Job fatality and injury risk, and compensating differentials

Last week, my ECONS102 class covered health economics. Part of that topic involves discussion of approaches to measuring the 'value of a preventable fatality' (sometimes also called the 'value of a statistical life', or VSL). One of those approaches is the willingness-to-pay (WTP) approach, which involves estimating what people would be willing to pay in order to avoid small increases in risk. One way of applying the WTP approach in practice is to look at revealed preferences, based on people's actual risk avoidance behaviour. And one example that I use in class to illustrate the revealed preference method is to measure compensating differentials which, rather than measuring willingness-to-pay to avoid risk, measure workers' willingness-to-accept additional risk.

Compensating differentials recognise that jobs that differ in non-monetary characteristics may offer different wages. For example, consider two jobs that are similar in terms of skill requirements. If one of the jobs has positive non-monetary characteristics (e.g. it is safe, clean, and engaging), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, if the other job has negative non-monetary characteristics (e.g. it is dangerous, dirty, and boring), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. The difference in wages between the attractive job that lots of people want to do and the unattractive job that fewer people want to do is called a compensating differential. The compensating differential essentially compensates workers for working in jobs with negative non-monetary characteristics compared with working in jobs with positive non-monetary characteristics.

The risk of being injured on the job is a substantial negative non-monetary characteristic for some jobs. Based on the idea of compensating differentials, workers should only be willing to take on a job with a higher risk of death or injury if that job comes with a higher wage. Measuring that additional wage would provide a measure of the compensating differential, which could then be used to estimate the value of a preventable fatality.

As an example, consider this 2022 article by Zac Reynolds, Daehoon Nahm and Craig MacMillan (all Macquarie University), published in the journal Economic Record (open access). They estimate compensating differentials for job fatality and injury risk in Australia, using income data from the Household, Income and Labour Dynamics in Australia (HILDA) survey from 2010-2018, and risk data from Safe Work Australia. Their regression model estimates the compensating wage differential (CWD) controlling for industry and occupation, as well as for a range of demographic and labour force characteristics of the workers in the sample. In their preferred set of results:

...the CWD and corresponding VSL for fatal risk are 0.13% and $9.7 million respectively.

Interestingly, union members receive significantly higher compensation for fatality risk. In their preferred model, the CWD for union members is 0.44 percent for an increase in fatality risk of one in 100,000 workers, significantly higher than for non-members. If you need a good reason to join a union, this might provide it.

Surprisingly, Reynolds et al. find no evidence of a CWD for non-fatal risk overall. In fact, their preferred results suggest that higher non-fatal injury risk is associated with lower wages, rather than higher wages, for non-union workers. However, alongside that there is a significant CWD for union members, where:

...union members receive a CWD of 0.09% for a unit increase in injury risk from the mean level which corresponds to a VSI of $65,300.

VSI is the 'value of a statistical injury', which is the non-fatal equivalent of the VSL. One limitation of Reynolds et al.'s analysis is the potential for omitted variable bias. Their models include either fatal risk or non-fatal risk, but never both together. Since these risks are positively correlated, omitting one may bias upwards the estimated effect of the other. However, Reynolds et al. explain that including both risks would create multicollinearity problems, meaning that the results would potentially be less biased, but also less precise.

Finally, Reynolds et al. compare their results with the 'official' VSL applied by the Australian government, noting that:

For Australian workers who belong to a union, this estimate implies a VSL of $34.9 million. Ignoring union coverage results in a VSL of $9.7 million. These estimates are both well above the Australian government VSL estimate of $5.1 million...

For comparison, the New Zealand government currently applies a VSL of $12.5 million (in 2021 dollars, which is comparable with the 2021 VSL that Reynolds et al. report for Australia) for measuring the benefits of road safety improvements. This is equivalent to about AU$10 million at the current exchange rate.

The 'value of a preventable fatality' (or value of a statistical life, if you prefer) isn't a price tag on anyone's life, but an estimate based on how people trade off money against small changes in the risk of death. As Reynolds et al. demonstrate, those estimates can vary substantially, which is worth remembering when governments use a single number to represent the benefits of increased safety and in other applications.

Read more:

• The likely consequences of New Zealand's new value of a statistical life

How Alaska is like South Waikato

I've written a couple of times about the challenges that South Waikato faces in attracting workers (see here and here). This problem is not unique to South Waikato - a lot of rural and remote areas face the same challenges. In just the latest example I've seen, Jordan McGillis reports in City Journal on the situation in Alaska:

My analysis of Census data finds that more than 40 percent of civilian, prime-age, noncollege Alaska men employed in blue-collar occupations earn at least $75,000. More strikingly, 9.4 percent of Alaska’s civilian, prime-age, noncollege men work a blue-collar job and earn at least $100,000, compared with 3.6 percent nationally, ranking Alaska first in the country. Among those in such occupations more than one in four earns six figures...

That’s no surprise to [Ray Weber, Dean of technical and vocational education at the University of Alaska Anchorage]. “Can [wages in Alaska] be higher [than in the rest of the country]? Yes, especially Slope jobs or jobs that suck. Like, we have electrical linemen that go across the state. They’re going to Unalakleet, the only way to get there is by airplane. And there’s one pizza joint. One. No other restaurant. You generally end up sleeping either in a bunkhouse, if you’re lucky. Or you’re sleeping in the school auditorium. . . . I like Alaska, but we’re asking the wrong questions if you’re saying, ‘high-paying, lucrative jobs.’ What do the younger generation consider important? The answer is: Things that are not in Alaska.”

Economists call this a compensating wage differential: the premium required to induce workers to accept jobs with undesirable nonpecuniary characteristics. Work in Alaska is colder, darker, lonelier, and often more dangerous. The roughly $120,000 premium earned by North Slope oil-and-gas workers over their counterparts elsewhere, and the roughly $40,000 premium earned by electricians deploying to isolated communities such as Unalakleet, are partly the price employers must pay to fill jobs few want.

Workers with the same skills can often accept lower wages in Texas or Louisiana in exchange for a more attractive lifestyle.

Wages differ for the same job in different firms or locations. Consider the same job in two different locations. If the job in the first location has positive non-monetary characteristics (e.g. it is in an area that has high amenity value, where people like to live), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, if the job in the second location (Alaska, for example) has negative non-monetary characteristics (e.g. it is in an area with lower amenity value, where fewer people like to live, where it is cold, dark, lonely, and more dangerous), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. As McGillis notes, the difference in wages between the attractive job that lots of people want to do and the unattractive job that fewer people want to do is called a compensating differential. The compensating differential essentially compensates workers for working in jobs with negative non-monetary characteristics compared with working in jobs with positive non-monetary characteristics.

And so, jobs that pay less in the rest of the US must pay much more in Alaska in order to attract workers.

Read more:

• Reason to be wary if a job in Taumarunui offers an Auckland salary
• The compensating differential for rural GPs must be enormous
• Compensating differentials are alive and well in Tokoroa
• Rural Australia sets a new high bar for compensating differentials
• The $300,000 job that no one wants
• The South Waikato compensating differential strikes again

Sometimes people intuitively understand compensating differentials

Today my ECONS102 class covered compensating differentials, in a topic on the labour market. A compensating differential explains why jobs that are otherwise similar might have different equilibrium wages. For example: consider two jobs that are similar in terms of skill requirements. If one of the jobs has positive non-monetary characteristics (e.g. it is safe, clean, and engaging), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, if the other job has negative non-monetary characteristics (e.g. it is dangerous, dirty, and boring), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. The difference in wages between the attractive job that lots of people want to do and the unattractive job that fewer people want to do is called a compensating differential. The compensating differential essentially compensates workers for working in jobs with negative non-monetary characteristics compared with working in jobs with positive non-monetary characteristics.

