More on the value of words in wine descriptions

I posted last month about consumers' willingness to pay for wine bullshit. That was based on research by Kevin Capehart, which was published in the Journal of Wine Economics. Now, Capehart has another new article published in the same journal on a related topic (sorry, I don't see an ungated version online). In this new article, Capehart follows up on earlier research by Coco Krumme (described here). Essentially, Capehart uses a dataset of 120,000 wine descriptions, and classifies them into 'high price' (over US$50) or 'low price' (under US$15). He then trains a Naive Bayesian Classifier to predict which wines belong to the low-price category and which belong to the high-price category, based on the words in their descriptions.

Capehart is mostly able to reproduce very similar results to the earlier Krumme work, but perhaps more interestingly:

...I find for the dataset studied here that there do seem to be two mostly distinct vocabularies for high- and low-priced wines. Out of the roughly 20,000 unique words used to describe the over-$50 and/or under-$15 wines, only 42% of those words overlap by being used to describe wines in both price categories. The remaining 58% of words are non-overlapping.

In other words, the descriptions of high-priced wines use very different words than the descriptions of low-priced wines. You might argue that is because high-priced wines have different characteristics than low-priced wines, their descriptions should include different vocabularies. However, the key question that isn't answered (and which Capehart alludes to in his conclusion) is, does the vocabulary relate to the quality of the wine, is it simply a signal of the price? In other words, do those who are writing the descriptions choose their vocabulary based on the price of the wine, or based on the quality of the wine? We'd need more research in order to answer that question, and more like Capehart's earlier work.

Read more:

• The willingness to pay for wine bullshit

Unexpected alcohol prohibition and mortality in South Africa

The District Health Boards in New Zealand are busy cancelling elective surgeries and non-urgent care in order to deal with the ongoing surge in coronavirus cases. In 2020 and 2021, South Africa took things much further, on a number of occasions banning the sale of alcohol in order to reduce alcohol-related hospital presentations and injuries (see here). This new working paper by Kai Barron (Wissenschaftszentrum Berlin für Sozialforschung) and co-authors looks at the impact of the second ban (from 13 July to 18 August 2020) on mortality and other related outcomes. This particular ban makes a good natural experiment because:

...it was unexpected. The alcohol ban was announced in the evening of Sunday, July 12, 2020, and came into immediate effect from Monday morning on July 13, 2020. Second, it was implemented in the middle of the so-called “Level 3” COVID-19 policy response period during which time other policies and regulations were largely held constant.

In other words, no one could have anticipated the ban and adjusted their behaviour beforehand, so it provides a clean 'break' in the time series data, and no other policy could make it difficult to isolate the effect of the alcohol ban. [*]

Barron et al. focus on the effect on mortality due to unnatural causes (which includes road traffic injuries, interpersonal violence, and suicides) in the first instance. They use data on daily mortality from 2017 to 2020, and employ a difference-in-differences approach. I haven't seen it employed in quite this way before. They essentially treat the alcohol ban dates in each year from 2017 to 2019 as a control, and the same dates in 2020 as the treatment period. So, their difference-in-differences is the difference between the alcohol ban dates and the rest of the year in 2020 compared with the difference between the alcohol ban dates and the rest of the year in 2017 to 2019. In one of the footnotes, they argue that this approach:

...can be justified when there is strong year-on-year temporal regularity in the outcome of interest.

There does seem to be a persistent trend across the years 2017 to 2019, and Barron et al. control for day-of-the-week effects, week-of-the-month effects, and month fixed effects, which should capture most of the regularities over time. Their key results are best summarised in Figure 2 from the paper:

Notice that there's a drop in mortality from unnatural causes in 2020/21 every time there was an alcohol ban in 2020. Barron et al. are focused on the middle period, where the ban was unanticipated, and not correlated with other policy changes. The effect looks smaller there, but in their preferred econometric model they find that:

...the alcohol ban reduced unnatural mortality by 21.99 deaths per day... 

That doesn't sound like a lot, but it represents about a 14 percent reduction in deaths from unnatural causes. Barron et al. then go on to show that:

For men, the pattern is similar to that observed in the population as a whole, with the estimates indicating that the alcohol ban reduced mortality by approximately 21 deaths per day... For women, we find no significant impact of the alcohol ban on mortality.

That shouldn't be too surprising, given that men are at greater risk of deaths from unnatural causes. And then when they look at young adults (aged 15 to 34 years) they find that:

 ...the alcohol ban reduced mortality amongst men in this age-group by approximately 12 deaths per day... and may have had a small impact on the mortality of younger women.

So, overall, the alcohol ban reduced mortality from unnatural causes, almost entirely among men, and over half of the reduction was among young men. Barron et al. then go on to report results week-by-week using an event study, and it looks like most of the effect is concentrated in the first few weeks of the ban. That suggests that there might be some adaptation, or that there was less compliance with the ban as it extended over time. Those results should caution us from assuming that a complete prohibition on alcohol would lead to a large improvement in mortality.

