Lecture recording and lecture attendance

Should lectures be routinely recorded and made available to students? This is a question that frequently comes up at staff meetings, education or academic committees. Arguments in favour of lecture recording include that it increases flexibility for students, helps with revision, reduces the negative impacts of timetable clashes, allows students to manage their non-study commitments (work, family, etc.), and improves equity for students with disabilities or those studying in a second language. Arguments against lecture recording include negative impacts on class attendance, that students relying on recorded lectures miss participating in important in-class activities and discussions, and (occasionally) that guest lecturers (or the lecturers themselves) do not want their recorded images available online.

I want to focus this post on the impact of recordings on class attendance, prompted by this article in The Conversation last week, by Natalie Skead (University of Western Australia) and co-authors. :

We conducted a large-scale study in our law school to uncover whether lecture recordings are responsible for declining student attendance and what motivates students to attend or miss class.

By manually counting how many students were in lectures across sixteen different subjects, we found attendance rates averaged just 38% of total enrolments across the semester.

There was a natural ebb and flow of lecture attendance throughout the semester. There was peak attendance at the beginning (57%), a significant drop in the middle as assessments became due (26%) and a rebound at the end of semester as exam season hit (35%).

Attendance at 38% is horrifically low. When asked about reasons for non-attendance, Skead et al. note that:

Availability of lecture recordings was the most common reason students gave for not attending lectures (18% of students said this). But work commitments were a close second (16%). Then it was timetable conflicts (12%), the time and day of lectures (11%) and assessments being due (8%).

So, lecture recording is just one factor among many that affects lecture attendance. In my experience (both as a student and as a lecturer) the biggest impact on attendance is value added. If a lecture consists mainly of reading from pre-prepared PowerPoint slides (especially if they are the default textbook slides), then students will rightly question whether attendance is worth it.

I have recorded all of my lectures in both first-year economics papers for at least the last ten years. Attendance at my lectures doesn't appear to be negatively affected by recording. There was no noticeable drop-off in attendance when I started recording, and when I look at the server logs, it tends to be the students who are attending class who are watching the recordings (for revision), rather than the students who are not attending. I guess it is possible that students are not attending and trying to convince themselves that they will watch the recordings, then failing to do so. However, there isn't any data to support that assertion.

So, why would recording my lectures have little (if any) effect on attendance? I try to make attendance at my lectures worthwhile by punctuating the lectures with exercises - opportunities to practice the material immediately. And while students are completing the exercises, I circulate the room talking to them and providing directed assistance. This interactive teaching approach gives me important feedback on what the students are not understanding, but also helps develop students' learning. This is one aspect of my teaching practice that students most agree is helpful to their learning, and if they're not attending class they wouldn't be exposed to it.

Unfortunately, there are trade-offs with any teaching approach, including interactive teaching. The interactive teaching approach doesn't work quite so well for recorded lectures, unless students are willing to pause recordings and work on the problem before proceeding. In my experience, the majority of students who are watching recorded lectures don't do this (again, the server logs show this - in fact, many students watch only portions of the lectures). This makes attendance in my lectures the number one contributor to students' grades. I don't keep this a secret - on the first day of class, I tell my students how important attendance is going to be, and show them the data (from the previous year) to support it. And when a student appeals their failing grade at the end of a semester, invariably if I look, I will see that their attendance was low.

Encouraging attendance is therefore important. A rational student is going to weigh up the costs and benefits of attending class. Given particular opportunity costs of attending, attendance can be increased if the benefits are increased. I began offering extra credit in my ECON110 (now ECONS102) class in 2012, and extended it to ECON100 (now ECONS101) in 2016 (see this post for more details). So, students receive both an extrinsic reward (extra credit) and an intrinsic reward (better learning) by attending class.

The overall effect is that attendance remains fairly high in ECONS101 and ECONS102 throughout the semester. Of course, as with all papers, attendance in my class does drop off over time, but in ECONS101 last A semester we had attendance of 58% in the second-to-last week (that was the lowest attendance for the entire semester).