Compensating differentials don't only apply to labour markets. As one example in a rental market, see this post. Another interesting example comes from this article in The Conversation last year by Andrew Vonasch (University of Canterbury):

If you’re offered a free cookie, you might say yes. But if you’re paid to eat a free cookie, would your response be the same?

In our new research, twice as many people were willing to eat a cookie when they weren’t offered payment compared with when they were...

Research participants who were offered a free cookie plus payment thought maybe the cookies were poisoned. Or maybe someone spat on them. Or they expected they would then owe a favour to the person handing out the treats once the cookie was eaten.

Vonasch claims that their research results reveal that the research participants were making irrational economic decisions, or that "people aren’t purely economic". However, that need not be true. A rational decision-maker who intuitively understands compensating differentials might respond in exactly the same way as Vonasch's research participants.

To see why, consider the choice that the research participants were offered. Eating a cookie is an enjoyable experience for most of us most of the time. Most of us wouldn't need to be paid to eat a cookie. So, if someone offers you a cookie and offers to pay you to eat it, it is natural to wonder what negative unobservable characteristics the payment is supposed to overcome. If there wasn't anything wrong with the cookie, why would they need to pay you to eat it? That is quite a rational response to the offer.

I often apply the same approach to thinking about salary offers in jobs (for example, see here). If a job is offering a much higher salary than other similar jobs, my first thought is always: what are the negative non-monetary characteristics that the extra salary is trying to compensate for? After all, who wants to live in South Waikato? Or rural Australia?

Compensating differentials are one of my favourite concepts in economics (and that's why there are so many regular posts on this blog about them). Interestingly, it appears that research participants who are offered payment to eat cookies understand them, even if they don't realise it!

The South Waikato compensating differential strikes again

The New Zealand Herald reported last month:

Robbie Winterson says he faces a battle every time he tries to hire new plumbers in his business.

He runs Go Fox Plumbing and Electrical in Putāruru in the South Waikato. When he puts a job ad on Seek or Trade Me, he says, he either gets no New Zealand applicants at all, or only people completely unsuitable for the job.

“We don’t get good-quality applicants at all. You just don’t get people applying.”

Winterson said plumbers would be paid more than electricians and his firm paid the same as they would get in Auckland, but it was still hard to hire.

The problem here is that Go Fox Plumbing is only offering to pay the same as plumbers would receive working in Auckland. To get quality applicants, they might have to offer more. They face essentially the same problem as South Waikato District Council looking for a health and safety manager in 2018, or a Tokoroa GP looking for a doctor in 2016. In all cases, despite offering what they thought was a competitive wage (compared with elsewhere), the employer was unable to attract good people for the role. 

Aside from difficulty in recruiting, there is one common thread there, and that's the location: South Waikato. Before we talk about why that's relevant (and potentially throw some shade on South Waikato), we need to review a bit of theory on compensating differentials.

Wages differ for the same job in different firms or locations. Consider the same job in two different locations. If the job in the first location has positive non-monetary characteristics (e.g. it is in an area that has high amenity value, where people like to live), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, if the job in the second area has negative non-monetary characteristics (e.g. it is in an area with lower amenity value, where fewer people like to live), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. The difference in wages between the attractive job that lots of people want to do and the unattractive job that fewer people want to do is called a compensating differential. The compensating differential essentially compensates workers for working in jobs with negative non-monetary characteristics compared with working in jobs with positive non-monetary characteristics.

Now, if South Waikato employers (the council, or a GP, or a plumber) are all offering 'competitive' wages and unable to find quality workers, then that suggests that they are not offering wages that are high enough to compensate for the non-monetary characteristics of the job. If they have to offer a wage that is even higher than workers would receive in other locations, that suggests that there is a compensating differential at play. For some reason, it appears that workers perceive that working in South Waikato comes with negative non-monetary characteristics relative to other areas, and are unwilling to move and work there at the wages that are being offered.

Workers' perceptions have an important implication for South Waikato employers. If they want to attract quality applicants, then South Waikato employers either need to find some way to convince potential workers that there are positive reasons for living in South Waikato (South Waikato District Council is clearly trying their best), or they need to pay more to offset the perceived negative characteristics of living in South Waikato.

Read more:

• Reason to be wary if a job in Taumarunui offers an Auckland salary
• The compensating differential for rural GPs must be enormous
• Compensating differentials are alive and well in Tokoroa
• Rural Australia sets a new high bar for compensating differentials
• The $300,000 job that no one wants

How meaningful jobs may contribute to the gender wage gap

Earlier this month, Dave Heatley wrote a great post on the NZAE's Asymmetric Information Substack about people working in jobs they are passionate about:

“Follow your passion”. That’s pretty much the universal career advice nowadays. But it comes with a rarely voiced kicker — if you choose a career in which passion-fueled supply exceeds demand, then don’t expect to be well paid.

I’ve seen this play out for my friends and family members who’ve chosen a career in conservation management. Job openings are scarce, highly contested, and get filled by passionate people who, on paper, are overqualified for the role.

This works to the advantage of employers — their employees are better qualified and their wages bill is lower than it would be otherwise. And lower wages have a further benefit from the employer’s perspective — they tend to screen out people without passion for the cause. That can benefit employees too, as they are pretty much guaranteed to work alongside other passionate people. It’s a win-win all round, at least until some employees decide they really would like to own a house, raise kids, or pursue other goals that require a more “normal” income.

Why do people get paid less in jobs that they are passionate about? I put this down to compensating differentials. Jobs have both monetary and non-monetary characteristics. Monetary characteristics include the pay and other monetary benefits. Non-monetary characteristics include the whole range of other things associated with the job. Perhaps it is dirty, dangerous, or boring. Or perhaps it is clean, safe, or fun. When a job has attractive non-monetary characteristics, then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, when a job has negative non-monetary characteristics, then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. It is the difference in wages between jobs with attractive non-monetary characteristics and jobs with negative non-monetary characteristics that we refer to as a compensating differential (essentially, workers are being compensated for taking on jobs with negative non-monetary characteristics, through higher wages).

The passion that a worker can express through their job is a non-monetary characteristic. If a job is one that people are passionate about, then more people will want to do the job (holding other job characteristics constant), and wages will consequently be lower. Another way of thinking about it is that employers of workers who offer jobs to people who are passionate about them don't have to compete hard to attract workers, and so they don't have to offer as high a wage to fill the job. Either way, jobs that attract people with passion pay less because of compensating differentials.

Interestingly, one aspect that Heatley doesn't explore in his post is the types of people who do tend to choose jobs that they are passionate about. That's what Alice Evans did in this post the same week. She mostly writes about this article published recently in the journal American Economic Review (ungated earlier version here). After summarising the article, Evans notes that:

Burbano, Padilla, and Meier's careful study offers valuable insights into women's career preferences, revealing that income maximisation isn’t always the primary goal...

Women seem drawn to meaningful, socially responsible roles, but these often come with a financial penalty.

If women are more drawn to jobs that are meaningful, and more drawn to jobs that they are passionate about (and I'm going to use those two descriptors interchangeably), then this will drive a gender wage gap due to the compensating differential between jobs that attract people with passion and those that don't. On average the types of jobs that women prefer are more meaningful and therefore they are also jobs that pay less.

This seems like it would be a difficult problem to fix. If the government tries to legislate that meaningful jobs must pay the same as jobs that don't attract people with passion, then the meaningful jobs will become even more attractive, meaning even more workers try to get into those jobs, and the supply of workers in those jobs is even higher, and that has an even larger negative impact on wages. And because there are fewer workers wanting the jobs that don't attract people with passion, the supply of labour for those jobs will decrease and the wages for those jobs will increase even further. Or, because the number of meaningful jobs is finite, it would simply result in a larger number of unemployed and disappointed workers who can't get the meaningful job.

