This week in research #137

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

• Avina et al. (open access) conduct a meta-analysis of studies into public attitudes toward immigrants in host societies, finding that while preferences are broadly similar across countries and demographic groups, economic considerations have become more influential over time, and evaluations of individual immigrants differ sharply depending on where people stand on the broader immigration debate
• Márquez and Scartascini (open access) evaluated a randomised controlled trial of a behavioural economics course for public officials in Latin America and the Caribbean, finding that the course improves applied reasoning and problem-solving
• De Boer et al. (open access) compare trust behaviour towards AI (ChatGPT 4o) and human receivers using a trust game in an experimental setting, finding no significant differences in trust behaviour either between individuals and groups or between AI and human receivers
• Voorintholt et al. (open access) find that reported climate change worries are on average significantly higher when people are asked whether they 'worry about climate change', compared with when they are asked if they agree that 'climate change 'worries me' (survey wording matters!)
• Morris (open access) challenges whether the concept of 'alcohol use disorder' is confused
• Anagol, Ferreira, and Rexer (with ungated earlier version here) estimate the economic value of zoning reform in São Paulo, finding that the reform increased the aggregate housing stock by 1.6 percent, reduced house prices by 0.4 percent, and produced welfare gains of 0.65 percent of city GDP
• Murphy (with ungated earlier version here) evaluates a randomised control trial in rural Kenya in which selected households received cognitive behavioural therapy and medication to reduce alcohol abuse, finding that the program decreased the likelihood of positive spot breathalyser tests among men by 14 percentage points, the likelihood of heavy drinking by 19 percentage points, and increased household real annual harvest values by 32 percent

Is it worth starting a Division III college football programme?

College football starts towards the end of August. The big and successful college football programmes attract millions of dollars and hundreds, if not thousands, of additional student enrolments, as well as keeping alumni engaged. It's not just college students who care about the result of a Michigan vs. Michigan State matchup!

But does it pay off for colleges further down the NCAA ladder to have football programmes? In the NCAA divisional system, Division I contains the powerhouse athletic programmes, Division II consists mainly of smaller public and private schools, and Division III is reserved for schools that don't offer athletic scholarships. Is it worthwhile for those Division III schools to have a football programme?

That is the question addressed in this 2025 article by Bryan McCannon (Illinois Wesleyan University), published in the journal Economics of Education Review (ungated earlier version here). McCannon starts by noting the growth in the number of schools playing Division III football, as shown in Figure 1 from the paper:

I was surprised that so many of these schools have added football programmes over the last thirty years, but note that the increase has levelled off since the mid-2010s. McCannon looks at data from 1984 to 2021, for all schools that had a Division III programme in 2022. He is interested in whether there are changes in student enrolment, gender balance, and endowment. He employs a two-way fixed effects (TWFE) approach, which essentially compares changes at schools before and after they introduced Division III football with changes at schools that did not introduce it. Conventional TWFE estimates can be biased when schools adopt football at different times and its effects vary across schools or over time, so McCannon applies a correction for that problem and also uses a synthetic difference-in-differences approach.

It turns out that both approaches produce similar results, and those results are not favourable, and McCannon reports that:

I fail to provide evidence that the adoption of Division III football has any effect on undergraduate enrollment. The change is statistically indistinguishable from zero. In addition, I provide evidence that the proportion of the student body that is female reduces. Taken together, this suggests that any increases in the male student population attributed to the introduction of football is offset by either reduced demand from female students or changes in the institution’s admissions practices.

And in terms of endowments:

Schools which added college football were overdrawing their endowments prior to adoption... I fail to find evidence that the addition of college football reverses these downward slides. This suggests that it did not sufficiently energize alumni giving or reduce financial pressure on the institutions.

So, adding a Division III football programme appears to offer little measurable reward for a college or university, at least in terms of the outcomes McCannon looked at. Why then would these schools start football programmes? One possibility is that they are caught in a competitive arms race, which is a type of prisoners' dilemma (which I covered in my ECONS101 class this week). A Division III college may believe that introducing football will attract students away from rival institutions, or prevent it from losing students when other Division III colleges introduce football. But if every Division III college introduces a football programme, none of them gains relative to the others, but they all incur the cost of running a football programme. The result is that many Division III colleges introduce football programmes, only to leave them all worse off (or at least no better off, based on McCannon's results).

Alternatively, McCannon suggests in his conclusion that it may be attractive for these schools to add a football programme in times of financial distress, in order to attempt to reverse the decline. However, these results suggest that such efforts would be largely unsuccessful in reversing declining enrolments or financial pressure.