Finally, using police data Barron et al. find that there were:

..at least 77 fewer homicides, 790 fewer assaults and 105 fewer rape cases reported per week during the alcohol ban period in comparison to the preceding five weeks. These constitute a drop in each outcome of 21%, 33% and 19% respectively.

Altogether, this supports a conclusion that the alcohol ban reduced interpersonal violence, leading to less alcohol-related harm, and lower mortality. We know that alcohol is associated with harm. This study has given us a particularly clean estimate of just how much harm it can cause.

[HT: Marginal Revolution]

*****

[*] Actually, that's not quite true, as there was also a curfew put in place, but the curfew lasted much longer than the alcohol ban, and Barron et al. show that removing the ban but leaving the curfew in place was associated with a bounce back in mortality and other outcomes.

We can (and should) support tertiary education students more

Auckland Central MP Chloe Swarbrick and I probably don't agree on too much when it comes to economics, but I can agree on this from her column in the New Zealand Herald today:

This week is the beginning of Semester One for many tertiary education students around the country. There's a lot made of the "choice" to take on higher education, to the extent that in the 1980s, politicians began the process that would see students take on ever-increasing, exorbitant debt and decreased quality of life to get through it.

For far too many in this country, this supposed "pathway out of poverty" tends to look quite a lot like a level of mainstream social comfort with several years spent in poverty.

There's a neat story in "the student experience" of two-minute noodles, mouldy flats and part-time work. Working or studying in poverty isn't some cute cosplay. Students are paying an arm and a leg to live in flats that see some develop preventable respiratory illnesses that may stay with them the rest of their lives. Working to study now means chasing the tail of recorded lectures in the dead of the night after a day of low-paid work in order to afford … to study.

How far can we argue our society has really developed if one of our main arguments for this continual suffering is "I went through it too"?

In my ECONS102 class, we discuss the private tertiary education decision as weighing up the private costs and benefits of education. Students face a range of costs associated with tertiary education, including the costs of tuition fees, books, stationery, and so on. However, by far the largest cost is foregone income - students have to give up some time that they could have spent working, in order to spend that time studying. On the other side of the equation, the benefits of education are mainly captured in a higher future income once they graduate.

The fact that the costs of tertiary education has up-front costs, but the benefits don't happen until sometime in the future creates a number of problems. First, and most obviously, how are students expected to pay for their education? They face very real credit constraints. Banks and other lenders are typically unwilling to lend money for educational purposes, because there is little in the way of collateral that can be seized in the event of non-payment of the loan. So, students would find it very difficult to borrow in the private loan market to fund their education. Like many western countries, New Zealand solves this problem by a system of student loans. Students can borrow from the government now to pay the costs of their education, and then repay the loan through the tax system once they start earning (hopefully, following graduation and a higher-paying job).

Students can borrow to cover the cost of their fees, course-related costs (for books, stationery, computer items), and living costs. However, there is a problem here. Students can currently borrow up to $242.53 per week for living costs (see here). But if you know anything about the cost of living, you know that isn't going to stretch too far. And forget student allowances. As Swarbrick notes in her article:

Students make up 6 per cent of the population of this country. Of those 350,000 odd students, only around 8 per cent of them receive means-tested student allowance, on average receiving half of the maximum, leaving the small minority who do get that support with around $130 a week. The average rent in this country is $540 a week.

Of course, Swarbrick is overstating the case, because students aren't all going to be renting their own home and paying the average rent by themselves. Nevertheless, it should be clear that student loans and the student allowance (currently $240.65 for a single student living away from home, if they qualify - see here) are not sufficient to pay all of a student's living costs.

The meagre nature of the support that is provided to students explains why so many students have to work while studying. So what, you say? Students should be picking fruit? Working has a negative impact on students' academic performance (see here). The more that students have to work in order to live, the less time that they can devote to their studies, and the lower quality education they will receive. And this has equity implications as well. Students from well-off families might be able to avoid having to juggle work and study, being well supported financially by their parents. Students from lower socio-economic groups do not have that luxury. The current system reinforces existing societal inequities.

We need to provide better financial support to tertiary students. Students shouldn't have to be the only group in society that has to borrow in order to live. They shouldn't have to compromise their studies in order to be able to feed and shelter themselves. And the way that tertiary education students fund their studies shouldn't simply transfer inequity from one generation to the next.

There is a good argument to be made that students are the beneficiaries of their education, because their future income is higher, and therefore they should be the ones to pay the costs of that education. That is a good argument for why students should pay tuition fees, and why the first-year free tuition should be scrapped. However, students are not the only ones who benefit from their education. As Swarbrick notes in her article:

It's argued you can earn more after you complete a degree, so why should "the rest of us" shoulder the burden?

Firstly, try telling that to a nursing or teaching student. Secondly, every time you walk into a building and it doesn't collapse, or know you're in safe hands in the emergency room of the hospital, you're benefiting from other people's education.

