Perpetual Guardian, four-day workweeks and the Hawthorne effect

Back in February, the trust management company Perpetual Guardian caused a bit of a media stir by announcing that it would trial moving all of its employees to a four-day week (with no salary reductions). Importantly, they also announced that they would evaluate the trial. We were let in on the results of that trial today, as the New Zealand Herald reported:

The Kiwi boss who trialled giving his staff a full salary for four days' work says it was a success and that he wants it to become permanent at his Auckland company.

Andrew Barnes, the chief executive at Perpetual Guardian, says he's already made a recommendation to his board to take the policy beyond the initial eight –week trial...

During March and April, Perpetual Guardian conducted what was essentially a corporate experiment in allowing the company's 240-person staff to retain full pay as well as a three-day weekend.

To ensure an objective analysis, Barnes invited academic researchers Jarrod Haar, a professor of human resource management at AUT, Dr Helen Delaney, a senior lecturer at the University of Auckland Business School, into the building to observe the impact of the trial on the workforce.

From the outset, there was always the risk that reducing work hours would increase the stress on staff to achieve objectives while also leading to lower levels of output as working time was cut by a fifth.

But, as the trial rolled on, the researchers found quite the opposite to occur. 

"What we've seen is a massive increase in engagement and staff satisfaction about the work they do, a massive increase in staff intention to continue to work with the company and we've seen no drop in productivity," said Barnes.

You can read Jarrod Haar's report (or at least a brief version of it) here. The key point though, that makes me skeptical that we can take too much away from this trial, is that the data are based on surveys of staff and supervisors.

Think about the incentives here. Your boss offers to reduce your workweek to four days as a trial, with no decrease in your pay, and announces that they will be evaluating the impact of that trial. You're then asked to fill out a survey just before the trial starts, and then again just after the trial ends. The survey asks a bunch of questions about how you feel about your job (and other related stuff).

You know this is just a trial. If the trial goes well, then it's likely your boss will want to make the change permanent. If the trial doesn't go well, then you're probably back to working a five-day week. What would you do?

It doesn't take a PhD to work out that staff survey data is basically worthless here. You want something that the staff can't game. The supervisors' survey answers are no more valuable. They have the same incentives to game their responses as the staff do. Maybe you could observe behaviour, or measure workplace productivity? Nice try, but if the staff know what you're measuring they will game that too.

This is an example of the Hawthorne effect, which The Economist does a great job of explaining:

The experiments took place at Western Electric's factory at Hawthorne, a suburb of Chicago, in the late 1920s and early 1930s. They were conducted for the most part under the supervision of Elton Mayo, an Australian-born sociologist who eventually became a professor of industrial research at Harvard.

The original purpose of the experiments was to study the effects of physical conditions on productivity. Two groups of workers in the Hawthorne factory were used as guinea pigs. One day the lighting in the work area for one group was improved dramatically while the other group's lighting remained unchanged. The researchers were surprised to find that the productivity of the more highly illuminated workers increased much more than that of the control group.

The employees' working conditions were changed in other ways too (their working hours, rest breaks and so on), and in all cases their productivity improved when a change was made. Indeed, their productivity even improved when the lights were dimmed again. By the time everything had been returned to the way it was before the changes had begun, productivity at the factory was at its highest level. Absenteeism had plummeted.

The experimenters concluded that it was not the changes in physical conditions that were affecting the workers' productivity. Rather, it was the fact that someone was actually concerned about their workplace, and the opportunities this gave them to discuss changes before they took place.

The Perpetual Guardian situation isn't quite the same as the original Hawthorne experiments, but in general we refer to the potential for Hawthorne effects as occurring whenever you conduct an experiment in a workplace and the workers know they are being monitored more closely than usual.

How do you get around this problem? You need to find something that the workers will find more difficult to game. For instance, if you think the four-day week will reduce workplace stress, you could test workers' cortisol levels before and after the trial. It is much more difficult for workers to game a biophysical response than a survey response.

So, the takeaway message here is: don't read too much into the Perpetual Guardian trial. If they roll out the four-day week on a more permanent basis, it will be interesting to see if they still think it's a good idea after a year or two.

[Update: Jarrod Haar wrote an article about the research on The Conversation. No limitations such as those I have highlighted are mentioned.]