Evans' solution instead is to change the 'vibes' associated with working in different industries - her post is looking at industries rather than particular jobs, but the principle is essentially the same. That would involve making people (young women, especially) passionate about the jobs that they are currently not passionate about. That doesn't sound easy either, but is certain to be a more sustainable solution in the long term.

Read more:

• Meaningful jobs and compensating differentials

If a salary seems too good to be true, it's probably a compensating differential

The New Zealand Herald reported last week:

It’s not often you get a chance to relocate to a coastal town with a beautiful white sand beach along with a whopping pay rise.

But that’s exactly what is on offer, and it’s right on Kiwis’ doorstep - sort of.

Western Australian beachside community Bremer Bay is offering one lucky person an eye-watering $300,000 to $450,000 wage, a rent-free five-bedroom home and a car if they relocate to their remote town.

So what does the job entail?

Bremer Bay, located on the south coast between Albany and Esperance, is in desperate need a new general practitioner (GP).

According to Indeed, the average Australian GP earns an annual salary of $233,304.

As I've noted before, when a job offers a pay package that is far higher than elsewhere, you ought to be thinking: what's wrong with this job? There must be something about the job that means the employer has to pay a much higher salary in order to attract people to work there.

Wages differ for the same job in different firms or locations. Consider the same job in two different locations. If the job in the first location has attractive non-monetary characteristics (e.g. it is in an area that has high amenity value, where people like to live), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, if the job in the second area has negative non-monetary characteristics (e.g. it is in an area with lower amenity value, where fewer people like to live), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. The difference in wages between the attractive job that lots of people want to do and the unattractive job that fewer people want to do is called a compensating differential.

Is the high salary on offer for a GP in Bremer Bay a compensating differential? Consider this:

Bremer Bay is a five-and-a-half hour drive from Perth and as of 2021 had a population of just over 200.

Over the past 10 years, the beachside town’s population has swelled as high as 6500 people during the Christmas and holiday periods.

The successful applicant will be the only GP in a rural community that's a long way from urban amenities (that might be a positive aspect for some people, but negative for many). However, being the only GP for 6500 people during summer has to be a strong downside. A beachside job sounds great, but if you spend your summer working flat out instead of enjoying the sun, that kind of destroys the positive aspect of it. And that is probably why the town is having trouble attracting anyone for this position, and why they have to offer such a high salary.

Read more:

• Reason to be wary if a job in Taumarunui offers an Auckland salary
• The compensating differential for rural GPs must be enormous
• Compensating differentials are alive and well in Tokoroa
• Rural Australia sets a new high bar for compensating differentials
• The $300,000 job that no one wants

Willingness-to-pay for working from home

Jobs come with both monetary and non-monetary characteristics. The monetary characteristics include the salary or wage (obviously) and other monetary benefits. The non-monetary characteristics include how pleasant or unpleasant the job is, how clean or dirty, and how safe or risky. An important non-monetary characteristic of jobs that has become particularly important since the pandemic is the flexibility to work from home. However, it isn't clear whether working from home is a positive or negative characteristic. Many people prefer to work from home, but many others don't. Incidentally, I'm in the latter group, because we only have a small house, and working from home entails working at the dining room table.

Now, non-monetary characteristics of jobs can give rise to wage differences between jobs - what economists refer to as compensating differentials. Jobs with desirable non-monetary characteristics tend to have lower wages than jobs with undesirable monetary characteristics (for an extreme example, see here). One way of explaining this is that many fewer workers want to work in jobs that have undesirable characteristics, and that lower supply of labour leads to higher wages. In other words, workers are essentially compensated for taking on jobs with undesirable non-monetary characteristics.

What does a compensating differential look like for working from home? I wrote about this last year, but the research I referred to there didn't look specifically at compensating differentials. In contrast, this new article by Akshay Vij (University of South Australia) and co-authors, published in the Journal of Economic Behavior and Organization (open access, with non-technical summary on The Conversation), does. They use data from a survey of 1113 employees conducted in Australia in 2020-21, where:

Respondents with an on-site job that had some ability to be done remotely were presented with multiple stated preference experiments where they were offered a choice between job arrangements with different salaries, and differing degrees of flexibility with regards to when and where job tasks needed to be performed... Each respondent was shown 8 scenarios, and the job attributes were varied systematically across scenarios...

This is what economists refer to as a discrete choice experiment, since research participants are asked to make a discrete choice among alternatives, which have different characteristics. Since each research participant makes many such choices, that data can be used to extract the marginal willingness-to-pay for each of the characteristics. In this case, the characteristics included the 'flexibility to work remotely on some days', and the 'flexibility to work remotely at some hours'. So, this research essentially worked out how much workers were willing to pay (that is, how much salary or wage they were willing to give up) in order to have the ability to work remotely.

Vij et al. then used a latent class model to identify four different groups of research participants based on their different responses, as shown in Table 2 from the paper:

Each class represents a roughly equal share of the sample of research participants. However, only two of the groups (Class III and Class IV) value the ability to work remotely some of the time. Vij et al. summarise the results as:

Across our sample, the average worker is willing to forego roughly AUD$3000 - AUD$6000 in annual wages to have the ability to work remotely some workdays and/or workhours. Given that the average respondent in our sample earns roughly $73,000 in annual wages, this implies a compensating wage differential of 4 – 8 per cent. However, median values are lower at AUD$1000 - AUD$1800, or roughly 2 per cent of average annual wage, due to considerable heterogeneity across the four classes. Classes 1 and 2 together comprise 54.3 per cent of the sample population, and do not have a statistically significant preference for either the ability to work remotely some workdays and/or workhours, and therefore have a corresponding wage differential of $0. Class 3 is willing to forego roughly 3 - 5 per cent of average annual wages (AUD$2000 - AUD$4000) to have the ability to work remotely some workdays and/or workhours, and Class 4 is willing to forego 16 – 33 per cent (AUD$12,000 - AUD$24,000) for the same.

Interestingly, the different classes differ on their beliefs about remote work, and Vij et al. note that:

...we observe that Class 1 is less optimistic than the other classes about the quality and quantity of work that can be done remotely, explaining their lower marginal willingness to pay for the ability to work remotely, and Class 4 is most optimistic, explaining their higher marginal willingness to pay...

Next, we compare responses to attitudinal indicators measuring impacts on human relations. Here, Class 2 has significantly greater concerns than the other classes, explaining their lower marginal willingness to pay for the ability to work remotely. In particular, workers belonging to Class 2 are more concerned on average about the negative impacts on their relationships with their colleagues, supervisors and the firm as a whole, as well as opportunities for learning and career advancement.

When you think about the types of jobs that each class predominantly engages in (from Table 2 above), this makes a lot of sense. Class 1 is mostly clerical and administrative workers, but Class 2 is mostly managerial workers, and the latter probably rely more on interpersonal relationships in their work that would be negatively impacts by remote work. In contrast, Class 3 and 4 workers are mostly professional workers, likely to be more self-directed and in some cases fairly autonomous.

However, in light of recent increases in remote work, this was interesting:

Interestingly, in terms of experience with remote working, individuals belonging to Class 2 were more likely to have had greater experience with remote working arrangements prior to the pandemic than other classes...

And yet, those workers had a zero compensating differential for remote work. That is, they didn't value working from home. The survey was conducted in 2020/21, when many of us were experiencing large-scale remote work for the first time. As other workers gain more experience with remote work, I wonder whether the Class 3 and Class 4 workers will be as positively inclined towards remote work in the future. This is something that deserves further investigation.

Finally, in terms of demographics, there was little difference between the classes, although:

...we find that women are most likely to belong to Class 4, and have a significantly higher valuation for remote working. This is consistent with previous studies that have found that women value job flexibility more than men, due to greater caregiving and other responsibilities...

