Thursday, 6 March 2025

University students should probably take notes by hand, not on laptops

Moving around the lecture theatre while my students are working on some problem or exercise, it is surprising to see how many students persist with trying to use a laptop. I say surprising because most of the exercises I do with my class involve drawing diagrams, and drawing diagrams on a laptop is not easy. It would be much easier to draw the diagrams on paper, and that is what most students do.

The choice of note-taking medium is not benign. There have been a number of studies that have shown that hand-written notes are better for student learning than notes taken on devices such as laptops or tablets. In fact, I've blogged on this topic before (see here, as well as this post on laptop use more generally).

A recent meta-analysis makes the case even more strongly, that hand-written notes are better than notes taken on devices. That meta-analysis is reported in this 2024 article by Abraham Flanigan (Georgia Southern University) and co-authors, published in the journal Educational Psychology Review (open access). They combined the results of 24 studies (published across 21 articles), limiting their scope to experimental or quasi-experimental studies that involved university students (therefore excluding studies on high school students, who may approach their studies in different ways). They focus on two outcomes: (1) student achievement; and (2) the volume of notes taken.

In relation to student achievement, Flanigan et al. find:

...a mean effect size of 0.248, p < .001[95%CI ∶ 0.181, 0.315], which was statistically significant. This finding indicates that the overall sample of studies found that handwritten note-taking had a positive effect on achievement, meaning that handwriting notes produced higher achievement than typing notes.

Students using hand-written notes perform nearly a quarter of a standard deviation better than students using laptops or tablets for note-taking. That's not a huge difference, but it could make a real difference for some students. In my ECONS101 class, a quarter standard deviation difference is about four percentage points in overall grade, enough to drop a student by a grade point (from a B+ to a B, for example).

Flanigan et al. them perform some further analysis, which shows that the positive effect of hand-written notes (compared with notes taken on a device) is statistically similar for immediate and delayed assessments, and for different measures of student achievement. When students are allowed to review their notes, the effect is larger than when they are not allowed to review them. 

In terms of the volume of notes taken, Flanigan et al. find that:

...the overall mean effect size was statistically significant (0.919, p < 0.001[95%CI ∶ 0.679, 1.160]). These results indicate that typed notes contain more words and ideas than handwritten notes.

Taking those two results together, when students take notes on a device, they write a greater quantity of notes, but those notes are less effective in terms of the students' learning. Flanigan et al. offer some explanation for these results, being that:

...handwriting notes produce deeper processing than typing notes. Longhand notes tend to capture lecture ideas in a paraphrased and personalized style meaningful to the note-taker, whereas typed notes tend to capture lecture ideas in a verbatim, almost thoughtless way... Although typing leads to a greater quantity of recorded ideas than writing does, the shallow, verbatim nature of typing notes seems to hinder their external storage value, thereby rendering typed notes less useful during review than handwritten notes...

...handwritten notes contain more lecture images than typed notes. In studies measuring the number of images recorded in notes, college students typing notes recorded zero lecture images, whereas longhand notetakers recorded multiple images... According to dual-coding theory... learning occurs best when information is coded both verbally and visually.

That latter explanation is likely to be particularly important in economics. If a student doesn't take good notes of the diagrams, then they are likely to struggle to learn in class, and struggle to review later, leading overall to worse achievement in their assessments. For this reason, students should really be hand-writing their notes.

However, there is an exception, and it was good to see Flanigan et al. make this point:

Handwriting or typing lecture notes might not be an option for some students, whether their disabilities are physical or cognitive in nature. Other students might require note-taking assistance, such as having another student record notes for them or instructors providing notes for them.

Despite the number of students accessing additional support for disabilities appears to have grown over time, I have noted the number of 'note takers' (employed to take notes for other students) has declined over time. That may be because devices are seen as alleviating the need for human note takers. However, Flanigan et al.'s results suggest that relying on devices rather than human note takers may be making students with a disability worse off.

Finally, there are two points that Flanigan et al. don't make in their article, which are useful to consider. First, not all laptops and tablets are created equal. Touch-screen devices that allow students to hand-write notes, and then convert those notes to text, are probably more like hand-written notes than notes taken on a device. However, that may depend on how the device is used, because they do of course allow students to type as well. Some further study on this seems warranted. Second, I wonder how note-taking by AI would fare in comparison with notes taken by a student? I suspect that the AI would err on the side of verbatim notes, similar to typed notes by a student, rather than paraphrased notes that a student who is hand-writing their notes would make. On the other hand, the AI could be explicitly instructed to paraphrase. Going back to the previous point about students with a disability, an appropriately instructed AI tool could make a substantial positive impact. That is definitely something worth exploring further.

How students take notes has an impact on their learning, and on their achievement in assessments. For now it seems, hand-written notes remain best, at least until we can let an AI take over the note-taking.

