Monday, 27 June 2022

When everything's a crisis, is anything really a crisis?

This Duncan Garner article in the National Business Review (gated) made me laugh, because it raised a point I have made many times (albeit, not on my blog):

The word crisis used to mean something. 

Now it seems everything is in a crisis. The latest crisis came just before our Matariki long weekend – a power shortage crisis. Maybe the Matariki stars will be our only form of light as now this country can't guarantee much at all, the latest being power.  

Why and how did this happen? And where's the accountability? The Minister overseeing this problem a year ago should walk the plank for failing to deliver a year later. That would be genuine accountability wouldn't it? 

So what's happening right now? Is it just us or is everything melting down? Look around – isn't everything a crisis or in crisis? 

There's the housing crisis, affordability crisis, cost of living crisis, mental health crisis, climate change crisis, health crisis, nursing shortage crisis, suicide crisis, water crisis, youth crisis, elderly abuse crisis, building supply crisis, Gib crisis. Did I mention the consumer confidence crisis

The obesity crisis? 

The manufacturing crisis?

Garner also missed the inequality crisis, the child poverty crisis, the supply chain crisis, the global data privacy crisis, and the Christmas toy crisis. And a few minutes on any search engine would no doubt turn up a dozen or more other crises.

Now, by definition, a crisis is: "a time of intense difficulty or danger". That may be true of most of the crises listed above (ok, maybe not the Christmas toy crisis, unless disappointed children and parents get really upset). However, the problem is that once you start to label everything as a crisis, the word starts to lose all meaning. In the good old days, a crisis really meant something. We had to act immediately, or face impending doom. Now, it just means things like a shortage of flowers on Valentine's Day. Yawn.

The problem here is that people's attention is scarce. People are not going to worry about the "pet adoption issue", or the "pet adoption problem", or even the "per adoption predicament". If you want rational people's attention, then it has to be a pet adoption crisis, or the perceived benefits of them paying attention won't outweigh the costs, and your issue will be lost in the general hubbub of people's social media feeds. However, if the incentive is to call everything a crisis, then there is no way for people to filter the really serious crises out from the noise, and they will stop paying attention.

Maybe, like Stephen Hickson's suggestion for a woolly words trading scheme, we need a more-specific crisis trading scheme, which caps the use of the word 'crisis'? We need this policy now, because we are in the middle of a crisis crisis.

Saturday, 25 June 2022

More on teaching evaluations and grade inflation

My Study Leave period is now over, and I've been preparing for my B Trimester teaching. At this time, many teachers would go back over past student evaluations, to determine what things they need to change or update in their teaching (instead, I tend to keep a detailed list of changes from the end of the previous teaching period, e.g. my current list of changes for ECON102 has about 90 minor tweaks to various topics, often incorporating new examples or new ways of organising or explaining the ideas.). So, student evaluations could in theory be a useful tool for improving teaching. However, as I've outlined in many past posts (for example, see this post and the links at the end of it), student evaluations of teaching (SETs) have a number of serious problems, particularly gender bias.

However, student evaluations also create incentive problems. Students tend to evaluate courses higher if they get a better grade. Teachers know that student evaluations affect their chance of promotion or advancement (even if research performance is considered more important by universities). So, teachers have an incentive to give students higher grades, and in turn receive better teaching evaluations as a result. I've posted on this incentive effect before.

Some further evidence of the relationship between grades and student evaluations is provide in this 2008 article by Laura Langbein (American University), published in the journal Economics of Education Review (ungated earlier version here). Langbein uses data from over 7600 courses taught at American University over the period from 2000 to 2003. She notes that even over that period, grade inflation is apparent in the data, as:

...the mean grade in 100-level courses increased from 3.1 to 3.2; the percent who earn less than a B in these courses dropped from 28% to 25%. For 200-level courses, the mean grade increased from 3.1 in Fall 2000 to 3.2 in Spring 2003, and the percent earning less than a B dropped from 29% to 24%. For 300- level courses, the mean grade remained unchanged at 3.3, but the percent below B dropped from 22% to 18%, and the median grade increased from B+ to A-. Among higher level classes, no such clear pattern of aggregate grade inflation is apparent.

Langbein then shows that students' actual grades and expected grades are both correlated with the students' evaluation of teaching, finding that:

...that the impact of a unit increase in the expected grade (say, from B to A, which contains most of the observations) would raise the instructor’s rating by an average of nearly 0.6 on a 6-point scale...

...a one-point increase in the average actual grade (say, from B to A, which is also where the observations lie) raises the SET by about 0.1 point on a 6-point scale...

Those results in themselves aren't necessarily a cause for concern. If the teaching is good, students should learn more (better actual and expected grades), and should evaluate the teaching higher. On the other hand, it could arise because when students are receiving and expecting a higher grade, they may 'reward' the teacher with a higher evaluation of their teaching, regardless of the actual quality of the teaching.

