Alcohol minimum pricing, elasticity and profits

One of the common refrains from public health advocates is that New Zealand should introduce unit minimum pricing for alcohol, similar to Scotland and Canada (and soon to be introduced in Ireland). A recent article in the New Zealand Medical Journal made the case (gated; I don't see an ungated version anywhere), which was picked up by the New Zealand Herald, and critiqued by Eric Crampton.

I want to take a different angle, of relevance to my ECON100 students. What would be the effects of alcohol minimum pricing, if it was introduced. For simplicity, I'm going to ignore the existing excise tax on alcohol, and any externalities, and just concentrate on the minimum price.

The effect is shown in the diagram below. Without minimum pricing, the market equilibrium price is P0, and the quantity of alcohol sold (and presumably consumed) is Q0. But with a binding minimum price (above the equilibrium price) of P1, the quantity of alcohol demanded falls to Q1. In other words, alcohol consumption falls.

Now consider the economic welfare effects. The consumer surplus is the difference between the price the consumers are willing to pay, and the price they actually pay. Without the minimum price, consumer surplus is AEP0, but with the minimum price this falls to ABP1 (which makes sense - consumers consume less alcohol with the minimum price than without it, and pay a higher price for that alcohol). The producer surplus is the difference between the price the alcohol retailers receive, and their costs (which are shown by the supply curve). Without the minimum price, producer surplus is P0EF, but with the minimum price producer surplus is P1BCF. However, we can't easily tell if producer surplus has increased or decreased - retailers are selling less alcohol, but they are receiving a higher price for it.

Whether producer surplus increases or decreases when minimum pricing is introduced depends mainly on the price elasticity of demand for alcohol. If alcohol is price elastic, then alcohol consumers are relatively sensitive to price changes. That means that if price increases by x%, then the quantity of alcohol demanded will decrease by more than x%, and the firm's revenue (price multiplied by quantity sold) will decrease. Whether that results in decreased profit depends on whether the loss of revenue is larger than the costs saved by selling fewer units (which in most cases it will be).

On the other hand if alcohol is price inelastic, then alcohol consumers are relatively insensitive to price changes. That means that if price increases by x%, then the quantity of alcohol demanded will decrease by less than x%, and the firm's revenue (price multiplied by quantity sold) will increase. Given that costs will likely decrease (because the firm is selling fewer units), then profits will necessarily rise.

So, is demand for alcohol price elastic or price inelastic? There is a fair amount of debate on this point, and Eric Crampton has some of the latest evidence here. However, we need not go too far to determine whether the sellers themselves believe that demand is price elastic - if they think that is the case, they will argue against any minimum pricing (because if demand was price inelastic, minimum pricing would increase their profits!). And indeed, supermarkets (who have the largest market share of the retail alcohol market) are arguing against this policy. That suggests alcohol demand is price elastic. [*]

As an addendum I recently had a student, who worked for a large brewer, estimating the price elasticity of demand for products (note: not for alcohol as a whole). This student (who I can't name given their position in the industry) found that demand for specific products was highly elastic. This shouldn't be too surprising - there are many substitutes for a specific brand of beer. However, the student's results also suggests that consumers are very willing to shift to cheaper options (within the beer category).

Overall then, it appears that alcohol minimum pricing would reduce profits (else the retailers would be less likely to argue strongly against it), suggesting that alcohol is price elastic.

[*] The supermarkets might also argue against the policy if they believed that it would increase their costs, such as if they had to change their pricing policies. The costs of complying with minimum pricing don't seem to me to be large, so this seems unlikely as an explanation.

Why women pay more

Back in December, Danielle Paquette wrote in the Washington Post about gender differences in pricing:

Radio Flyer sells a red scooter for boys and a pink scooter for girls. Both feature plastic handlebars, three wheels and a foot brake. Both weigh about five pounds.

The only significant difference is the price, a new report reveals. Target listed one for $24.99 and the other for $49.99.

The scooters' price gap isn't an anomaly. The New York City Department of Consumer Affairs compared nearly 800 products with female and male versions — meaning they were practically identical except for the gender-specific packaging — and uncovered a persistent surcharge for one of the sexes. Controlling for quality, items marketed to girls and women cost an average 7 percent more than similar products aimed at boys and men.