So, it is possible to maintain high attendance in spite of routinely recording lectures. Lecturers simply need to make it worth students' while to attend.

Why having a safer car could make your car insurance more expensive

When a car owner buys car insurance, they are looking to shift some of the cost of an accident onto the insurer. In exchange, the car owner agrees to pay an annual (or monthly) premium to the insurer.

Is selling insurance worth it to the car insurer? As with any decision, it depends on weighing up the costs and benefits. If the costs of offering insurance are greater than the benefits, then selling insurance would make the car insurer worse off (they would make a loss), and so they shouldn't sell car insurance. If the benefits are greater than the costs, then selling car insurance makes the car insurer better off (they would make a profit), and so they should sell car insurance.

How does the car insurer decide on the insurance premium? Obviously, they need to know how much it will cost them, and then set the premium to be higher than the cost (to ensure that they make a profit). Let's simplify things and say that all cars are the same, and all have the same chance of being involved in an accident. In simple terms, the cost of selling insurance to a car owner is the repair and other costs that the insurer would have to pay in the case of an accident, multiplied by the probability of there being an accident. For example, if there is a 5% chance on average of there being an accident in any year, and the accident would cost $20,000 in repairs and other costs, then the cost of providing insurance would be $1,000 ($20,000 x 5%) per year. In order to make a profit, the insurer would have to charge an insurance premium of more than $1,000 per year.

So, what happens to the car insurance premium if cars get safer? The probability of an accident probably goes down, but the cost of repairs goes way up. So, does the cost of providing car insurance go down (less chance of having to pay the repair costs), or up (when there is a repair, the cost of the repair is much higher)? We can't tell - the effect on the cost of providing insurance is ambiguous, because we can't tell if the cost goes up or down.

However, as this recent article in Wired reports:

American car insurance rates are going up up up. In the past decade, they climbed 29.6 percent, to an average of $1,548 in 2019 from $1,194 in 2011. The surge, detailed in a new report from insurance shopping site The Zebra, outpaced both inflation (by far) and the increase in average car prices (more narrowly). And it came even as the rate of crashes has fallen year over year.

Aggrieved drivers have plenty of directions to point their fingers. Vehicle theft is on the rise, and extreme weather fueled by climate change can destroy swaths of vehicles in short order...

A more surprising, counterintuitive culprit isn’t the wider world or the person behind the wheel but the car itself. It turns out that new features designed to keep vehicles in their lanes and out of trouble are contributing to rising insurance rates.

That’s because the sensors that power those systems make cars much more expensive to fix when they do crash. Dent a steel bumper, and a few hammer blows gets you back on the road. Smash one on a new car, and it could mean replacing a radar, a camera, and ultrasonic sensors, then calibrating them so they work properly. Replacing a cracked windshield now comes with the extra cost of having someone readjust any cameras that look through the glass. “Technology is playing a bigger role than ever in pricing,” says Nicole Beck, The Zebra’s communications chief. “It’s not actually making it cheaper for people.”

While some studies have shown the effectiveness of emergency braking, insurance companies haven’t yet seen enough evidence to justify a break in rates for most of these features. That’s not to say lane keeping, parking assist, and the rest don’t work. They’re all relatively new, and the actuaries aren’t yet confident that their benefits outweigh the extra costs they incur to repair.

So, these new safety features do reduce accident rates, but because they cost so much more to repair, the cost of providing insurance is increasing. So, insurers are passing the cost onto consumers, in the form of higher insurance premiums. However, this increase in insurance premiums might not last. As the article notes:

The good news for car owners is that the steep upward trend in rates may not last. More data showing the upsides of driver assistance tech may accrue. Repairs should get cheaper as more mechanics learn to replace and calibrate sensors and as the prices of those parts drop. The mystery lies in figuring out how long those trends will take to make their effects felt. “Knowing that it’ll happen eventually is pretty easy,” Carges [the chief actuary at Root Insurance] says. “Knowing exactly when the inflection point is, is not.”