To try and disentangle those two competing explanations, Langbein applies a Hausman endogeneity test. Essentially, she tests whether there is reverse causality between the actual grade in a course and the SET - that is, whether the higher SETs cause higher grades (as well as higher grades causing higher SETs). She finds that:

While the results... clearly uphold the conclusion that faculty are rewarded with higher SETs if they reward students with higher grades, the sign of the residual variable depends on the specification of the endogeneity test. Under one specification, the sign of the residual is negative; under the other, it is positive. Consequently, the results give no clear indication about whether some component of the SET is a measure of ‘‘good’’ teaching and more learning, or easy class content and less learning.

So, while higher grades to lead to higher SETs, Langbein isn't able to definitively tell us why, or whether SETs are a good measure of teaching quality. However, from other research we already have good reason to doubt SETs, due to biasedness. Add this research to the (growing) list of papers that suggest that student evaluations can't tell us anything meaningful about teaching quality, and instead simply create incentives for grade inflation.

Read more:

Friday, 24 June 2022

Narrowing down on the source of the beauty premium

I've written a number of posts about the beauty premium (see the links at the bottom of this post) - that more attractive people are paid more, on average. There is robust evidence for this beauty premium across many labour markets, and for both genders and different ethnic groups. However, evidence for the specific mechanism underlying the beauty premium remains elusive. There are a few different theoretical reasons that beauty premiums may arise. First, employers may engage in taste-based discrimination - they like attractive employees, so they pay them more. If that were the case, we would see beauty premiums in all jobs. On the other hand, perhaps attractive people are more productive (in the sense that they generate more value for employers). This might be the case for customer-facing roles, for example. If that were the case, then we would see beauty premiums in jobs that require more human interaction, but no premiums in jobs with less human interaction.

That is essentially the test undertaken in this 2019 article by Ralph Stinebrickner (Berea College), Todd Stinebrickner (University of Western Ontario), and Paul Sullivan (American University), published in the journal Review of Economics and Statistics (ungated earlier version here). They use data from the Berea Panel Study, which included just over 500 students who first enrolled in Berea College in 2000 or 2001, and surveyed them each year after graduation (for up to ten years for some students). Because they can link the survey data back to students' characteristics during study, including their student ID picture, they are able to measure both labour market outcomes and attractiveness. Importantly, the surveys asked about the specific tasks that the graduates are undertaking in their jobs, allowing Stinebrickner et al. to classify jobs based on the actual tasks that are undertaken, rather than based on job titles. This reduces the measurement error from misclassifying whether the graduates are in people-centred jobs or not. Stinebrickner et al. classify all jobs into:

...four groups on the basis of jobs’ primary tasks: two groups where the primary task involves interpersonal interactions (high-skilled People and low-skilled People) and two groups where the primary task does not involve interpersonal interactions (high-skilled Information and low-skilled Information).

Each graduate's attractiveness was based on the average of 50 evaluators' ratings of their student ID picture, rated on a scale of 1 (significantly below average) to 5 (very attractive). They then run a fairly standard regression of wages on attractiveness, controlling for college GPA (which essentially accounts for differences in ability and motivation). Stinebrickner et al. focus most of the analysis on the sample of female graduates (because the sample size is much larger than for male graduates). For women, they find that there is:

...a large, statistically significant coefficient on the attractiveness measure. Specifically, increasing attractiveness by 1 sample standard deviation (0.78 on the 5-point scale) is associated with a 7.8% increase in wages...

The corresponding estimate for men is a 6.8% increase for each standard deviation higher attractiveness. Those results are consistent with the other literature on the beauty premium. However, of more interest are the results based on the different job classifications, where Stinebrickner et al. find that:

Providing very strong evidence that the attractiveness premium should not be attributed to an employer taste-based explanation, the results show that attractiveness has a strong effect on wages in jobs that specialize in People tasks but not in jobs that specialize in Information tasks. Specifically, a 1 standard deviation increase in attractiveness leads to a 9.7% wage increase in high-skilled People jobs... and a 9.3% wage increase in low-skilled people jobs (column 2)... In sharp contrast to the large wage premiums in People jobs... [the results] show no evidence of an attractiveness premium in Information jobs. Specifically, the coefficients on attractiveness for high- and low-skilled Information jobs are 0.011 and −0.039, and neither parameter is statistically significant...

Stinebrickner et al. also find that attractive people tend to sort themselves into people-related jobs:

The estimates of the marginal effects... show that increasing attractiveness by 1 standard deviation increases the probability of having a primary task of People by 0.053...

...these estimates indicate that attractive individuals are more likely to choose to work in both high-skilled People jobs and in low-skilled People jobs than in low-skilled Information jobs.

