Monday, 25 November 2024

Try as they might, the Australian Green party can't make university education free

The Australian Green party has proposed cancelling all student debt in Australia, as part of an aim for government to provide "free education for life". However, free education is not free. In an article in The Conversation earlier this month, Bruce Chapman (Australian National University) makes a case against the claim that cancelling student debt would make university education free. In Chapman's argument, someone has to pay the cost of providing education, and if it isn't students paying, then taxpayers will be the ones paying:

If there is no charge for a university degree, this means all taxpayers (including those without a university education) are fully subsidising graduates, who get lifetime advantages from their education.

In other words, calling for “free” universities is equivalent to supporting financial assistance going from the poor to the privileged.

Just about all political parties in Australia – and most governments around the world – agree this is not a not a wise idea.

Chapman is correct, of course. The cost doesn't go away just because students aren't paying some proportion of it. However, even if students are not paying any monetary cost, students are not receiving free education. That's because there are opportunity costs associated with education as well.

An opportunity cost is the cost of not pursuing the opportunity to do something else (the term dates back to the 19th Century Austrian economist Friedrich von Wieser). Studying (at all levels) takes time, and time is scarce. If a student devotes some of their scarce time to studying, they can't use that time for other activities that are valuable to them (and let's not get into the issues with students multitasking in class). A student might give up some leisure time, or work time, in order to complete their studies. The value of the time that they have given up is the opportunity cost of their education.

It turns out that the opportunity cost is the largest component of the cost of a university education. Think about it. A full-time student gives up at least three years of working in order to complete a university degree. If they are working while studying, chances are that they are working in a lower-paid job than they would have if they were instead working full time. The cost of their tuition fees pales in comparison to the cost of foregone income while they are studying.

None of this is to say that university education is not a good idea. For the majority of students, the benefits (higher lifetime income) far outweigh the costs (including opportunity costs) of education. There are also myriad social benefits from having a more educated population, which is why the government generally subsidises education for domestic students. That some of the benefits are private is one justification for students paying some of the costs of tertiary education (as Chapman notes in his article).

The Australian Green party can't legislate away the costs of education. Someone has to pay those costs, even if it isn't the students themselves. However, even if there were no monetary cost, the Australian Green party can't make education free for students, because even when education has no monetary cost, it will still have a large opportunity cost.

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Sunday, 24 November 2024

Book review: Understandable Economics

I used to review a lot of popular economics books, the kind that are written to explain key economic theories to general readers. Popular economics books vary widely in quality, but also in the ideological underpinning of the authors, and some authors are better than others at muting the underlying ideology. When they fail (or don't try) to avoid the ideology, to me it often gets in the way of a clear-headed explanation or omits key understandings of the real world. For example, that was the case for the market fundamentalist book Common Sense Economics (which I reviewed here). Since reading that book, I have mostly avoided popular economics theory books.

However, I couldn't avoid them forever, and I recently finished reading Howard Yaruss's Understandable Economics. Yaruss is absolutely not a market fundamentalist, and his sympathies to more left-wing ideals are clearly on display throughout the text. It can be a little preachy, but to me it didn't get in the way of understanding. Apparently, the original title of the book was to be 'Economics for Activists'. I'm glad Yaruss didn't choose that title, as I don't think it accurately conveys the content of the book.

The book is tightly focused on understanding the US economy, and much of the content relates to macroeconomics and public policy. Readers from other countries will therefore get less out of the book than US readers (although the general underlying principles are mostly the same for other countries). The examples are also very specific to the time that the book was published. This is a book for its time, and it will not remain current for too long.

Having said that, I really appreciated some of the commentary and some of the explanations. For example, Yaruss clearly explains why currency in a bank vault is not 'money' (as defined by economists):

Only currency in the hands of someone who can actually spend it, like a consumer, a business, the government, or a thief who stole currency from the bank and managed to get away, counts as money. So, although currency in bank vaults may look very much like money, it cannot be spent by anyone and, therefore, isn't money.

I also liked the example of an auction to explain money's role in creating inflation:

Imagine an auction where a fixed number of play "dollars" are divided among participants so that they can buy the goods on display. If the total number of play dollars were increased (remember, these play dollars have no value outside of this auction) without an increase in the number of goods for sale, people would be willing to bid and will, in fact, bid more and pay more for each good. Therefore, the bids, or prices, for each of these goods will go up - there will be inflation.