This has interesting implications for the gender wage gap. Since women are more likely to choose flexible work arrangements, and are willing to pay (through lower wages) for the flexibility that remote work provides, should a zero gender wage gap be the appropriate goal, or a zero gap accounting for differences in flexible work arrangements? Again, this is something that deserves further consideration.

Remote work isn't going away any time soon. Some of us might think that the flexibility is a good thing for all workers, but it is clear that not all workers themselves feel that way.

Read more:

• Remote work, wages, and compensating differentials

What workers are willing to pay for jobs at safer times of the day

Not all jobs pay the same. Some jobs are pleasant, fun, and/or clean. Other jobs are unpleasant, boring, and/or dirty. Because more people want to do the pleasant, fun, and clean jobs, the wages for those jobs tend to be lower (holding other characteristics of jobs the same). And because fewer people want to do the unpleasant, boring, and dirty jobs, the wages for those jobs tend to be higher (holding other characteristics of jobs the same). This is an explanation of what economists call compensating differentials. Jobs with desirable non-monetary characteristics tend to have lower wages than jobs with undesirable monetary characteristics. Workers are essentially compensated for taking on jobs with undesirable non-monetary characteristics.

One of the important non-monetary characteristics of a job is how safe or risky the job is. Jobs that are risky tend to pay more than jobs that are safe. Usually, economists think about this in terms of how safe or risky the job itself is. However, the same theory should apply to jobs in risky locations, compared with jobs in safer locations, or to jobs at risky times of the day, compared with jobs at safer times of the day.

How much are workers willing to sacrifice to work at a safer time of the day? That is the question that was addressed in this recent article by Oscar Becerra and José-Alberto Guerra (both Universidad de los Andes), published in the Journal of Economic Behavior and Organization (sorry, I don't see an ungated version online). They used an experimental approach, where they offered:

...participants a one-hour job and elicit individual preferences about alternative arrangements affecting the job’s safety perception by exploiting the time of the day (early versus late shift) and location (online versus on-site). In the first round, we offer students to participate in a second round in which they must perform an unspecified simple task at the university campus, which is located in a neighborhood generally perceived as more unsafe than most of the city. Participants are then allowed to choose between an early shift (9–10 a.m.) and a late shift (8–9 p.m.), given a compensation schedule of 11 fixed payments. We told participants, without deception, that we would invite them for this future one-time job under the proposed payment scheme. Based on their choices, we recover a measure of the willingness to pay for the early on-site shift. In the second round, a subsample of subjects from the first round faced a similar setting but now the future task could be completed remotely, which removes safety concerns related to the workplace’s neighborhood and commute. 

The research participants were all students at Universidad de los Andes in Colombia. Becerra and Guerra document that there are negative perceptions of safety around the university campus at night, and then based on their experiment they find that:

...safety concerns about the late shift on campus and gender differences (beyond those in safety concerns) are the main determinants of willingness to pay for the early on-site shift. The unconditional difference in willingness to pay between individuals who consider the late shift as riskier than the early shift is 3,721 Colombian Pesos (COP) –about USD 2.8 PPP and 11%–15% of the baseline payment. Similarly, we also find an unconditional gender gap in willingness to pay for the early on-site shift of 2,843 Colombian Pesos (COP) –USD 2.1 PPP and 8%–11% of the baseline payment. Using regression analysis, controlling for safety concerns reduces the gender gap by 20%.

So, workers are willing to sacrifice a relatively large proportion of pay in order to work in a job at a safer time of the day. Workers who feel less safe are willing to sacrifice more if they have high safety concerns, and women are willing to sacrifice more than men (even accounting for women having higher safety concerns than men). Becerra and Guerra then go on to show that there is likely to be external validity for their results, because based on administrative data from the university:

...students whose willingness to pay for the safer shift is larger than the median participant were more likely to exit University premises before 5 p.m., and they were also less likely to enroll in courses with lectures occurring after that time.

In other words, the experimental results were consistent with actual behaviour, in relation to being on campus in the evenings. So, as expected it appears that workers are willing to pay (11-15 percent of their wage) for jobs at safer times of the day. That means that there should be a substantial compensating differential for jobs that require working at unsafe times.

The gender difference in willingness-to-pay for working at safer times of the day has interesting implications. It means that, given a particular wage on offer, women are less likely to accept a job at an unsafe time (like evening or night work), so we should expect to see more men than women working at those times. It also means that women would be willing to accept a lower wage for working at safer times of the day than men do, since women are willing to give up more wages to work at those times than men. This could be an unrecognised contributor to the gender wage gap in locations where personal safety is generally low (or where risks are particularly high at certain times of the day). This is definitely something that is worth further exploring in other settings.

The compensating differential for university professors

I love my job. I honestly have the best job in the world [*]. Now, there is a serious problem inherent in those statements. It isn't that we shouldn't love our jobs. Every one of us deserves to do a job that we love. The problem is that, when we do a job that we love, we are willing to do so for a much lower wage than we could earn in a job that we didn't love nearly as much.

This is what economists refer to as a compensating differential. Consider two jobs that are similar in almost all ways, except that one job has some attractive non-monetary characteristics (e.g. it is a job that is pleasant, fun, and/or clean), while the other job has unattractive non-monetary characteristics (e.g. it is a job that is unpleasant, boring, and/or dirty). More people will be willing to do the first job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, fewer people will be willing to do the second job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. The difference in wages between the attractive job that lots of people want to do and the unattractive job that fewer people want to do is the compensating differential.

Is there a compensating differential for university professors? According to this 2018 article by Daniel Hamermesh (Barnard College), published in the journal Economics of Education Review (ungated earlier version here), there is, and it is substantial. Using data from the American Community Survey for 2012-2016, and comparing workers with doctorates working in academia with workers with doctorates working in other occupations, Hamermesh finds that:

Comparing pay differences at various quantiles of the distributions, near the bottom of the pay distributions academics earn more than other doctorate-holders; but the differences rise steadily as we move up the earnings distributions, with academics’ pay beginning to fall below that of other doctorate-holders at the 17th percentiles of the distributions. At the 25th percentiles of the distributions the earnings advantage has turned into a disadvantage of 6%; at the medians it is 19%; and it rises to an astounding 50% disadvantage at the 95th percentiles. At the means academics receive 24% lower pay than non-academic doctorate-holders...

University professors get paid less than doctorate-holders in other occupations. The mean difference is US$29,802 (US$121,704 vs. US$91,902), and the difference at the 95th percentile is a staggering $196,594 (US$394,058 vs. US$197,464). Controlling for various demographics, the mean difference in pay is 17 percent.

This suggests an incredibly large compensating differential for being a university professor. What explains it? Hamermesh looks at the flexibility of work timing using a simple utility model calibrated to data from the American Time Use Survey, and concludes that:

Under what seem like reasonable assumptions about utility a not tiny, but also not huge part of the earnings differential can be explained by the more equal distribution of leisure across days of the week that academics enjoy.

To be more specific, time flexibility can explain no more than a quarter of the difference in pay between university professors and other doctorate-holders. Hamermesh then looks at data from a survey of 288 academic economists, which asked which aspects of their job contributes most to their enjoyment of being a professor. The survey results show that:

Freedom and novelty of research, and the satisfaction of working with young minds, are by far the most important attractions of academe, listed by 88 and 74% of survey respondents respectively. Only 36% of respondents listed time flexibility as a top-three attraction, slightly fewer than listed enjoying intellectual and social interactions with colleagues.

University professors are poorly paid compared to workers with doctorates in other occupations. The compensating differential here appears to capture how much professors value the freedom and novelty of doing their own research, and the thrill and inspiration that comes from working with students. I totally buy into that argument. I love my job.

****

[*] Important note to my employer: Nothing in this post should be taken as an indication that I don't deserve to be paid way more than my current salary.