When the costs of repairs come down, the cost of providing insurance comes down, and insurers will start to charge lower premiums for car insurance.

[HT: Marginal Revolution]

Book review: Reinventing Capitalism in the Age of Big Data

One of the books I recommended for the Prime Minister's summer reading list was Reinventing Capitalism in the Age of Big Data, by Viktor Mayer-Schönberger and Thomas Ramge. At this time, I thought it would be good for understanding the current period of creative destruction. However, I'm not so sure now.

The premise of the book is to promote the idea of 'data-rich markets', which rely on three elements: (1) Improvements in data ontology (the way we organise data); (2) Advances in matching algorithms; and (3) Machine learning systems to observe us and identify our preferences. To many of us, that probably sounds dystopian and maybe a little tone deaf given the current debates over data and privacy.

Mayer-Schönberger and Ramge are well-intentioned - they suggest that data rich markets will increase efficiency. Which is probably true, but does not come without cost. In my ECONS101 class, we talk about perfect price discrimination, where every consumer pays a different price. If executed perfectly, with full knowledge of what consumers are willing to pay, every consumer will pay the maximum that they are willing to. Ironically, that approach maximises economic welfare - it is perfectly efficient. However, it involves a substantial transfer of welfare from consumers to producers, and whether that is ideal may be debatable.

Mayer-Schönberger and Ramge argue that we make decisions on the basis only of price. They note that:

Price greatly reduces the amount of information that needs to flow through the market; the information is compressed into a single figure for which traditional communications channels are sufficient.

However, to make such a claim is to ignore the fact that, from the consumer's perspective, price is only one element of the decision. Again, thinking about ECONS101, our model of consumer choices demonstrates that a consumer's choice to purchase depends also on the price of all other goods, the consumer's income, and most importantly of all, their preferences. The consumer's preferences are not collapsed into a price. The price may collapse the information for the other side of the market (i.e. for sellers), but not for buyers.

This isn't the only place where Mayer-Schönberger and Ramge betray a misunderstanding of key economic principles. They also have an idea that, in the future, money will become irrelevant, and that we will transact using data. For example, they argue that corporations might pay their taxes in data. However, money has several functions, of which being a medium of exchange (e.g. for paying taxes) is just one. Importantly, money is a unit of account - you can measure the value of things with it. Data can't easily replace money's function as a unit of account. To use their own example, how would the taxes that a corporation needs to pay be measured? No doubt in dollars, i.e. money as a unit of account.

There are some interesting examples in the book, but sometimes they haven't been thought through well enough. For instance, shortly after claiming that banks' business models are doomed to failure (my words, not theirs), they present the example of Robinhood Markets, which allows people to trade stocks on US exchanges with zero commission. They can afford to do that because they "depend on interest generated from deposited but not yet invested funds". But wait? If banks are doomed to failure, then where is this business going to get its interest income from in the future? Isn't it doomed to failure as well? Similarly, based on my experiences, I'm not convinced that Amazon's product recommendation engine is an exemplar for anything (e.g. when will it stop recommending books that I have already bought... from Amazon?).

When I bought this book, I thought it was going to challenge the current market model and present a potential alternative. It does that, but in the opposite direction of what I expected! I'm not convinced that we need more freedom for markets. The book fails to engage with some of the obvious critiques that it will engender. First, how does would data-rich markets prevent or mitigate a new Global Financial Crisis? It seems to me that, if anything, the risks would be greatly increased. Second, although the authors argue the opposite, won't data-rich markets simply embed decision-making biases further into decisions through their extensive use of algorithms? Cathy O'Neil's book Weapons of Math Destruction (which I reviewed here) seems very relevant.

In short, I'm kind of glad this book didn't make it onto the Prime Minister's summer reading list. I recommend that you avoid it too.