As noted above, if the beauty premium arises because of employers' taste based discrimination, then there would be a beauty premium for all jobs. But Stinebrickner et al. only find a beauty premium for jobs that involve mostly interpersonal interactions, and not for jobs that are mostly information-related. That is consistent with a productivity explanation. However, Stinebrickner et al. sound a note of caution:

While we tend to refer to the alternative to this explanation as a productivity-based explanation, it is worth stressing that it is difficult, even from a conceptual standpoint, to distinguish between a productivity based explanation and a customer taste-based discrimination explanation. To help fix ideas, consider a standard textbook-type example in which a customer is willing to pay more to interact with an attractive server in a restaurant. This preference might be viewed as productivity based if the attractiveness leads to more efficient employee-customer interactions that help a customer arrive at the best possible food order. Or this preference might be viewed as customer taste-based discrimination if attractiveness does not influence the customer’s order, but the customer simply enjoys looking at a more attractive employee.

The existence of only fairly nuanced differences between the two scenarios in the example highlights why it will always be difficult to conclusively distinguish between the customer discrimination and productivity-based explanations...

So, Stinebrickner et al. have provided us with a bit more detail on the source of the beauty premium. It arises either from higher productivity of more attractive workers in people-facing roles, or from customer taste-based discrimination. Unfortunately, because we can't disentangle those two explanations, we are left without an answer to the important policy question of whether the beauty premium leads to inefficiency (as it would if based on customer taste-based discrimination) or not, and so there is no strong evidence to favour any intervention in the market to limit or reduce the premium.

Read more:

Thursday, 23 June 2022

Why price controls likely make things worse, not better

Phil Lewis wrote a good article on The Conversation today, about price controls:

Australian shoppers are facing a crisis in the fresh-food aisles.

Iceberg lettuces that cost $2.80 a year ago have doubled, or tripled, in price. Brussel sprouts that cost $4 to $6 a kilogram are now $7 to $14. Beans that cost $5 to $6 a kilogram are now more than double – and five times as much in remote areas...

The price hikes have led to calls for supermarkets to impose price caps to ensure shoppers can still afford to feed their families healthy food.

But price ceilings on goods or services rarely, if ever, work. Prices play an important role in allocating resources efficiently. They send a signal to both customers and suppliers. To arbitrarily reduce prices would only increase shortages – both now and in the longer term...

Higher prices provide a signal both to consumers and producers. They tell consumers to buy less and switch to alternatives. They provide an incentive for producers to grow more – though this process is fairly slow given the time needed to grow and harvest fruit and vegetables.

But eventually, if the market is left to its own devices, prices will eventually return to “normal”, consistent with historical prices.

Capping the price, on the other hand, will benefit those lucky enough to grab supplies when they available. But it will likely reduce supply even further, by affecting the decision of producers unwilling to supply at below-market prices.

It could also lead to a “black market”, with some customers sourcing supplies by other means at higher uncapped prices...

So generally price caps are to be avoided.

Now, if anything, Lewis understates the case against price controls (specifically, price ceilings - a legal maximum price which the market price is not allowed to exceed). Price ceilings are effective in lowering the price, but with a lower price, consumers want to buy more (this is the 'Law of Demand'). However, there isn't more to go around (if anything, the lower price reduces the incentive for sellers to supply the good. So, you have more consumers wanted to buy a restricted quantity of the good - it creates a shortage.

Shortages mean that the limited quantity available must be rationed in some way among the many consumers who want to buy at the low price. Usually, price is the main rationing mechanism in the market (only consumers who are willing and able to pay the market price will buy the good). However, when there is a price ceiling keeping the price artificially low, then some form of non-price rationing, is going to have to occur. Perhaps this rationing is based on who can get to the store first in the morning when the new stock is available, or is lucky enough to be at the store when shelves are re-stocked. Perhaps consumers have to queue in order to avoid missing out. Perhaps retailers have a lottery. Perhaps there is a rationing system where consumers are limited in the quantity they are allowed to buy. Perhaps interested consumers sign up and receive tickets that guarantee them a small amount of the good.

Notice how all of these non-price rationing alternatives do one of two things: (1) they impose a direct (non-monetary) cost on consumers (such as the time cost of queueing); or (2) they involve an element of luck. Higher non-monetary costs simply undo a lot of the good that the price ceiling was intended to create. Getting a good that you want only because you were lucky in a lottery, or happened to be in-store when shelves were re-stocked, is in my view not a particularly fair allocation system.

These non-price rationing schemes are also open to abuse, by consumers who are lucky (or who are happy to face the non-monetary cost) on-selling the goods to other consumers who are willing to pay more. This is the black market that Lewis refers to. And higher black market prices than the controlled price provide an incentive for unscrupulous sellers to ensure that their friends receive the goods in the lottery, or just happen to be in store at the right time. This sort of corruption is simply not worthwhile if there is no price ceiling in place.

For some graphic examples of how price ceilings can go wrong, look no further than rent controls (see some of my posts on that here, here, here, and here). The short version is that rent controls reduce economic welfare, they reduce the quality of housing available to rent, and they may even increase inequality. And, their effects get worse over time. In a famous quote, the Swedish economist Assar Lindbeck (who passed away in 2020) wrote that “Rent control appears to be the most efficient technique presently known to destroy a city - except for bombing.”

So, even though some consumers will certainly benefit from the lower prices that price controls create, we must never lose sight of the fact that they don't come with significant negative consequences as well.