Back in the days when I hoped to one day write a book about the economics of the reality TV series Survivor, I had intended to use the 'Survivor Auction' (which has recently been revived for season 46 after many years absent) as an example. The explanation for why a Survivor contestant would pay $400 for a burger in the Survivor Auction would be almost identical to Yaruss's explanation above.

I also appreciated Yaruss's humour. Consider this quip about the averages:

If there is wide variation, an average can be very misleading. Think about the fact that the "average" adult human being has one breast and one testicle.

Overall, I enjoyed this book. However, I think that there are better books within the popular economics category that general readers would benefit from. However, in terms of clearly explaining the US economy and public policy, this book is great.

Saturday, 23 November 2024

Jared Cooney Horvath on how generative AI could harm learning

In a post last month about generative AI, I expressed some scepticism towards those among my colleagues who are trying to integrate generative AI into assessment (an "if you can't beat them, join them" solution to the impact of generative AI on assessment). I also expressed some hope that generative AI can be used in sensible ways to assist in student learning. Both of those views are contested. They certainly are not universally held among teachers.

In a recent article on the Harvard Business Publishing website, Jared Cooney Horvath outlines three critical problems generative AI poses for learning: (1) AI tools lack empathy, and an empathetic learner-teacher relationship is a strong contributor to learning; (2) while AI tools are good at retrieving information, in so doing they make having internal knowledge less important for students, and yet it is a broad internal knowledge that helps us to understand and solve problems; and (3) generative AI encourages multitasking, which is bad for learning.

On the latter point, Horvath concludes that:

It’s not that computers can’t be used for learning; it’s that they so often aren’t used for learning that whenever we attempt to shoehorn this function in, we place a very large (and unnecessary) obstacle between the learner and the desired outcome—one many struggle to overcome.

Finally, Horvath notes one positive for generative AI and learning:

There is one area of learning where generative AI may prove beneficial: cognitive offloading. This is a process whereby people employ an external tool to manage “grunt work” that would otherwise sap cognitive energy.

However, as noted above, when novices try to offload memorization and organization, learning is impaired, the emergence of higher-order thinking skills is stifled, and without deep-knowledge and skill, they’re unable to adequately vet outputs.

Experienced learners or experts can benefit from cognitive offloading. Imagine a mathematician using a calculator to avoid arithmetic, an event planner using a digital calendar to organize a busy conference schedule, or a lawyer using a digital index to alphabetize case files. In each of these scenarios, the individual has the requisite knowledge and skill to ensure the output meaningfully matches the desired outcome.

Horvath hasn't really changed my views on generative AI and learning. He does give some food for thought though, especially in relation to the value of created a finetuned AI designed to help with a particular course. If students use it as an interactive tutor, to help them develop their internal knowledge, then it is likely positive. However, if they use it purely to ask contingent questions, it may impair their ability to develop that internal knowledge and make them worse off. I wonder if there are particular learning tasks that can be used to encourage the former behaviour without too many students resorting to the latter? Clearly I have more thinking to do on this before I roll something like that out for my students.

{HT: Mary Low]

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Friday, 22 November 2024

This week in research #50

As I mentioned, last week I was at the North American Regional Science Congress in New Orleans. This isn't a science conference per se. Regional science is essentially a mix of economics, geography, sociology, and political science (and a bunch of other fields mixed in as well). As is often the case, there were more sessions that I wanted to attend than I could possibly attend, but here are some of the highlights I found from the conference:

  • My long-time friend and collaborator Matt Roskruge presented on the challenges of developing quantitative measures of Māori social capital (my takeaway was that it may be best to throw away the Western conceptions of social capital, and start over with a Te Ao Māori (Māori worldview) perspective, but apparently that has been done several times already)
  • Steven Deller presented on elder care and female labour force participation, showing that female labour force participation is lower in counties that have less access to elder care
  • Rosella Nicolini presented data that showed immigrants in rural areas are associated with increased GDP growth in Spain, while immigrants in urban areas are associated with decreased GDP growth
  • Rafael González-Val presented analysis of the impacts of the Spanish Civil War, showing a large (12 percent) reduction in industrial employment in provinces aligned with the Republicans, compared to those aligned with the rebels (although it must be noted that all of Spain's main industrial centres were aligned with the Republicans, so it may be no surprise that they declined relative to other regions)
  • Aurelie Lalanne presented some amazingly detailed data on urban growth in France, drawn from historical censuses that have been harmonised, and covering the period from 1800-2015

Aside from the conference, here's what caught my eye in research over the past week:

  • Davis, Ghent, and Gregory (with ungated earlier version here) use a simulation model (calibrated to real-world data) to show that the pandemic induced a large change to the relative productivity of working from home that substantially increased home prices and will permanently affect incomes, income inequality, and city structure
  • Galasso and Profeta find that reducing or eliminating time pressure decreases the math gender gap by up to 40 percent, and that time pressure contributes to the gap through increased anxiety rather than through students modifying their test-taking strategies
  • Mizzi (open access) looks at how economics teachers develop and utilise pedagogical content knowledge (the intersection of pedagogical knowledge and content knowledge) to assist their students’ engagement with disciplinary knowledge in economics (I feel like we should know more about this topic)
  • Liu et al. find that large increases in minimum wages have significant adverse effects on workplace safety, increasing work accidents by 4.6 percent, based on US state-level data
  • Matthes and Piazolo (open access) analyse data from over 40 seasons of professional road cycling races, and find that having a teammate in a group behind positively impacts win probability
  • Fernando and George find that home-team cricket umpires are less biased when working with a neutral colleague (one who is neither a national of the home nor the foreign team)
  • Chilton et al. find that there are large potential gains in better identifying exceptional students in law schools, if changes were made to certain personnel, course, and grading policies to improve the signalling quality of grades (and yet to me, it seems like most universities are on a policy trajectory to reduce the quality of grades as a signal)

Thursday, 21 November 2024

Will New Zealand finally deal with excess demand for access to tourist destinations?

New Zealand has long had a problem with excess demand for access to tourist destinations. I've written about this before, using the Great Walks as an example (see here, and here). Because the price for access to these tourist destinations is too low, the demand for access far exceeds the supply. The consequence is a much-degraded experience for everyone.

The solution, as I have noted before, is to let the price increase. Charge more for access to the Great Walks, and other tourist destinations. And, finally, that may be about to happen. As the New Zealand Herald reported last week:

A $20 access fee for Cathedral Cove, the Tongariro Alpine Crossing, Franz Josef Glacier, Milford Sound, and Aoraki Mount Cook National Park?

The Government is floating the idea of charging visitors – including New Zealanders – as part of two discussion documents, released today, which Conservation Minister Tama Potaka calls the biggest potential changes in conservation in more than three decades...

Charging $20 per New Zealander and $30 per non-New Zealander for accessing those places would bring in an estimated $71 million a year. Charging only international visitors would yield about half that.

Charging for access to these tourist destinations would go some way towards dealing with the excess demand. I'm totally ok with the differential price for New Zealanders and overseas travellers as well (which is something I have noted before, again in the context of the Great Walks). My main concern though is that the price of $20 for New Zealanders and $30 for non-New Zealanders may be too low. However, others have a different view:

But it has triggered a strong reaction from Forest and Bird, which said: “Connection to te Taiao (nature) is a fundamental part of being a New Zealander. All New Zealanders should be guaranteed the ability to connect with our natural environment regardless of how much money they earn.”

How easily can New Zealanders connect with their natural environment when it is thronged with tourists all visiting for free? Charging a price for access limits the numbers of tourists (including other New Zealanders), and makes it more likely, not less likely, that New Zealanders can get genuine access to these places. There is a meaningful difference between accessing a tourist location when there are hundreds of other tourists swarming all over it, and when few people are around and a peaceful engagement with nature is possible.

Quite aside from this being a way for the government to fund the Department of Conservation's operational costs, this proposal to charge a fee for access to these tourist locations is a sensible way to manage demand. Maybe we will finally have a working solution to the excess demand problem in these places.

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Wednesday, 20 November 2024

Natural capital and the problematic measurement of GDP

I've been thinking a bit about GDP this year, and in particular about the weirdness of its measurement. One of the key problems that has occupied me has been an asymmetry in how capital is accounted for within GDP. When new capital is created, the spending on the new capital adds to GDP. However, when capital is depleted, that depletion does not subtract from GDP. That is why, following a large natural disaster, GDP might actually increase due to rebuilding activity (and because any destruction of capital is ignored).