The very fact that you don't have to understand the technological process underlying the computer code presenting these words on a screen for your reading pleasure, let alone that if you're reading this in print, you don't have to understand the proliferation of the printing press, means you're benefiting from others' education, experimentation and investment. It shows we as a society all benefit from the education of each other.

Imagine how many other life-changing inventions and ideas could have been found had the brains capable of founding them been encouraged and supported, not punished to prove their worthiness to survive.

That barely scratches the surface of the social benefits of education, which also include higher tax payments (from higher-educated and higher-earning taxpayers), lower crime, healthier lifestyles (and lower public healthcare costs), better social outcomes for children (of higher-educated parents), healthier democratic processes, a richer and more sophisticated cultural environment, and more skilled volunteers for charity organisations. For all of these future social benefits, it is reasonable for the government to better support students in covering their living costs now.

How should the government better support students? I'm generally not in favour of a universal basic income, but in the case of students I can see a strong argument for one. The key question is how generous such a payment should be. As a starting point, consider paying all full-time students an amount equal to the full-time minimum wage. From 1 April 2022, that would be $848 per week before tax, and probably around $720 per week after tax. Students should easily be able to support themselves on that, without needing to work (in fact, this treats their studying as a full-time job). The total net cost of this is around $7.6 billion per year (based on 330,000 domestic students being paid $720 net per week for 32 weeks per year). Total government spending on education (at all levels) is currently about $15 billion per year, so that would probably be an infeasible increase (and might come from Vote Social Development, rather than Vote Education, in any case). It is certainly well up on the $680 million currently paid in student allowances per year (see here). The payment needn't be nearly as generous as the starting point of paying all students the full-time minimum wage, but there is clearly scope for something more than is currently offered. And more is clearly needed.

Finally, the payment should come with strings attached. The point of paying students generously is so that they can focus on their studies. There could be a case for means testing, to incentivise students not to take on too much additional work. Also, there should be an expectation of attendance at classes, and completion of courses. In order to qualify, students should have to attend a certain (and high) proportion of all of their classes, and to maintain a passing academic record. Given the generous nature of a payment like this, students need to fulfil their obligations to study.

We need to revise the social contract with tertiary students. Taxpayers need to support them better, and they need to use that greater level of support to focus more on their studies. Tertiary education has significant social benefits, and the current meagre support that is available to tertiary students is hampering their studies and actively impeding their future contributions to society. We can (and should) do better.

The non-effect of images of half-naked women on economic behaviour

You can get away with a lot of crazy things in a lab experiment (tempered somewhat by the fact that whatever you propose has to be approved by an ethics committee). For example, this 2018 paper by Evelina Bonnier (Stockholm School of Economics) and co-authors describes a lab experiment where research participants were shown advertisements, of three kinds:

...a treatment where advertisements contain half-naked women dressed in bikini or underwear, a treatment where advertisements contain fully dressed women, or a control condition where there are no women present.

Participants were then tested on their risk taking preferences, their willingness to compete, and the mathematics performance. Specifically:

Risk taking is measured from having participants complete two multiple-price lists in which they face a series of decisions between two lotteries, where one is more risky than the other. Participants make 20 such choices and our measure of risk taking is defined as the fraction of more risky lottery choices. The competitiveness task... participants in a first stage perform a math task and get paid according to a piece-rate scheme. In a second stage, participants perform a similar math task and are paid according to a competitive winner-takes-all tournament scheme. In a third stage, participants get to choose between the two payment schemes before performing the task for a third time. Willingness to compete is measured from this binary choice. As a measure of math performance, we use the number of correctly solved math problems in the first non-competitive stage of the competitiveness task. 

The research participants were 648 students (331 men and 317 women) at the University of Copenhagen or the University of Valencia. Bonnier et al. find that there are:

...no treatment effects on any of the three main outcome measures for female participants. For men, we also find no effect on math performance or willingness to compete, but suggestive evidence that men take more risk after having been exposed to images of half-naked women... Moreover, we do not find a significant difference between the half-naked treatment and the fully dressed treatment on risk taking for men.

Risk taking was 4.8 percentage points higher among men who saw the images of half-naked women compared with the control group who saw no women (47.1% vs. 42.8%), but this difference was only statistically significant in some (but not all) analyses. That probably reflects that the real effect (if any) is quite small, and so you would need a much larger sample in order to robustly find any effect of half-naked pictures on men's risk taking behaviour. That there was no statistically significant effect for women probably accords with expectations, although risk taking was about 4 percentage points higher for women who saw images of fully dressed women than the control group women. Interestingly, although this difference was statistically insignificant, it was larger than the difference for men.

So, more research is needed on this topic, if we really wanted to know how exposure to images of half-naked women affects economic behaviour. And, of course, as Bonnier et al. note in their conclusion, in the interests of gender equity:

...it would be interesting to explore the effects of exposure to images of half-naked men.

[HT: Marginal Revolution, back in 2018]