Is there not a compensating differential for having a naked landlord?

The New Zealand Herald reported earlier this week:

A landlord sunbathing naked in the courtyard of his building was no reason for one of his tenants to withhold its rental payments, a German court has ruled.

The case involved a building in an upmarket district of Frankfurt, which included an office floor, rented by a human resources company. The company withheld rent because it objected, among other things, to the landlord’s naked sunbathing. In response, the landlord sued.

The Frankfurt state court rejected the company’s reasoning, finding that “the usability of the rented property was not impaired by the plaintiff sunning himself naked in the courtyard”.

It said in a statement that it could not see an “inadmissible, deliberately improper effect on the property”.

In labour markets, economists refer to the idea of a compensating differential. This recognises that jobs with different non-monetary characteristics will have different equilibrium wages. Jobs with desirable characteristics will attract more workers (higher labour supply) and have lower wages. Jobs with undesirable characteristics will attract fewer workers (lower labour supply) and have higher wages. The difference in wages between otherwise identical jobs, based on their non-monetary characteristics, is a compensating differential.

Should there be a compensating differential for having a naked landlord? Unless your landlord is Henry Cavill, it is likely that having your landlord sunbathing naked around your building is likely to be an undesirable characteristic of your apartment. [*] The rent should be lower for the tenants of a naked-sunbathing landlord, to compensate them for that negative non-monetary characteristic.

However, having said that, it shouldn't be up to the courts to enforce a lower rent (by allowing a tenant to withhold rent payments). A landlord with a penchant for naked sunbathing would probably find that they have to find new tenants more often than other landlords, necessitating a costly search process (and an empty apartment in the meantime). That would lead the average rent from the apartment to reduce. So, unfortunately, unless a tenant can negotiate with the landlord about the rent (and given the experience of the tenant noted in the article, that seems unlikely), the compensating differential likely only affects the landlord, and not the tenants.

If the landlord is willing to receive a lower rent on average, then it appears that they can sunbathe naked with impunity.

*****

[*] For the tenants of a naked-sunbathing Henry Cavill, this would probably be a desirable characteristic. Their rent would likely be higher as a result.

The $300,000 job that no one wants

Every time I see a story like this in the news, my first thought is compensating differentials. The New Zealand Herald reported yesterday:

A Perth mining company has been forced to look for workers from New Zealand after Aussies continually turned down a $300,000 job.

Mineral Resources has launched an advertising campaign targeting Kiwi tradies, guaranteeing “a great pay packet”, News Hub reported.

“We’re offering plenty,” Mineral Resources CEO Mike Grey told NZ programme AM.

“The incentives are amazing, and I have no doubt that our salaries double [New Zealand salaries], in some examples, they triple.”

The old adage that when something seems too good to be true, it usually is, applies. When a job is offering a pay package that is far higher than comparable work elsewhere, you should be asking, what is wrong with that job? There must be something about the job that means the employer has to pay a much higher salary in order to attract people to work there.

Wages differ for the same job in different firms or locations. Consider the same job in two different locations. If the job in the first location has attractive non-monetary characteristics (e.g. it is in an area that has high amenity value, where people like to live), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, if the job in the second area has negative non-monetary characteristics (e.g. it is in an area with lower amenity value, where fewer people like to live), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. The difference in wages between the attractive job that lots of people want to do and the dangerous unattractive job that fewer people want to do is called a compensating differential.

Is the $300,000 salary for working in the Australian mines a compensating differential? It seems so:

Despite the high incomes and generous incentives, mining might not be the ideal career for everyone.

One of the downsides to the job is at least two-week blocks of work in isolated areas with sometimes basic living conditions.

The 12-hour shifts often involve heavy physical labour in a high-pressure environment where mistakes can cost a company millions and so result in instant redundancy, meaning a high turnover rate of staff.

The high salary is compensation for the negative non-monetary characteristics of the job. The worst negative characteristic (for most people) would be spending long periods of time in a remote location, far from nice amenities. The premium that the mining companies are offering isn't enough to entice Australians to work there. Australian wages are higher than New Zealand wages, so the pay premium is larger for a New Zealander working in the mines than for an Australian. By advertising in New Zealand, the mining companies are hoping to take advantage of that. Of course, remote Australia is even more remote from New Zealand than it is from the rest of Australia. Maybe they'll just have to offer to pay even more?

Read more:

• Reason to be wary if a job in Taumarunui offers an Auckland salary
• The compensating differential for rural GPs must be enormous
• Compensating differentials are alive and well in Tokoroa
• Rural Australia sets a new high bar for compensating differentials

Rural Australia sets a new high bar for compensating differentials

The New Zealand Herald reported last week:

More than A$500,000 ($553,000) and a free house haven’t been enough to attract a doctor to a small town in rural far-north Queensland, leaving residents forced to drive two hours to receive treatment.

McKinlay Shire Council in Julia Creek - 600 kilometres west of Townsville - has offered an enviable package for a GP looking for a career change in their tight-knit community.

The job includes a salary of up to A$513,620 and a rent-free house on a decent-sized block of land, but no doctors have taken up the call yet.

As I've noted before (see here and here), the job of rural doctor appears to subject to a very large and persistent compensating differential. What does that mean?

Wages differ for the same job in different firms or locations (such as the difference between a rural GP and an urban GP). Consider the same job in two different locations. If the job in the first location has attractive non-monetary characteristics (e.g. it is in an area that has high amenity value, where people like to live), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, if the job in the second area has negative non-monetary characteristics (e.g. it is in an area with lower amenity value, where fewer people like to live), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. The difference in wages between the attractive job that lots of people want to do and the dangerous job that fewer people want to do is called a compensating differential.

Living and working in a remote rural area might seem idyllic to some people. However, what you gain in rural lifestyle amenity is offset by the loss of urban amenity. Given that compensating differentials for rural doctor jobs appear to be so pervasive, is clear that doctors on the whole perceive the loss of urban amenity to more than offset the gain in amenity from the rural lifestyle. That's why these rural doctor jobs have to pay so much in order to attract doctors willing to do them.

Read more:

• Reason to be wary if a job in Taumarunui offers an Auckland salary
• The compensating differential for rural GPs must be enormous
• Compensating differentials are alive and well in Tokoroa

Remote work, wages, and compensating differentials

The labour market has undergone a massive upheaval since the pandemic, with the sudden shift to remote work, which has persisted even as the pandemic's effects wane. Or rather, some but not all sectors of the labour market have seen a sudden shift to remote work - I am yet to see a remote barista, for instance. Why has remote work persisted (in some sectors)? Clearly, this only happens if both workers and employers benefit. That is part of the premise of this new NBER Working Paper (ungated version here) by Jose Maria Barrero (Instituto Tecnologico Autonomo de Mexico) and co-authors.

Barrero et al. are focused on the effect of remote work on wage pressures. However, I think there is a more interesting story that sits alongside it, in relation to compensating wage differentials. Barrero et al. note that:

In equilibrium, workers and employers share the amenity-value gains arising from the shift to remote work. Since workers reap the direct benefits of the shift at any given wage, employer benefits take the form of wage-growth restraint during the transition to a new equilibrium with compensation packages that reflect the greater amenity value of higher remote work levels...The Nash bargaining benchmark, for example, says employers get half the surplus created by the rise of remote work.

This relates closely to search models of the labour market, where the surplus generated from a successful match between an employer and a worker is shared between both parties. The shares of the surplus that employer and worker receive depend on their relative bargaining power. In this case, remote work generates an additional surplus, which is shared between employer and worker. That additional surplus may arise from higher productivity of the worker at home, or from the worker spending more hours working (because they spend fewer hours commuting), or because the employer has to spend less on the work environment (because fewer employees are there on any given day, which this earlier post notes has also had an effect on the market for office real estate). How is this additional surplus shared? The additional value of production (or cost savings) are only partially passed onto the worker by the employer. The employer keeps a share for themselves.