With that in mind, I was interested to run across this 2019 article by Colin Mayer (Oxford University), Published in the journal Oxford Review of Economic Policy (ungated earlier version here), deep down in my to-be-read pile of articles. Mayer was a member of the UK's Natural Capital Committee, which ran from 2012 to 2020, and this article considers how economists can, and should, approach accounting for natural capital. Mayer distinguishes between economists' traditional view of natural capital, and an approach more similar to how an accountant would approach natural capital:

To the economist, natural capital, like any other asset, is the plaything of humans, there to be treated as mankind sees fit. To the accountant, the firm is an entity of which the managers are the stewards. They are there to preserve the firm and to promote its flourishing. So, too, we should consider whether it is our right to employ nature in the way in which we see fit, or our obligation to act as its steward or trustee.

Mayer's solution is that we should revise how natural capital is treated, and should:

...incorporate a maintenance charge in the balance sheets and profit and loss statements of nations, municipalities, corporations, and landowners to reflect the liability associated with maintaining or restoring these assets.

I think that Mayer could have been much clearer in the explanation here. When natural capital is depleted, through pollution, or extractive industries, or carbon emissions, my view is that the cost of that depletion should directly reduce GDP (which is the equivalent of the 'profit and loss statements' that Mayer refers to). Instead, Mayer seems to be suggesting that this is a liability. Both of those approaches may be correct, given the simple accounting identity (Assets + Expenses = Liabilities + Proprietorship + Revenues). A liability on the right-hand side of that identity equation can arise because of an expense on the left-hand side. However, the labelling as a liability implies an obligation to repay, which may not be the case for all types of natural capital (how would one pay off the liability of mining extraction, for instance?).

Anyway, there is clearly more thinking to be done here. I don't think that economists' approach to natural capital is correct. I think that the approach to other forms of capital (physical, social, and human capital) is similarly flawed. For example, decreasing social capital over time (as accounted by Robert Putnam's 2000 book Bowling Alone (which I reviewed here) should also decrease GDP in my view. By correctly accounting for changes in capital (both upwards and downwards) GDP would better capture changes in societal-level wellbeing.

Saturday, 16 November 2024

This week in research #49

Another quiet blogging week for me, due to travel and the North American Regional Science conference in New Orleans (more on that in next week's post). However, I have been trying to keep up with research, and here's what caught my eye over the past week:

  • Mello (open access) finds that winning the FIFA World Cup increases a country's year-over-year GDP growth by at least 0.48 percentage points in the two subsequent quarters
  • Boyd et al. (open access) describe how an agent-based model could be used to evaluate the impact of minimum unit pricing of alcohol in Scotland (but they don't actually show the results of any such modelling, which is a bit disappointing)
  • Singleton et al. (open access) find that a university located in a town that loses an English Premier League team (due to relegation to the Championship) suffers a reduction in undergraduate year-to-year admissions growth by 4–8 percent
  • Ozkes et al. find that human players of the ultimatum game do not differentiate between human and algorithmic opponents, or between different types of algorithms, but they are more willing to forgo higher payoffs when the algorithm’s earnings benefit a human (this has interesting implications for how humans interact with AI)
  • Gjerdseth (with ungated version here) finds that the destruction of ivory does not reduce elephant poaching rates, using CITES data from 2003 to 2019 (for more on this topic, see this post and the links at the end of it)
  • Hagen-Zanker et al. (open access) use data from a large-scale survey conducted in 25 communities in ten countries across Asia, Africa and the Middle East, and show that there is little consistency in the individual-level and community-level factors that are associated with migration intentions, although women are less likely to have migration intentions, while those with access to transnational social networks are more likely to have migration intentions

Saturday, 9 November 2024

This week in research #48

It's been a quiet week in terms of my keeping up with research, as I've been travelling. However, here's what caught my eye in research over the past week:

  • Rasmussena, Borb, and Petersen merge Twitter data with Danish administrative data, and find that individuals with more aggressive dispositions (as proxied by having many more criminal verdicts) are more hostile in social media conversations, and that people from more resourceful childhood environments (those with better grades in primary school and higher parental socioeconomic status) are more hostile on average, as such people are more politically engaged

In other news, as I said above my wife and I have been travelling this week. We started in Texas, then Oklahoma, and now Arkansas (with Alabama, Mississippi, and Louisiana to come). While in Texas, I had the great pleasure of meeting Cyril Morong, The Dangerous Economist:

Next week may also be fairly quiet on the blog, as I'll be at the North American Regional Science Congress in New Orleans. And, New Orleans, of course.