[HT: This article in The Conversation last month]

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Wednesday, 5 March 2025

Minimum wages and alcohol consumption

There are several reasons to believe that higher minimum wages will affect alcohol consumption. First, higher incomes for those on the minimum wage gives them greater purchasing power. If alcohol is a normal good (which it is), then as their incomes increase people will consume more alcohol. On the other hand, higher minimum wages may lead to disemployment, especially among young people and those in the food and beverage industries. In that case, those workers without jobs have lower incomes and would consume less alcohol. However, losing a job (or not having a job) can be a stressful experience, and increase the incentives to drink alcohol as a coping strategy. And having a job that pays more due to a higher minimum wage may reduce financial stress and reduce the incentives to drink. Overall, there is a lot going on, and it isn't clear at all whether, overall, a higher minimum wage should lead to more alcohol consumption, or less alcohol consumption.

That's where this new article by Yihong Bai (Western University in Ontario) and Michael Veall (McMaster University), published in the journal Economics and Human Biology (open access), comes in. Bai and Veall use longitudinal data from the Canadian National Population Health Survey (NPHS) from 1994/95 to 2010/11, and look at how alcohol consumption is related to the province-level minimum wage (adjusted for inflation). Their full sample includes over 18,000 observations for a little over 4000 individuals in Canada. They measure alcohol consumption in six different ways: (1) whether each person is a drinker or not; (2) whether they binge drink at least once per month on average; (3) whether they are a 'heavy drinker' (defined by binge drinking at least once per week on average, or having average daily alcohol consumption [ADAC] of two drinks for men, or one drink for women; (4) average number of drinks over the last month; (5) number of binge drinking events over the last month; and (6) ADAC.

Bai and Veall apply a two-way fixed effects approach to identify the effects of the minimum wage on alcohol consumption, and find that:

...almost all the estimated coefficients are very small with reasonably tight confidence intervals that cover zero.

In other words, there is very little evidence that higher minimum wages increase alcohol consumption. However, that is based on the whole population, and minimum wages are more likely to affect low-income workers. Rather than looking at low-income workers directly, Bai and Veall look at low-education workers (being those with high school education or less), who are also more likely to be affected by minimum wage changes. For that group, they also find that almost all of the coefficients are not statistically significant. Another group that tends to be more affected by minimum wage changes is young people, and Bai and Veall report that:

We also estimate using samples for a sample of ages 21–25 and ages 15–20 and find no evidence of minimum wages increasing drinking. However, our confidence intervals are wide and this finding must be treated with caution.

One of the key issues with this paper is that they perform a large number of regressions (with six dependent variables), but don't adjust for multiple comparisons. This is important because the more comparisons they make, the more likely it is that some will turn out to be statistically significant just by chance. That's why I discount their finding that the ADAC decreases when the minimum wage increases. I doubt that it would be robust to an adjustment for multiple comparisons, and the ADAC results are inconsistent with the effects in the other models.

On the other hand, the two-way fixed effects approach is problematic and has attracted a lot of criticism recently (which is nicely outlined in two posts on the Development Impact blog, here and here, as well as this post). The short version is that the two-way fixed effects approach is likely to lead to biased estimates of the treatment effect - in this case, it would lead to a biased estimate of the effect of minimum wages on alcohol consumption. It isn't clear what direction the bias would lead.

So, by itself this paper doesn't give an answer to the question of whether minimum wages affect alcohol consumption or not, and if they do affect alcohol consumption whether minimum wages lead to an increase, or a decrease, in alcohol consumption. This research question is far from settled and is an area where future research would be useful.

Tuesday, 4 March 2025

Local minimum wages and low-quality housing rents in Japan

In this 2023 post, I discussed the impact of higher minimum wages on homelessness. Part of the story related to housing rents:

There are a couple of reasons to expect that higher minimum wages might increase homelessness. If minimum wages decrease employment (a result that is contested, but I believe it is likely given the galaxy of literature we have to date; again, see the links at the end of this post), then higher minimum wages may directly increase the risk of people becoming homeless. That's because when low-income people workers lose their jobs, they may no longer be able to afford to pay rent, and may lose their homes. Second, if minimum wages increase incomes for those that are not made unemployed, they may increase the demand for housing, pushing up rents. This may indirectly increase the risk of people becoming homeless, who can no longer afford the higher market rent.

The research that I referred to in that post found that higher minimum wages increased homelessness, and that they also increased housing rents, consistent with the mechanism outlined above. However, we shouldn't believe just a single paper's research findings. This 2021 article by Atsushi Yamagishi (Princeton University), published in the journal Regional Science and Urban Economics (ungated earlier version here), provides some additional evidence, this time from Japan.

Japan provides an interesting case study for examining the effects of the minimum wage on housing, because:

Japan has forty-seven prefectures and each has a different minimum wage rate. There is no difference in the minimum wage rate within a prefecture...

And on top of that, each prefecture has little control over its local minimum wage. Yamagishi notes that:

...the minimum wage setting in Japan is highly centralized and unresponsive to trends in local housing markets due to institutional features. Japanese prefectural minimum wages are determined by the following process. First, the central government classifies prefectures into four categories, and it assigns the targeted amount of minimum wage increase to each category. The categorization is reviewed only once every five years and changes in the classification are rare.