This means that, although wages go up, they don't go up by as much as the additional value that is generated. This relates to the idea of a compensating differential, because workers are happy to accept a lower wage (or a lower increase in wages) when their job has positive non-monetary characteristics. To the extent that working from home is a positive non-monetary characteristic, workers would therefore accept a lower wage if their job includes more working from home.

And that is essentially what Barrero et al. find, using data from the Survey of Business Uncertainty (SBU) in April and May 2022. Specifically, they asked:

...each business executive in the SBU the following question: “Over the past 12 months, has your firm expanded the opportunities to work from home (or other remote locations) as a way to keep employees happy and to moderate wage-growth pressures?” According to the responses, 38 percent of firms did so in the previous 12 months... larger firms and firms in... Education, Healthcare & Social Assistance or in FIRE, Professional & Business Services, and Information are more likely to moderate wage-growth pressures by expanding remote work opportunities...

...we also ask: “Over the next 12 months, will your firm let employees work from home (or other remote locations) at least one day per week to restrain wage-growth pressures?” Forty-one percent of business executives respond “yes” to this question... the pattern of responses by firm size and across industry sectors to this forward-looking question is very similar to the response pattern for the backward-looking question. 

Notice that the sectors that report high degrees of remote work are those that you mostly would expect (although healthcare may be a bit of a surprise, but there are a lot of administrative staff in that sector, and some primary healthcare can be delivered remotely). Barrero then ask about how much the firms can (or have) restrained wage growth, and find that:

On a size-weighted basis, we estimate that expanded remote-work opportunities moderated overall wage-growth pressures by 0.9 (0.1) percentage points over the 12-month period ending in April/May 2022. Looking forward, we estimate that expanded remote-work opportunities will moderate wage-growth pressures by another 1.1 (0.1) percentage points in the 12 months following April/May 2022. These estimates have good precision, as indicated by the standard errors reported in parentheses.

Notice that remove work has reduced the extent to which firms are increasing wages (at least, as reported by the firms themselves). And by sector:

Over the two years centered on April/May 2022, the unweighted mean wage-growth moderation effect is 1.3 percentage points among Goods Producers and 1.4 points among firms in Trade, Transportation & Warehousing, and Leisure & Hospitality. These sectors offer relatively few jobs that can be readily performed in remote mode. In contrast, the mean wage-growth moderation effect over two years is 2.7 points in Education, Healthcare, Social Services and Other Services and 3.0 percentage points in FIRE, Professional & Business Services and Information. Except for Healthcare, these sectors have a relatively high share of jobs that can be performed in remote mode...

This provides some evidence that it is remote work driving the lower wage increases, since the effects are greatest in sectors where remote work has become more common. Finally:

We also draw out two other interesting implications of our evidence. First, we estimate that the amenity-value shock associated with the recent rise of remote work lowers labor’s share of national income by 1.1 percentage points. Second, we provide evidence that the “unexpected compression” in the wage distribution since early 2020 is partly explained by the same amenity-value shock, which operates differentially across the earnings distribution.

In other words, the shift to remote work and the compensating differential will have some interesting effects on the measurement of inequality. The labour share of income, which many people equate with a measure of inequality between workers and owners of capital, will decrease. However, because most remote work jobs are relatively high-earning jobs, their smaller wage increases relative to lower-earning non-remote-work jobs will tend to decrease measured income inequality.

No doubt some governments will pat themselves on the back if inequality appears to decrease. However, it's not really much of an improvement if income inequality is reducing, but only because the non-monetary job characteristics of those at the top of the income distribution are improving. This highlights one of the limitations of income inequality as a measure of differences in personal wellbeing.

However, that isn't the story that Barrera et al. are trying to tell in their paper. They conclude that:

...the recent rise of remote work materially lessens wage-growth pressures. In doing so, the rise of remote work eases the challenge confronting monetary policy makers in their efforts to bring the inflation rate down to acceptable levels without stalling economic growth.

I guess that may be some good news. To the extent that remote work persists, and to the extent that central bankers are paying attention, we might expect that interest rates may not have to increase as much in order to bring inflation back under control.

[HT: Marginal Revolution] 

COVID-19 risk and compensating differentials in a university setting

A compensating differential is the difference in the wage between a job with desirable non-monetary characteristics and a job with undesirable non-monetary characteristics, holding all other factors (like human capital or skill requirements, experience of the worker, etc.) constant. When a job has attractive non-monetary characteristics (e.g. it is clean, safe, or fun), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, when a job has negative non-monetary characteristics (e.g. it is dirty, dangerous, or boring), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. It is the difference in wages between jobs with attractive non-monetary characteristics and jobs with negative non-monetary characteristics that we refer to as a compensating differential (essentially, workers are being compensated for taking on jobs with negative non-monetary characteristics, through higher wages).

The current pandemic presents a situation where many jobs have suddenly had a new and negative non-monetary characteristic added to them - the risk of becoming infected with the coronavirus. The idea of compensating differentials suggests that workers who suddenly face a job that is riskier than before should receive an increase in wages (and indeed, we have seen that, such as the pay bonus that some supermarket workers have received).

There hasn't been much in the way of systematic research on the compensating differentials arising from the pandemic. No doubt we can expect some in the future. An early example is this new paper by Duha Altindag, Samuel Cole, and Alan Seals (all Auburn University). It turns out that Auburn University didn't strictly follow the CDC requirements for safe social distancing in class, leading to some classes having too many students, and therefore being higher risk. As Altindag et al. note:

Possibly due to the cost concerns, Auburn University did not implement any policy about maintaining six feet of distance between students within the classrooms... Instead, the university set an enrollment limit of half of the normal seating capacity in classrooms, despite the Center for Disease Control (CDC) guidelines and the public health orders of the state... This practice of the university led to about 50% of all face-to-face (F2F) courses in Spring 2021 being delivered in “risky” classrooms, in that the number of enrolled students in classes exceeded their classrooms’ CDC-prescribed safe capacity (the maximum number of students that can be seated in the room while allowing a six-foot distance between all students).

Altindag et al. looked at differences in which staff taught the risky (or 'very risky' - classes where the number of enrolled students was more than double the safe room capacity) classes, and then looked at differences in pay between those teaching risky classes and those teaching less risky classes. For the differences in pay, they are able to adopt an instrumental variables approach, using the presence of fixed furniture in the teaching room as an instrument. As they explain:

Our instrument, Dispersible Class, is an indicator for whether students in a classroom can spread away from each other while attending the lectures. This can only happen in in-person classes that take place in rooms with movable furniture or in online courses in which students have already spread away from one another.

I worry a little about the sensitivity of the results to the inclusion of fully online classes. By construction, the instrument (Dispersible Class) always takes a value of one for online classes, and the online classes are by definition non-risky, so the variation they are picking up is entirely driven by the riskiness of the face-to-face classes. That is what you want in this analysis, but why include the online classes in the analysis at all since they aren't contributing any variation?

Anyway, nit-picking aside, when Altindag et al. look at who teaches the risky classes, they find that:

...GTAs [Graduate Teaching Assistants] and adjunct instructors, who are ranked low within the University hierarchy, are about eight to ten percentage points more likely to teach a risky class compared to the tenured faculty (full and associate professors) and administrators (such as the department chairs, deans, and others) who teach courses in the same department...

...female instructors are more likely to be teaching risky classes. Additionally... younger faculty face higher risk in their classrooms.