Sunday, 3 November 2024

Book review: How Big Things Get Done

There are certain books that shouldn't need to be written. Inevitably, those are the books that, in reality, most need to be written. That is certainly the case for How Big Things Get Done, by Bent Flyvbjerg and Dan Gardner. This is a book about big projects, and importantly, how those projects succeed or, as is often the case, how they fail. As the authors note in the preface, it is a book that aims to answer a number of important questions:

Why is the track record of big projects so bad? Even more important, what about the rare, tantalizing exceptions? Why do they succeed where so many others fail?

The book draws on decades of Flyvbjerg's academic research on big projects, as well as his experience both consulting on, and being directly involved in, big projects. Through this work, Flyvbjerg has developed a massive database of projects, their cost and benefit estimates at the time the project began, and the cost over-runs and benefit shortfalls that so often resulted. The numbers do not make for easy reading, and the examples that Flyvbjerg uses range from transport infrastructure to It projects to nuclear power stations to the Olympic Games. On the latter, the book is a useful complement to Andrew Zimbalist's book Circus Maximus (which I reviewed here).

Flyvbjerg and Gardner spend a lot of time discussing failed projects, but devote substantial space to discussing successes, such as Terminal 5 at Heathrow. Many of us will remember the opening of Heathrow for the terrible problems associated with baggage handling in the first few days of opening, but the project itself delivered on time and on budget. Once you read this book, you'll realise just how extraordinary that accomplishment is.

Flyvbjerg and Gardner use the comparison between successful projects and failures to draw a number of lessons. Most of the lessons seem obvious, but clearly those lessons have not been learned well enough in the 'big projects' space, because they are so often not heeded. The biggest lesson of all is to 'think slow, act fast'. Thinking slow means spending substantial time planning before the project begins, ensuring that the risks are well known and have been planned for, before the first spade turns the first sod. Acting fast means completing the project as quickly as possible, to avoid the 'unknown unknowns' from impacting the project - the more delays, the more time there is for something unforeseen to happen.

The 'think slow, act fast' approach seems inconsistent with Silicon Valley's approach to development (as ably described in Jonathan Taplin's 2017 book Move Fast and Break Things, which I reviewed here). Flyvbjerg and Gardner anticipate that counterexample, and note that the two are not inconsistent at all, because:

Planning is doing: Try something, see if it works, and try something else in light of what you've learned. Planning is iteration and learning before you deliver at full scale, with careful, demanding, extensive testing producing a plan that increases the odds of the delivery going smoothly and swiftly.

That is, more or less, what the big tech firms do. Flyvbjerg and Gardner note that iteration is key to those firms' development process, and is generally successful (or where it isn't, the firm can rapidly iterate to something new). In contrast, most big projects are delivered using a 'think fast, act slow' approach that is doomed to failure. 

I really enjoyed this book, even though it does seem quite depressing at times, just how badly big projects are at delivering on their promises (both in terms of costs, and in terms of benefits). The book is not only well researched, but draws on many interviews that Flyvbjerg has completed with people in the industry. The writing did make me wonder what Gardner's contribution was - the whole book is written as if by Flyvbjerg alone (with lots of "I" and "my"), which seems an odd stylistic choice for a co-authored book. Nevertheless it is an enjoyable read, and definitely recommended.

Saturday, 2 November 2024

What does the Cantril Ladder really measure?

Imagine a ladder with steps numbered from 0 at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time?

Now, consider the question you probably just answered. What factors played into your answer? What sorts of things contribute to the best possible life for you, compared with the worst possible life for you? If we used your answer to that question as a measure of life satisfaction, what is it really measuring?

That's not an unimportant question. The first paragraph of this post is a commonly used way of measuring life satisfaction, known as the Cantril ladder (see here). It is used in the Gallup World Poll, and is recommended by the OECD as a way of measuring subjective wellbeing. When researchers (or governments, or others) measure life satisfaction or happiness, it is often the Cantril ladder that is being used.

The question of what the Cantril ladder measures was explored in this recent article by August Nilsson (Lund University), Johannes Eichstaedt (Stanford University), Tim Lomas (Harvard University), Andrew Schwartz (Stony Brook University), and Oscar Kjell (Lund University), published in the journal Scientific Reports (open access, with non-technical summary on The Conversation). Nilsson et al. looked at the framing of the Cantril ladder, and investigated how nearly 1600 people responded to different framings of the question, and the words that they used to describe the top and the bottom of the scale in those different framings, and where they would 'prefer to be' on the scale. The first framing was the traditional Cantril ladder. The second framing essentially replaced the ladder metaphor with the word "scale" (but left the rest intact). The third framing removed references to the "bottom" and "top" (as well as the ladder metaphor). The fourth framing did all of that plus changed "best possible life" to "happiest possible life" (and "worst possible life" to "unhappiest possible life"). And the fifth and final framing instead replaced "best possible life" to "most harmonious life" (and "worst possible life" to "least harmonious life").