These Division III schools are typically small, and education-focused. Perhaps they should stick to their strengths, and leave the expensive football programmes to the larger schools?

Can financial incentives help heavy drinkers stay sober?

Rational (and quasi-rational) decision-makers respond to incentives. If the costs of doing something go up, they tend to do less of it. If the costs go down, they tend to do more. And the reverse is true of benefits. Changing the costs and/or benefits of an activity therefore should be expected to change behaviour.

Does that logic extend as far as behaviours involving addiction and self-control problems? Consider alcohol consumption. Can heavy drinkers be incentivised to remain sober, at least temporarily, by increasing the costs of drinking, or increasing the benefits of not drinking? That is essentially the question addressed in this 2019 article by Frank Schilbach (MIT), published in the prestigious journal American Economic Review (open access).

Schilbach conducted a field experiment over three weeks with 229 cycle-rickshaw drivers in Chennai, India. In the experiment, the drivers were randomly split into three groups. The first group received a financial incentive to remain sober (the 'Incentive group'). The second group were paid an unconditional payment of similar magnitude (the 'Control group'). The third group got to choose between the sobriety incentives and the unconditional payment (the 'Choice group'). To receive their payment, the study participants had to report to the study office and submit to a breathalyser test. Schilbach was really interested in the effect of alcohol consumption on savings behaviour, so each research participant was offered the opportunity to save money at the study office each day. He was also interested in the effects on labour market participation and earnings, which were determined using surveys of the research participants.

The results reveal a number of important things about rational behaviour among heavy drinkers. First, the group that was given the choice between sobriety incentives and an unconditional payment demonstrated a strong demand for sobriety:

One-third to one-half of study participants chose sobriety incentives over unconditional payments, even when this choice entailed a potential or certain reduction in study payments...

One-third of the participants in the 'choice group' were willing to give up as much as 30 percent of their study earnings in order to be given the sobriety incentives. Schilbach isn't able to definitively determine why there was such high demand for sobriety, but he does note that:

First, study participants had significant experience with alcohol consumption and the potentially resulting self-control problems. The average study participant had been drinking alcohol for over a decade and many of them had been drinking (almost) daily...

Second, individuals perceived the costs associated with their drinking as significant. Many individuals expressed a strong desire to reduce their drinking in surveys and informal conversations. These men had spent substantial income shares on daily alcohol consumption for many years before participating in the study. Compared to these expenses, the forgone study payments due to the commitment choices may have appeared relatively small to individuals, especially if they implied a positive (perceived) chance of reducing subsequent alcohol consumption in the longer run.

So, the research participants may have perceived the experimental setting, and the money on offer, as a way to commit themselves to sobriety, at least for the period of the study. Did the incentives work, though? Schilbach finds that they did:

In the pre-incentive period, about one-half of the individuals in each of the three groups visited the study office sober. This fraction gradually declined in the Control Group to about 35 percent by the end of the study... In contrast, with the start of the incentivized period, sobriety in the Incentive and Choice Groups increased by about 10 to 15 percentage points. Subsequent sobriety at the study office also declined in these two groups, but the difference to the Control Group remained roughly constant.

Regression models confirm that the Incentive and Choice groups were approximately 13 percentage points more likely to visit the study office sober than the Control group, and the average breath alcohol content (BAC) was 2 to 3 percent lower for the Incentive and Choice groups than for the Control group (conditional on visiting the study office). Schilbach notes that the effect was largest on daytime drinking and not overall alcohol consumption, suggesting that many study participants simply shifted their drinking to later in the day (after visiting the study office).

Did sobriety affect labour market outcomes? Schilbach finds small and statistically insignificant effects on labour supply, hours worked, and earnings. As for savings, Schilbach found that the intervention increased savings, with the Incentive and Choice groups saving about 50 percent more than the Control group over the study period. Schilbach interprets this as showing that:

...increasing sobriety reduced self-control problems in savings decisions. An alternative interpretation could be that alcohol is a key temptation good for this population such that reducing alcohol consumption mitigates the need for commitment savings. However, given that the intervention only moderately reduced overall alcohol consumption and expenditures, this channel is unlikely.

My takeaway from this paper is that many heavy drinkers recognised their own self-control problems and were willing to give up some income for a commitment device that would help them remain sober. The commitment device increased the costs of drinking (or, equivalently, increased the benefits of not drinking). So, the drinkers who chose the sobriety incentives were acting rationally in response to a change in incentives. The research participants who shifted their drinking to later in the day were also acting quite rationally. By shifting their drinking to later in the day, they could receive the benefits of the sobriety incentive, while continuing to drink (albeit later in the day). In other words, the incentive changed behaviour, just not necessarily in the way it was intended to.