The results are similar for 'very risky' classes. Young faculty and low-ranked faculty (and, possibly, female faculty) have less bargaining power with departmental chairs, so are more likely to acquiesce to a request to teach particular classes, and that is what Altindag et al. find. Those academics have consequently taken on more COVID-19 risk. But, are they compensated for this risk? In their instrumental variables analysis, Altindag et al. find that:

...instructors who teach at least one risky class earn 22.5 percent more than their counterparts who deliver only safe course sections... Relative to the average monthly wage of an instructor in our sample, this effect corresponds to approximately $2,100. In a four-month semester, this impact corresponds to $8,400.

Again, the results are similar for 'very risky' classes. So, even though junior faculty and female faculty take on more risky classes, they are compensated for that additional risk. Note that the estimates of the compensating differential control for the instructor's demographic characteristics, academic level, and experience at Auburn. Altindag et al. find that the compensating differential is roughly the same at all academic levels.

One other criticism is that perhaps the types of classes that junior faculty typically teach happen to be those that are riskier. Altindag et al. address this by running their analysis using data on classes from the previous year, when COVID-19 was not a thing. They find no statistically significant differences in who teaches 'hypothetically-riskier' classes, and no statistically significant wage premium for those teaching 'hypothetically-riskier' classes. That provides some confidence that the effects they pick up in their main analysis relate to risk in pandemic times.

This paper raises an interesting question. Faculty are compensated for coronavirus risk, through higher wages. However, it isn't only faculty who face higher risk. Students attending those classes are at higher risk as well. Is there a compensating differential for students, and if so, how would we measure it? That is a question for future research.

[HT: Marginal Revolution]

Read more:

• The compensating differential for being an academic

Meaningful jobs and compensating differentials

In The Conversation last week, Andrew Bryce (University of Sheffield) wrote about the meaningfulness of jobs. These bits in particular caught my eye:

Work provides many things over and above the monthly pay cheque: status and identity, community and social connection, doing tasks that we find stimulating, and the opportunity to make a positive contribution to society. All of these things make work feel meaningful.

My research explores how paid work is experienced as meaningful compared to the other activities people do in their everyday lives. I also identify the types of job in which people experience the most meaningfulness and explore how these results can be explained by the particular qualities of different occupations...

People in community and social service occupations (which includes social workers, counsellors and clergy) experience the most meaningfulness in their work.

The other top-ranking occupations are: healthcare practitioner and technical occupations; education, training and library occupations; and, perhaps surprisingly to some, legal occupations. More broadly, people working in the non-profit sector and self-employed people report significantly more meaningfulness in their work than those employed in private sector for-profit firms...

When work is meaningful, then that becomes a reward in itself and generous pay offers are not prioritised to motivate people and retain staff. In contrast, less meaningful work has no such intrinsic value, so a monetary reward is needed to get people to do these jobs.

This of course leads to the perverse situation where the most socially useful jobs are those that are paid the least. It may seem unfair but it’s the reality of how the labour market works.

It's the reality of how the labour market works because of compensating differentials. Jobs have both monetary and non-monetary characteristics. Monetary characteristics include the pay and other monetary benefits. Non-monetary characteristics include the whole range of other things associated with the job. Perhaps it is dirty, dangerous, or boring. Or perhaps it is clean, safe, or fun. When a job has attractive non-monetary characteristics, then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, when a job has negative non-monetary characteristics, then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. It is the difference in wages between jobs with attractive non-monetary characteristics and jobs with negative non-monetary characteristics that we refer to as a compensating differential (essentially, workers are being compensated for taking on jobs with negative non-monetary characteristics, through higher wages).

The meaningfulness of a job is a non-monetary characteristic. If a job is meaningful, then more people will want to do the job (holding other job characteristics constant), and wages will consequently be lower. Another way of thinking about it is that employers of workers who offer meaningful jobs don't have to compete hard to attract workers, and so they don't have to offer as high a wage to fill the job. Either way, meaningful jobs pay less because of compensating differentials.

Economists in schools of public affairs, and compensating differentials

New Zealand doesn't have any schools of public affairs, but they are a reasonably common feature of U.S. universities (Victoria University does have a School of Government, but I'm not sure that is quite the same). Economists in the U.S. are employed in both economics departments, and in schools of public affairs. You would think that they would be paid the same (conditional on their 'quality' as an academic) regardless of which school or department they are employed in. Not so, according to this 2019 working paper by Lori Taylor, Kalena Cortes, and Travis Hearn (all Texas A&M University).

They first compile salary and demographic data from 2152 academics employed in schools of public affairs, economics departments, or political science departments, from the 33 public universities with schools of public affairs ranked in the top 50 in the U.S. (the other 17 are private universities, where data on salaries are not readily available). Their data demonstrate three key facts:

First, leading schools of public affairs employ a large number of economists. The 33 leading public affairs departments in our sample employed more than 100 economists, or 12 percent of the economists in the sample.

Second, a disproportionate number of the economists employed by schools of public affairs were female... 19 percent of the faculty in departments of economics were female; whereas 23 percent of the economists in departments of political science were female and 35 percent of the economists in schools of public affairs were female...

Third, average salaries in schools of public affairs were lower than those in traditional economics departments. On average—and without adjustment for faculty rank or institution reporting differences—salaries were 33.5 percent higher in departments of economics than they were in schools of public affairs. Among economists, average salaries were 11 percent higher in departments of economics than they were in schools of public affairs.

Taylor et al. then go on to explore the differences in salaries between schools of public affairs and departments of economics (and political science) in a bit more detail. In particular, they are interested in whether, given that schools of public affairs employ more women, and there is a gender gap in salaries, the proportion of female faculty makes a difference. It turns out it doesn't, and they report that:

...we found a significant, negative differential for female faculty members, but controlling for gender did not eliminate the public affairs discount...

...female faculty members were paid significantly less than male faculty members regardless of discipline or department.

Interestingly, there was no difference arising from the seniority of faculty in the schools or departments either. However, then they go on to investigate measures of 'research productivity' (or quality) and find that:

...controlling for citation metrics as well as years since degree and faculty rank, we estimated that economists in schools of public affairs earned at least 28 percent more than otherwise similar faculty members, and economists in departments of economics earned 17 percent more than economists in schools of public affairs. On the other hand, political scientists were better paid in a school of public affairs than in a traditional department of political science, even after controlling for research productivity.

Including citation metrics (as a measure of research productivity) rendered the gender difference in salaries statistically insignificant, suggesting that the difference in salaries was capturing differences in research productivity. That is quite a different result from much of the earlier literature on this topic (for example, see my earlier post here).

This working paper seems a bit unfocused to me. It starts with the premise of comparing salaries between schools of public affairs and departments of economics, but quickly strays into evaluating the gender gap in salaries. The analysis and the exposition would be a lot clearer if they could distinguish those two aims. The finding that the gender gap is explained by differences in research productivity needs a bit more unpacking, especially given that it contradicts the previous literature.

However, the most interesting finding to me is the salary penalty for economists who work in schools of public affairs, and that the penalty remains statistically significant even after controlling for research productivity. Departments of economics have been labelled a toxic environment for women (for example, see my earlier post here). Could the public affairs salary penalty reflect a compensating differential? Are (female) economists willing to accept a reduction in salary in order to locate in a department that has a more welcoming environment (and in reverse, do they require a higher salary to compensate for the toxic working environment in a department of economics)? The public affairs salary penalty for economists was higher for women than men, and was statistically significant in some (but not all) of Taylor et al.'s results, after controlling for research productivity (see Table 4 in the working paper). That provides some further evidence that the salary penalty might be capturing a compensating differential that is more salient for women than for men.

On the face of it, the salary penalty for working in a school of public affairs would tend to suggest that economists should avoid working there. That probably holds true for male economists. However, if it reflects a positive compensating differential, which it probably does for women, then that changes the parameters of the decision and may favour jobs at the schools of public affairs. The problem with taking that interpretation though, is that it may 'lock in' the cultural differences between schools and departments that are the very source of the compensating differential. Food for thought.