When a seller offers a product (or service) for different prices to different customers (or groups of customers), and those price differences don't relate to differences in cost, we refer to that as price discrimination. In order for price discrimination to work, sellers need to meet three conditions:

1. Different groups of customers (a group could be made up of one individual) who have different price elasticities of demand (different sensitivity to price changes);
2. You need to be able to deduce which customers belong to which groups (so that they get charged the correct price); and
3. No transfers between the groups (since you don't want the low-price group re-selling to the high-price group).

What about the case of boys' scooters and girls' scooters? The sellers must believe that buyers of scooters for boys have more elastic demand for scooters than buyers of scooters for girls. How could that be? In my experience (having both a son and a daughter), if your child really wants a scooter you probably want to shop around for the best option. If you do so, you quickly realise that there are lots of scooter options targeted at boys, but far fewer options targeted at girls. This is of course related to the relative sizes of the markets for boys' scooters and girls' scooters. The larger market size means that more firms want to sell scooters for boys than for girls (as well as more variety of scooters for boys than for girls), which has a flow-on impact on pricing.

Because there are more options for boys' scooters, we say that there are more substitutes. Customers have more choice, and that makes demand relatively more elastic, so firms find it harder to raise prices (because customers would simply buy a boys' scooter from a different seller instead). With girls' scooters, there are fewer options (fewer substitutes), so firms find it easier to raise prices (or rather, to not lower them to the same price as scooters for boys).

This isn't just happening in the market for scooters. Paquette goes on to note other products where women pay more, including razor cartridges, haircuts, and clothing. You can make elasticity-related arguments for those differences in pricing too, though not all are related to the number of available substitutes. As Tim Harford notes:

This female insensitivity to price — if it really exists — might be driven by all kinds of things. Perhaps women tend to be busier and have less time to shop around. Or perhaps they care more about quality when it comes to deodorant or shampoo, whereas men just want something cheap.

Uri Gneezy and John List, in their book book "The Why Axis: Hidden Motives and the Undiscovered Economics of Everyday Life", argue that this type of discrimination is unfair, and for some products (like the scooter) it is hard to see the fairness in the pricing. However, as I have argued, for many products it may be more unfair not to have price discrimination. Either way, this is a more common pricing practice than many people realise. The next time you want to buy a scooter for your daughter, maybe you should buy the red one.

ED data doesn't tell us much about the spatial distribution of acute alcohol-related harm

One of my main research areas in recent years has been the social affects of alcohol outlet density - essentially looking at the relationship between the number of outlets in an area and measures of alcohol related harm. So, this recent paper in the journal Addiction (sorry I don't see an ungated version anywhere) by Michelle Hobday, Tanya Chikritzhs, Wenbin Liang, and Lynn Meuleners (all Curtin University) interested me.

In the paper, the authors look at the effect of alcohol outlets, sales and trading hours on alcohol-related injuries in Perth, Australia. The idea of looking at outlet numbers (separately for on-licence and off-licence outlets), sales, and trading hours all within the same statistical framework is interesting and potentially important. However, there is a problem in that they use data from emergency department (ED) presentations (I'll explain why that's a problem shortly). Anyway, the authors find:

At postcode level, each additional on-premises outlet with extended trading hours was associated with a 4.6% increase in night injuries and a 4.9% increase in weekend night injuries. An additional on-premises outlet with standard trading hours was associated with a 0.6% increase in night injuries and 0.8% increase in weekend night injuries.

So that seems fine. However, when looking at off-licence outlets:

Conversely, counts of off-premises outlets were associated negatively with alcohol-related injury, indicating a 3.9-4.9% lower risk per additional outlet.

What the hell? So, more off-licence outlets are associated with less harm?

John Holmes and Petra Meier (both University of Sheffield) wrote a commentary on the article in the same issue of Addiction. In the commentary, they correctly note that these sort of inconsistent results are endemic in the literature on the relationship between alcohol outlets and harm. By inconsistent I mean both inconsistent between different studies (even within the same geographic area), and inconsistent with theoretical predictions.