Nilsson et al. found that:

The ladder and bottom-to-top scale anchor descriptions influenced respondents to use significantly more words from the LIWC dictionaries Power and Money when interpreting the Cantril Ladder... compared to when these anchors were removed. Of all the words respondents used to describe the top of the Cantril Ladder, 17.3% fell into the Power and Money dictionaries. This language was reduced by more than a third when the ladder was removed in the no-ladder condition (absolute difference of 6.0%, d = 0.35, p < 0.001), and more than halved when the bottom-to-top scale descriptions were removed too (absolute difference of 10.3%, d = 0.64, p < 0.001). Further, for the Cantril Ladder, words in the Power and Money dictionaries occurred 3.3 times as frequently compared to the alternative Harmony anchor condition (absolute difference of 12%, d = 0.77, p < 0.001).

They interpret those results as meaning that:

...the original Cantril Ladder influenced respondents to focus more on money in terms of wealth (whereas when the ladder framing was excluded, they focused more on financial security) than the other conditions.

Were you thinking about the financial aspects of life when you answered the question above? The results seem to suggest that is more common than thinking about social relationships or the various other contributors to our subjective wellbeing. Nilsson et al. don't explore the use of words other than in the 'Power' and 'Money' domains, but it would have been interesting to see some others to compare with.

It's not surprising that financial security, income, or wealth are important contributors to subjective wellbeing or life satisfaction. We should expect people to be better able to satisfy their needs when they have greater financial resources available to them. However, the results on research participants' preferred level on the ladder are genuinely surprising, because:

...over 50% did not prefer the highest level (of 10) in any of the study conditions, and less than a third preferred the top of the Cantril Ladder, which had a significantly lower average preferred level than all the other study conditions.

In other words, even though the top of the Cantril ladder is framed as the 'best possible life', around two-thirds of research participants said that they would prefer not to be at the top of the ladder. This proportion was lower (but still not zero) for other framings, as shown in Figure 4 from the article (where the dark blue part of the bar shows the proportion of research participants who responded that 10 was their preference):

What was your preferred level on the ladder? Did you want to have the best possible life (that is, 10 on the scale)? Or would you prefer to be somewhere just below the best possible life? What do you think about in answering the question on your preferred level? Maybe research participants want 'room to grow' and become even happier or more satisfied with their lives? I have no idea. Nilsson et al. have given us something to really think about here, but unfortunately the article doesn't go far enough in exploring why people don't prefer the top of the ladder. There is definitely scope for further follow-up research on this point.

In addition to being surprising, that last result may call into question how the Cantril ladder is interpreted (on top of the arguments about the validity of happiness data generally - see here, and here, and here). If the top of the scale is not the top of the scale, or if it is different for different research participants, then how do we interpret an average across all people responding to the question? That should make researchers worry, and makes follow-up research even more important.

[HT: New Zealand Herald, back in April]

Read more:

Friday, 1 November 2024

This week in research #47

Here's what caught my eye in research over the past week:

  • Geerling, Mateer, and Wooten (open access working paper) identify a group of “rising stars” in the economics teaching field (where I'm ranked #27 in the world according to their ranking, and #5 outside of the US)
  • Li and Xia find that students just above a letter-grade cutoff in an introductory course are 3.6% more likely to major in the same field as that course, using data from the National University of Singapore
  • Divle, Ertac and Gumren find in an online experiment that although working in a team is more profitable and participants also expect this, a large proportion shy away from teamwork, and that research participants primed with COVID-19 are less likely to self-select into teamwork
  • Dickinson and Waddell find, using data from GitHub, that the transition to Daylight Saving Time reduces worker activity, but that the effects are relatively short-lived, although when using more detailed hourly data losses appear in the early working hours of work days into a second week following the initiation of Daylight Saving Time
  • Naidenova et al. look at twelve years of data from professional Counter-Strike: Global Offensive games and find that there is a substantial decrease in the performance of esports players during overtime, which they attribute to 'choking under pressure', although the impact is less in online competitions compared to live events
  • Martínez-Alfaro, Silverio-Murillo, and Balmori-de-la-Miyar (open access) find in an audit study that job applications from transgender candidates received 36% fewer positive responses than those from cisgender candidates in Mexico