[HT: Marginal Revolution, last year]

The compensating differential for being an academic

It seems obvious that wages differ between different occupations. There are many explanations for why, such as differences in productivity between workers in different occupations. However, there are also less obvious explanations. Or at least, explanations that are less obvious until you start to recognise them (after which, you start to see them everywhere). One such explanation is what economists refer to as compensating differentials.

Consider the same job in two different locations. If the job in the first location has attractive non-monetary characteristics (e.g. it is in an area that has high amenity value, where people like to live), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, if the job in the second area has negative non-monetary characteristics (e.g. it is in an area with lower amenity value, where fewer people like to live), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. The difference in wages between the attractive job that lots of people want to do and the dangerous job that fewer people want to do is the compensating differential.

So to summarise, jobs that have highly positive characteristics will have lower wages than otherwise identical jobs with less positive characteristics. Now let's consider a specific example. Academics in many fields could probably earn substantially more if they worked in the private sector, than what they earn as an academic. For some fields (like finance, economics, accounting, computer science, or engineering), the differential is much higher than others (like education or anthropology). Why don't academics simply shift en masse into the private sector? Is that partially a result of compensating differentials?

A NBER Working Paper from earlier this year (ungated version here) by Daniel Hamermesh (Barnard College, and author of the excellent book Beauty Pays: Why Attractive People are More Successful, which I reviewed here), goes some way towards addressing the latter question. Using data from the U.S. Current Population Survey for 2012-2016, Hamermesh finds that:

...the adjusted pay difference between professors and other advanced-degree-holders shows a disadvantage of about 13 percent.

In other words, holding other factors (like demographic and economic characteristics) constant, academics earn 13 percent less than holders of a PhD (or EdD) degree in other jobs. At the median (the middle of the wage distribution), the difference is 16 percent.

Many people argue that academics like their jobs because they have more flexible use of their time (or, as I have fallaciously heard, that we have a sweet job because we only have to work when students are on campus). Using data from the American Time Use Survey 2003-2015, Hamermesh finds that:

...professors do much more of their work on weekends than do other advanced-degree-holders, and they do less during weekdays. They put in nearly 50 percent more worktime on weekends than other highly-educated workers (and 50 percent more than less-educated workers too). Professors spread their work effort more evenly over the week than other advanced-degree-holders...

...the spreading of professors’ work time across the week can account for nearly five percentage points of the wage differential, i.e., almost one-third of the earnings difference at the median...

So, more flexibility in work schedules accounts for part of the difference, but not all. Hamermesh also supports this with the results from a survey of 289 academics who specialise in the study of labour markets (I guess this was Hamermesh surveying people he knew would respond to a survey from him!). The survey shows that:

[f]reedom and novelty of research, and the satisfaction of working with young minds, are by far the most important attractions into academe. Only 41 percent of respondents listed time flexibility as a top-three attraction, slightly fewer than listed enjoying intellectual and social interactions with colleagues.

Clearly there are a number of characteristics that make academia an attractive job proposition for well-educated people who could get a higher-paying job in the private sector. Academics are willing to give up some income (and in some cases substantial income) for those characteristics - what they are giving up is largely a compensating differential.

[HT: Marginal Revolution, back in January]

Return migrants are willing to accept lower wages in exchange for better institutional quality

Last year, I wrote a post about how return migrants to Vietnam prefer areas with higher-quality institutions. The post was based on the research of one of my PhD students, Ngoc Tran, myself, and Jacques Poot. Ngoc recently submitted her PhD thesis for examination, which is a great achievement. Along the way, she completed four research papers (see here, here, here, and here), and also has a forthcoming book chapter. In this post though, I want to focus on the fourth research paper, as it is the most novel.

In the paper, co-authored between Ngoc Tran, Jacques Poot and I, we looked at the intensity of migrants' preferences to high-quality institutions back in their home country. In other words, we asked how much things like absence of corruption, political stability, and the rule of law, mattered for migrants' decision-making about potentially returning home. To measure the intensity of preferences, we used a novel application of the contingent valuation method.

To do this, we first recognised that there are compensating differentials for working in different locations - in areas with higher-quality amenities (such as higher-quality institutions), wages will be lower than in areas with lower-quality amenities (such as lower-quality institutions). We can exploit this to work out what higher-quality institutions are worth, by looking at how much a migrant's income would have to change to make them indifferent between the area with lower-quality institutions and the area with higher-quality institutions.

We did this by asking Vietnamese migrants in New Zealand two questions:

1. Given your perceptions of the difference in institutional quality between New Zealand and Viet Nam, what would be the smallest level of weekly income before tax in Viet Nam where you would be happy moving back to Viet Nam permanently?; and
2. Now imagine that the institutional quality in Viet Nam changed so that it was equal to New Zealand in all ways (and everything else remained the same). If this happened, what would be the smallest level of weekly income before tax in Viet Nam where you would be happy moving back to Viet Nam permanently?

The first question allowed us to estimate the compensating different based on the current differences in institutional quality and other amenities between the two countries, as well as migration costs. The second question modifies the institutional quality in Vietnam so that it is equal to that in New Zealand, holding everything else (including migration costs) constant. The difference between the answer to Question 1 and the answer to Question 2 provides an estimate of the willingness of the migrant to accept lower wages in exchange for improved institutional quality in Vietnam.

Our estimates show that willingness to pay for an incremental unit improvement in institutional quality in Viet Nam is, on average, NZD 79.80 per week (approximately 33 percent of the average weekly wage in Viet Nam for the same period). Moreover, older migrants are willing to pay more, as are migrants who perceive institutional quality to be more important for the repatriation intentions.

As far as we know, this is the first paper ever to use contingent valuation to measure the intensity of preference for institutional quality, certainly among migrants if not among any population group. Notwithstanding the continuing debate on the use of the contingent valuation method (which I've written about here, here, and here), this was a really innovative piece of work.

Congratulations again to Ngoc on submitting her PhD thesis!

Read more:

• Return migrants to Vietnam prefer areas with higher-quality institutions

Compensating differentials are alive and well in Tokoroa

The New Zealand Herald reports:

A South Waikato District Councillor is puzzled as to why they're struggling to fill a well-paid job in the region.

The local district council is advertising for a health and safety manager in the town of Tokoroa, paying around $90,000 a year.

The council's last manager lasted just 12 weeks in the role and the officer before that 18 months.

Chairman of the Finance, Audit and Risk Committee Gray Baldwin told Larry Wiliams he's surprised more people haven't applied.

Some readers might remember a very similar story in 2016 about a general practitioner (also in Tokoroa) who was unable to attract a doctor for $400,000 per year (around double the going rate for a GP). Or the tourist operator in Taumarunui last year, offering an 'Auckland salary' of over $150,000 and similarly unable to find a good candidate.

At the risk of repeating myself, economists recognise that wages may differ for the same job in different firms or locations. Consider the same job in two different locations. If the job in the first location has attractive non-monetary characteristics (e.g. it is in an area that has high amenity value, where people like to live), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, if the job in the second area has negative non-monetary characteristics (e.g. it is in an area with lower amenity value, where fewer people like to live), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. The difference in wages between the attractive job that lots of people want to do and the dangerous job that fewer people want to do is called a compensating differential.

So, why would people be unwilling to take a job in Tokoroa for $90,000? Perhaps the job comes with undesirable non-monetary characteristics (living in Tokoroa might be high on that score for many of us). You have to wonder why the last two people in the job lasted just 12 weeks and 18 months respectively. If this job was worth it for the salary on offer, why did the last two people leave so soon?

Read more:

• Reason to be wary if a job in Taumarunui offers an Auckland salary
• The compensating differential for rural GPs must be enormous