So, if you wanted to roll out a broader intervention based on changing incentives for heavy drinking, it might be better to measure sobriety at multiple times of the day. However, in this context even the later drinking may have reduced some of the potential alcohol-related harm, since there may have been fewer drunk-driving cycle-rickshaw drivers on the streets of Chennai (although, to be fair, the study doesn't actually show that there was less drink-driving).

It would be interesting to know how much of these study results are context-dependent, and whether a similar intervention would work elsewhere. If you tried to incentivise heavy drinkers in a high-income country to reduce their consumption, would they respond in a similar way? That question will have to wait for future research.

Could student-run social media groups reduce university student dropout?

Universities are quite focused on student retention, and as I noted in this 2018 post, if we can identify at-risk students, perhaps we can help to find ways to ensure they succeed. However, around that time I had a summer research scholarship student looking into the reasons that students drop out, and it turned out that each student dropped out for quite different, and difficult to predict, reasons. I call this the Anna Karenina principle of dropout: 'all students who persist are alike; each student who drops out does so in their own way'.

What if there were a simpler way of reducing student dropout, that did not require universities to identify at-risk students in advance, but instead reduced the risk of dropout from the outset? That would seem to be an attractive proposition.

So, I was interested to read this 2021 article by Lucio Masserini (University of Pisa) and Matilde Bini (European University of Rome), published in the journal Socio-Economic Planning Sciences (ungated version here), which evaluates the impact of student-created social media groups, such as Facebook pages, on student dropout. Masserini and Bini use survey data from 1879 first-year students from a major university in Central Italy.

Why would joining social media groups reduce dropout? Masserini and Bini suggest that these groups may help students form social connections and feel greater 'belonging' within the university community, while also providing a way for students to share information about courses, assessments, and study materials.

The key challenge in the analysis is that students are not randomly assigned to join social media groups - they choose whether or not to do so. And students who join these groups may differ from those who don't in ways that would bias a simple comparison of the students who joined social media groups and those who didn't. For example, more engaged students, who are less likely to drop out, might also be more inclined to join university-related social media groups run by other students. Masserini and Bini deal with this using propensity score matching - which involves identifying 'control' students who didn't join a social media group but who are most similar to each 'treated' student who did join a social media group. Then, comparing their matched control and treated students deals with any observable differences between the students who did, and did not, join social media groups.

Masserini and Bini then report a range of results of the estimated impact of social media groups on dropout, based on different assumptions used to do the matching, and:

...with the exception of k=1 nearest-neighbour, all the estimates indicated that students joining groups or Facebook pages had, on average, a lower probability to dropout, compared with those who were not part of such groups. The results also showed that the extent of the difference between the treated and control groups was not negligible, as it varied from 0.081 to 0.113, depending on the matching algorithm.

So, the results suggest that joining student-run social media groups or Facebook pages reduces the probability of a student dropping out by between 8.1 and 11.3 percentage points. Now, I should note that I don't in general find propensity score matching to be terribly convincing as a way of dealing with selection bias. 

Now, I should note that I do not find propensity-score matching entirely convincing as a way of dealing with selection bias. Although matching can make the treatment and control groups similar on observed characteristics, there is still something that is different about the treated and control students that leads the treated students to choose to join social media groups and the control students to choose not to join. That something is an omitted variable in the propensity score matching approach, and it is unclear how big the omitted variable bias will be. If, for example, joiners are more motivated or feel more connected to university life, then some of the apparent effect of joining the group on the probability of dropping out may instead reflect those underlying differences. Masserini and Bini's results are robust across several matching methods and sensitivity checks, which is reassuring, but robustness checks cannot establish that there isn't some omitted variable bias in the matching.

Having said that, if we take these results at face value, then there may be some merit in having student-run social media groups that university students can join. We must bear in mind that these results come from a survey in 2016, and they may not have aged well. But social media groups still exist, and students still participate in them. It could be worth exploring whether these effects still hold, given that increasing student retention remains a key focus for universities.

Having said that, student-run social media groups would probably be a relatively inexpensive way for universities to reduce dropout. Now, these results come from students surveyed in 2016, and both social-media use and the university environment have changed considerably since then. Nevertheless, the basic idea remains plausible. Universities could support the creation of student-run groups and randomly encourage or 'nudge' some students to join, then compare their subsequent retention with that of students who were not encouraged. That experimental approach would provide more contemporary and causal evidence of whether the groups reduce dropout, rather than merely attracting students who were already less likely to drop out.

Read more:

• Predicting student success, and failure
• Big data, student dropouts, and failing fast