The benefits (or not) of school uniforms

I've blogged a couple of times about school uniforms (see here and here), mostly to highlight the negative impacts of giving firms market power. That highlights the costs of introducing school uniforms (or more accurately, the costs of introducing school uniforms and then having a single monopoly seller of those uniforms). What about the benefits of school uniforms? Many people argue that there are a number of benefits of school uniforms (see for example here or here). Is there evidence to support the assertions of the benefits of school uniforms?

A 2012 paper by Elisabetta Gentile and Scott Imberman (both University of Houston), published in the Journal of Urban Economics (ungated earlier version here), provides us with some evidence. Gentile and Imberman use data from "a large urban school district in the southwest United States" with "more than 200,000 students and close to 300 schools", and look at the impacts of school uniform policies on school attendance, the rate of disciplinary infractions, suspensions (in-school and out-of-school), and achievement in maths, reading, and language. They look at both elementary schools and middle/high schools. Importantly, over the period they look at (1993-2006):

Initially, only a handful of schools required uniforms. However, uniform adoption grew substantially over the following 13 years. Of schools that responded to our survey of uniform policies, which we describe in more detail below, only 10% required uniforms in 1993. By 2006, 82% of these schools required uniforms. In addition, no schools abandoned uniforms after adoption.

So, we know there is sufficient variation in school uniform policies that we can essentially be looking at before-and-after comparisons within each school of the effects of adopting a school uniform policy. After controlling for student, school, and principal characteristics, they find:

For elementary students we find little evidence of uniforms having impacts on attendance or disciplinary infractions... On the other hand, for middle and high school students, we find significant improvements in attendance rates, particularly for females... female attendance increases by a statistically significant 0.3 percentage points after uniform adoption. This is equivalent to an additional 1/2 day of school per year in a 180 day school-year... For disciplinary infractions estimates for middle/high school students are similar to those for elementary students. 

In other words, there was some evidence that uniforms are associated with greater school attendance (for middle/high school students), but no association with discipline (including suspensions). Interestingly, they also find that:

...attendance improvements mainly accrue to students who are economically disadvantaged, particularly those who are in high poverty schools.

Given that attendance improves, and improves most among disadvantaged students, does this translate into better student achievement? Unfortunately, their:

...results indicate that uniforms have little impact on achievement gains.

There's also no evidence of an impact on students switching schools (either to avoid uniforms or to get into a school that has uniforms) and no association with grade retention. Overall, there is little evidence to support claims that school uniforms reduce bullying or violence. And while it might be good if school uniforms increase school attendance, that isn't much benefit if it isn't reflected in learning gains.

Read more:

• Market power, mark-ups and school uniforms
• School uniform monopolies

The success of smiling football teams and scientists

Which of these two groups will win on Monday morning (New Zealand time)?

Can you tell just by the photos which team is more likely to win? For instance, if the players are smiling, does that indicate self-confidence and a higher likelihood of victory? If they're striking a more angry facial expression, does that demonstrate strength and determination?

In a new paper published in the Journal of Economic Psychology (ungated earlier version here), Astrid Hopfensitz (University of Toulouse Capitole) and Cesar Mantilla (Universidad del Rosario, Colombia) looked at data from player photos (from the Panini stickers collections) for every world cup from 1970 to 2014. First, they identified using automated software (FaceReader):

...the activation level of six basic emotions: anger, happiness, disgust, fear, sadness, and surprise, which are non-exclusive.

They then tested whether those emotions (averaged at the team level, rather than individually) were associated with team success in the World Cup, for the 304 teams that took part in those tournaments. They found that:

...display of anger as well as happiness is positively correlated with a favorable goal difference (i.e. more goals scored than conceded). This correlation is robust to the inclusion of our control variables... We also observe the standardized display of anger and happiness is negatively correlated with the overall ranking in the World Cup... That is, teams that display either more anger or happiness, reach an overall better position in the whole tournament...

We observe a clear difference with respect to the two emotions. While the display of happiness is linked to the scoring of goals... anger is linked to conceding fewer goals...

Interesting, when they separate the analyses for defensive and offensive players, they find that:

...the display of happiness is still predictive in each sub-group. By contrast, the display of anger remains predictive only for defensive players, and for one of the outcomes.

Teams with happy offensive players do well, and teams with happy (or to a lesser extent, angry) defensive players do well.

Now, I know you're scrolling back up to check the France and Croatia teams to see who is smiling more [*], but before you do you should know that the links between smiling and success are an example of correlation, not causation. There isn't anything in the study to suggest that smiling causes success, even though you can tell a plausible story about it.

