender, Bryan reports that:

...only 20.4% of star students are female, a percentage never exceeding 25% in any of the 6 years in our sample.

This is not great news, although Bryan notes first that this reflects the pipeline at top universities:

In the 2018 cohort, among the 11 programs that historically produce the most star students, there are 187 men and 50 women listed on those programs’ job market websites. That is, only 21.1% are female.

Bryan then notes in a footnote that:

Although 2019 data is preliminary at publication time, and hence not included in the overall analysis, there is a stark difference in that cohort: 20 of 43 stars, or 46.5%, are female.

So, perhaps there is some evidence of a balancing of genders in top programmes, and among 'young stars', although we would need more than just one year of data to support that conclusion. Moving on to the question of what 'young stars' study, Bryan finds that:

...the most striking fact is that job market stars almost universally studied economics or a technical field as their undergraduate degree... Over 75% of all job market stars have an undergraduate degree in economics, and nearly 95% have an undergraduate degree in either economics or a technical subject (mathematics, statistics, operations research, physics, or engineering).

That might be a striking fact, but not at all surprising. Interestingly though, there are different pathways to the PhD for American and non-American stars:

...34% complete their PhD within 6 years of their first tertiary degree. Americans are slightly more likely to do so, and men as well, though the differences are statistically insignificant... the reasons why Americans and non-Americans do not go straight from their undergraduate to PhD work are very different—Americans work, often as RAs, and non-Americans study at the master’s level—but the net effect is that both groups delay going “straight through” from undergraduate study at a similar rate.

In terms of field of study for their PhD job market paper, Bryan notes that:

...when we concatenate subfields into the broad categories of “applied micro,” “macro,” and “micro and econometric theory,” applied micro is the primary field of 45.6% of stars. There is no time trend...

There are large differences in field between male and female stars. Over 67% of female stars have applied micro as their primary field; only 40% of men have the same (Fisher exact test: p < .005). This difference is largely driven by the overrepresentation of women among stars in development and labor. On the other hand, in the broad definition of macroeconomics, in which we include growth, monetary, pure macroeconomics, finance, international and political economy, there were only seven female stars over 6 years, representing barely 10% of macro stars in that period.

This gender difference in areas of specialisation within economics is well known (for example, see here). However, I thought this bit was surprising: 

Publications prior to the job market are not a necessary condition for stars... 51% have a publication or an R&R [Revise and Resubmit]... That said, the flip side of this statistic is that half of job market stars have no publication or R&R at all, and 80% do not have a top five publication or R&R.

That really does mean that 'young stars' are being hired on the strength of their networks, and whatever they can convey through an interview process, rather than the signal provided by high-quality publications. And: 

Looking at heterogeneity in publishing, female stars are 32% less likely to have a publication or R&R than men (Fisher exact test: p < .05).

That result is interesting, and I'm unsure how to interpret it alongside the other gender differences. Could this simply reflect that female economists take longer to get published (as this paper suggests)? Or that, among potential young stars with no publications, universities are more likely to flyout a promising female applicant? Either of those could be the case, and it would be interesting to see if this result holds up in more recent cohorts, and dig into what might explain it.

Finally, Bryan looks at where they 'young stars' go, reporting that:

A total of 64.2% of all stars take a job at a U.S. economics department, and 47% of stars go to the top 15 departments alone. Another 21.7% accept jobs at a U.S. business school, almost always at a top 10 school.

That is not surprising, although this may be:

The only star student in our sample who went to the private sector went as a postdoc, and has since returned to academia.

I suspect that more recent cohorts have larger numbers attracted to private sector tech jobs, although it is also possible that 'young stars' still have a strong preference for academia, and it is the next tier down of PhD graduates who end up in the private sector. And Bryan cites some research to support that interpretation. Finally, Bryan turns his attention to postdocs, noting that:

Fourteen students, or just over 5%, became a star on the market following a postdoc... That is, not only is it not necessary to do a postdoc before being competitive for top permanent jobs in economics, it is in fact rare to do so.

I found that quite interesting, and a little surprising that more students didn't use a postdoc as a 'finishing school' or a way of getting a head-start on publications before the tenure clock starts. Again, perhaps that is more of a feature for the next tier of PhD graduates, and the 'young stars' are less affected?

Anyway, these 'young star' economists will almost all now be tenured professors, and no doubt form the core of the next generation of 'senior star' economists. It would be interesting to see some follow-up research on more recent cohorts, especially to investigate whether there have been any changes in the gender balance and gender differences within these top emerging economists.

*****

[*] I'd love to argue that the six-year gap (which nicely aligns with the tenure clock) between publication and my reading of this article was purposeful. But really, as regular readers of this blog might have noticed, I'm running through a bunch of papers I set aside in 2019 to read, and never got to (thanks in large part to pandemic-related teaching workload).