The origins and consequences of the Mexican drug cartels

A new article published in the Journal of Development Economics (sorry I don't see an ungated version online), by Tommy Murphy and Martin Rossi (both Universidad de San Andres) tracks the history and consequences of drug cartels in Mexico. There are several surprising bits in this article, especially for those of us with less knowledge of Mexican history. First, on the origins and geographical distribution of the cartels:

The distribution of cartel activities in Mexico is, of course, the result of many different factors, some which are better understood than others. Here we document the particular claim made by some authors... that one of these factors is the Chinese immigration to Mexico at the turn of the 19th century, and provide evidence that its influence seems to persists until today. A series of events justifies this connection. Drug prohibition (mainly in the U.S.) created the market that illicit organizations eventually filled. Yet the time in which this took place (the 1910s) made Chinese migration relevant, particularly the one that settled in Mexico around the turn of the 20th century. During the 19th century many Chinese emigrated and sought refuge in the Americas. For the most part, this flow directed towards the U.S., but in the early 1880s the U.S. introduced restrictions on immigration aimed at Chinese people, many of which end up settling in Mexico. This event is important to understand the onset of drug trade in the region, as there are good reasons to believe the Chinese had a comparative advantage in that trade. One of them is that, outside alcohol and tobacco, the main ‘recreational’ drug consumed at the time was opium... But, along with an advantage in the production of a good whose market remained largely unregulated until the 1920s, Chinese arguably also had developed an advantage on the distribution of illegal goods across the border. With the restriction on Chinese immigration by the U.S., many Chinese south of the border began to gather specialized knowledge on an activity that will prove useful with the introduction of drugs prohibition: smuggling Chinese into the U.S...

So, the areas where Chinese migrants settled were more likely to be areas where opium was cultivated, because Chinese migrants brought opium seeds with them. Chinese migrants had a comparative advantage in producing opium, and then developed a comparative advantage in smuggling into the U.S. as well. This knowledge would eventually filter to the locals in the areas where the Chinese were located, who wanted to take over the business. Murphy and Rossi note that:

...part of the well-recorded sinophobia that eventually lead to the expulsion of most Chinese from Mexico was influenced by criminals wanting to gain control of this lucrative business.

So, after the Chinese were expelled, the Mexicans had control of the opium growing and smuggling operations. Importantly, Murphy and Rossi then go on to show that:

...places where more Chinese migrated at the turn of the 20th century, nowadays are more likely to show cartel activity.

Specifically, they find that municipalities where the Chinese were present in 1930 are 12.8 percentage points more likely to have cartel activity in the 21st Century, than municipalities without Chinese present in 1930. That's after controlling for a lot of population and geographical variables, including the presence of German migrants (which would pick up any areas that are on average more attractive to migrants), and distance to the U.S. border. Drug cultivation and supply are reasonably persistent activities, particularly when they are highly profitable.

Murphy and Rossi then use their initial results (Chinese presence in 1930 is associated with cartel activity in more modern times) to investigate the socio-economic effects of cartel activity (in an instrumental variables analysis). They find that:

...cartel presence ...is strongly associated with good socioeconomic outcomes, such as lower marginalization rates, lower illiteracy rates, higher salaries, and better public services. We also report that cartel presence is associated with higher tax revenues and more political competition, in line with what is reported in Mexican literature.

This result is a surprise, since we typically think about the cartels as being overwhelmingly negative. However, Murphy and Rossi explain that:

...the counterfactual are Mexican municipalities without cartel presence. It is then entirely possible that all municipalities in Mexico are worse off compared to a situation without cartels, even if within Mexico those with cartels are doing relatively better.

Everything is relative, including the impact of drug cartels it seems. They also argue that:

...since their main business is not –in principle– intrinsically based upon violence (as mafia), but on producing and distributing a tradable good, they have local positive effect in the areas where their activities are concentrated.

This point is a little bit harder to believe. We know from lots of media reports that there is extreme violence associated with cartel activity. Perhaps areas that have more cartel activity have more government resources devoted to them? Perhaps the data are subject to some selection bias in those areas? I think we need more investigation on this before we can conclude that cartel activity is positive.

[HT: Marginal Revolution]

Read more:

• Book review - Narconomics
• Why your anti-drug policies just might annoy your neighbours
• What do Mexican maize farmers do when maize prices are low?