Yamagishi uses data from 2007 to 2013, and exploits an interesting natural experiment, where:

From 2007 to 2012, a new consideration took the primary role in setting minimum wages due to the national policy change... after the revision of the Minimum Wage Law in 2007, the primary consideration in setting the minimum wage rate became closing the gap between the quality of life of minimum wage workers and people relying on Public Assistance (seikatsu-hogo, PA henceforth)...

Since the gap was generally larger in urban areas, the policy resulted in a plausibly exogenous minimum wage increase in urban prefectures...

So, not only is there variation in minimum wages across prefectures, and that variation is not related to local housing markets, there is a change in the variation driven by the policy change. Yamagishi uses data on advertised apartment [*] rents from At Home, "one of the most popular online real estate search engines in Japan". Using both an event study research design and a difference-in-differences design, Yamagishi found that:

...low-quality apartments experience around a 2.5-4.5% rent increase in response to a 10% minimum wage increase.

When looking at differences by apartment quality (proxied by the age of the apartment, with 'old' apartments being over 25 years old and 'very old' apartments being over 35 years old), Yamagishi found that:

An old apartment experiences a rent increase of around 3.3% when the minimum wage increases by 10%, which is statistically significant at the 1% level. A very old apartment experiences an increase of around 4%, which is also significant at 1% level. Overall, the result reveals the larger impact on the rents of lower-quality apartments...

Of course, the key point here is that workers on the minimum wage are more likely to live in low-quality apartments than in higher-quality apartments. So, the takeaway from this paper is that higher minimum wages may make some workers better off in terms of higher wages (while also considering the disemployment effects of the higher minimum wage), but that the gains of those workers would be offset somewhat by higher rents. Yamagishi estimates that landlords gain between 7.5-13.5 percent of the increased minimum wage, but the assumptions necessary to arrive at that estimate are a little difficult to justify.

Nevertheless, the overall point stands. The minimum wage workers lose some of their higher minimum wage to higher rents.

[HT: Marginal Revolution, back in 2023]

*****

[*] As an interesting aside, Yamagishi notes that in Japan, 'apartments' are generally low quality. A high quality apartment is referred to as a 'mansion' (see here).

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Monday, 3 March 2025

15 years of US research on the minimum wage elasticity of employment

It's time to pick up my recent thread of posts on the minimum wage (most recently in this post). I want to return for a moment to more conventional research on the minimum wage, specifically looking at the effects of higher minimum wages on employment. The majority of minimum wage research has focused on estimating some variation on the minimum wage elasticity of employment - that is, the responsiveness of employment to a change in the minimum wage.

This 2019 article by Paul Wolfson (Dartmouth College) and Dale Belman (Michigan State University), published in the journal Labour (ungated version here), presents a meta-analysis of the findings of 15 years of such research in the US context. As they explain:

The beginning of the New Minimum Wage Research can be dated to a 1991 conference at Cornell University, and the exchange between Neumark and Wascher (2000) and Card and Krueger (2000) in the December 2000 issue of the American Economic Review marks the end of its first period. Our study includes analyses of US data that have appeared after December 2000. We identified 60 analyses, working papers, and published articles that both satisfied these criteria and included at least one estimate of the effect of the minimum wage on employment. In 37 of these 60, either the analysis explicitly reported one or more elasticities and their standard errors or it was possible to calculate them...

As a reminder, a meta-analysis involves combining the results from many other studies in order to estimate an overall effect. Wolfson and Belman's meta-analysis overall includes 739 estimates of the minimum wage elasticity of employment, drawn from those 37 studies. They also run analyses based on the 'best' estimate from each study, as well as the average estimate from each study. All of the analyses result in similar findings. 

The starting point for Wolfson and Belman is an estimate from a survey article by Brown et al. published in 1982, which estimated that the elasticity was between -0.1 and -0.3. That would mean that a 10 percent increase in the minimum wage would result in a decrease in employment of between 1 percent and 3 percent. Brown et al.'s estimates were not based on a meta-analysis, but instead based on a narrative review of the literature up to 1982. Obviously, there literature has moved on a lot since then, and new methods and better data have been applied to the question of the employment impacts of the minimum wage.

So, what do Wolfson and Belman find? They report that:

...the range of the employment elasticity has shifted toward zero since Brown et al. (1982), from [-0.3, -0.1] to [-0.13, -0.07]... Teenagers, and eating and drinking establishments together account for more than half of the estimates in our sample. Estimating separate models for teens and for eating and drinking places has little effect on our estimated range, moving it from [-0.13, -0.10] to [-0.11, -0.07]... The minimum wage then has negative employment effects, but estimates of them have become smaller and are largely localized to teenagers, who comprise a declining share of the labor force.

The estimated elasticity range overall of -0.07 to -0.13 implies that a 10 percent increase in the minimum wage would result in a decrease in employment of between 0.7 and 1.3 percent. That effect is small, but it is not zero either. Overall, estimates from the literature do tend to show that higher minimum wages decrease employment (as also noted in some of the more recent findings in my earlier posts - see the list below).

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