However, you should also know that the correlation between smiling and success isn't limited to football. In another new paper, published in the Journal of Positive Psychology (ungated version here), Lukasz Kaczmarek (Adam Mickiewicz University, Poland) and co-authors looked at the correlation between smiling and success for scientists. Using data for 220 male and 220 female scientists taken from the research social networking site ResearchGate, Kaczmarek et al. first coded whether the researchers were smiling in their profile picture, and then looked at whether that was related to a range of research metrics. They found that:

As expected, smile intensity was significantly related to the number of citations, the number of citations per paper, and the number of followers after controlling for age and sex... Smile intensity was not significantly related to the number of publications produced by the author or the number of publication reads.

It is plausible that there is causality working in two directions here. More successful researchers (those whose papers are cited more often) are more likely to be smiling, happy people (explaining the correlation between citations and smiling), while smiling, happy researchers are more likely to entice other people to follow them on a social network (explaining the correlation between followers and smiling). However, more work would need to be done to establish whether those explanations hold for a larger sample.

Either way, both studies suggest a strong correlation between smiling and success. Go Croatia!

[HT: Marginal Revolution, for the Kaczmarek et al. paper]

*****

[*] Please note that I take no responsibility for the outcomes of any bets you make as a result of your new knowledge about successful smiling footballers.

Oh, the places you’ll go!

In economics, the cost-benefit principle is the idea that a rational decision-maker will take an action if, and only if, the incremental (extra) benefits from taking the action are at least as great as the incremental (extra) costs. We can apply the cost-benefit principle to find the optimal quantity of things (the quantity that maximises the difference between total benefits and total costs). When we do this, we refer to it as marginal analysis.

Marginal analysis challenges the idea that we are always better off with more of things. Yes, we might like there to be more white rhinos, but if there was one living in every front yard, we'd probably regret it. More is not always better.

The easiest way to understand marginal analysis is to see it in action. A recent article in The Economist provides us with a good example:

When it comes to habitat, human beings are creatures of habit. It has been known for a long time that, whether his habitat is a village, a city or, for real globe-trotters, the planet itself, an individual person generally visits the same places regularly. The details, though, have been surprisingly obscure. Now, thanks to an analysis of data collected from 40,000 smartphone users around the world, a new property of humanity’s locomotive habits has been revealed.

It turns out that someone’s “location capacity”, the number of places which he or she visits regularly, remains constant over periods of months and years. What constitutes a “place” depends on what distance between two places makes them separate. But analysing movement patterns helps illuminate the distinction and the researchers found that the average location capacity was 25. If a new location does make its way into the set of places an individual tends to visit, an old one drops out in response. People do not, in other words, gather places like collector cards. Rather, they cycle through them. Their geographical behaviour is limited and predictable, not footloose and fancy-free.

When it comes to the number of locations we visit, there appears to be an optimal number and that optimal number is 25. Why? Consider the costs and benefits of adding one more location to the number that you regularly visit. We can refer to those costs and benefits as marginal costs and marginal benefits. When economists refer to something as marginal, you can think of it as being associated with one more unit (in this case, associated with one more location that you regularly visit).

The marginal benefit of locations declines as you add more locations to your regular routine. Why is that? Not all locations provide you with the same benefit, and you probably go to the most beneficial places most often. So naturally, the next location you add to your regular routine is going to provide less additional benefit (less marginal benefit) than all of the other locations you already visit regularly. So, as shown in the diagram below, the marginal benefit (MB) decreases as you include more locations in your routine.

The marginal cost of locations increases as you add more locations to your regular routine. Why is that? Every location you choose to go to entails an opportunity cost - something else that you have given up in order to go there. When you add a new location to your routine, you are probably giving up spending some time at one of the other locations you were already going to, which provide you with a high benefit. The more locations you add, the more you need to cut into your time at high-benefit locations. So, as shown in the diagram below, the marginal benefit (MC) increases as you include more locations in your routine.

The optimal number of locations occurs at the quantity of locations where marginal benefit exactly meets marginal cost (at Q*). If you regularly visit more than Q* locations (e.g. at Q2), then the extra benefit (MB) of visiting those locations is less than the extra cost (MC), making you worse off. If you regularly visit fewer than Q* locations (e.g. at Q1), then the extra benefit (MB) of visiting those locations is more than the extra cost (MC), so visiting one more location would make you better off.

And, it turns out, the optimal number of locations (Q*) is limited to roughly 25.