In this case, the problem is the measure of alcohol-related harm. Hobday et al. use (alcohol-related) ED presentations, which on the surface seems like a good measure of alcohol-related harm. Person drinks too much, suffers an accident (or violent incident) and goes to the hospital. Simple enough, right? The problem lies in the address coding in the ED dataset. In health data (like ED data), patients are geographically coded to their home address. This may, or may not, coincide with the location of the harm.

For chronic harm (e.g. cirrhosis), coding to patients' home addresses makes a lot of sense. The geographic accessibility of alcohol over the long term can reasonably be measured by the extent of access to alcohol from each patient's home. However, for acute harm (e.g. injury presentations) this doesn't hold. The geographic accessibility of alcohol on the night of the incident relates to where the patient was on that night, which may or may not be their home address at all. I'd wager that a lot of alcohol-related injury presentations at night (the measure used by Hobday et al.) arise from encounters in the night-time economy away from the patient's home. Indeed, Hobday et al. recognise the problems with their data:

A limitation of using ED records is that location information is restricted to the patient's place of residence, and data on last place of drinking are not recorded.

So, there is little reason for us to believe that we would observe a positive relationship between alcohol outlet numbers (or hours or sales) and ED presentation data. In fact, my co-authors and I observed mostly statistically insignificant results when looking at similar data for Manukau City. Having acknowledged the problems with the ED data, we have avoided this approach in our subsequent work (e.g. see here or here).

Now, let's think through the unexpected results. Hobday et al. find that there are more ED presentations from people who live in areas that have fewer off-licence outlets (especially those that open later) compared with areas that have more off-licence outlets. One potential explanation is that people who live close to an off-licence outlet (especially off-licence outlets that open later) have ready access to alcohol and can easily drink at home, and have less reason to travel to entertainment precincts where they might be at higher risk of becoming a victim of violence. This might be reinforced by drinkers who don't want to go to entertainment precincts to drink, but still want to have ready access to alcohol, choosing to live in areas where an off-licence outlet is nearby. In contrast, people who don't live close to an off-licence outlet (or where such outlets close earlier) must travel further to drink, and may therefore be more likely to drink in entertainment precincts where they are at higher risk of alcohol-related harm such as violence. I'm not sure whether this explanation is the true one that underlies the results, but it might be one contributing factor.

Overall though, for the sake of credibility of results, it might be best not to use ED data as a measure of acute alcohol-related harm, unless the location data relates to the location of harm rather than the patient's residential address.

The compensating differential for rural GPs must be enormous

In the news this morning was a story about a Tokoroa GP struggling to recruit a new doctor:

A Tokoroa doctor is struggling to fill a job that offers a young GP the potential to earn an eye-watering $400,000-plus a year - and he will even chuck in half his practice for free...

In the past four months, Dr Kenny has not received a single application for the permanent position, which he believes is due to the perception of a rural general practitioner being a dead-end job.

The 61-year-old said $400,000 after expenses was more than double a GP's average income. But even the prospect of no weekend or night work had failed to attract a taker.

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 the supply of labour to be higher, 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 the supply of labour to be lower, 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.

Now, consider the case of this job for a doctor. Even when offering a 100% premium, Dr Kenny isn't able to fill the position. There are a number of ways the compensating differential may arise in this case.

First is the location. Living in urban areas is often more attractive to young people (including presumably young doctors) than living in rural areas. So, a premium is required to overcome that difference (which, admittedly, might not apply to all people).

Second are the job characteristics. Reputedly, working as a rural GP is very hard work, involving long hours, and where it is difficult to take breaks or holidays (or more so than for urban GPs or other doctors). Dr Kenny says as much:

"Last year, I cancelled a holiday because I couldn't get a locum ... and this year I am probably going to have to cancel a holiday ... and it's just tough for me."...

He worked between 8.30am and 6pm without a lunch break.

Again, a premium would need to be offered to make a job with long hours and difficult working conditions attractive.

Third, are firm characteristics. In an occupation like doctors, it would not surprise me if firm's reputations for working conditions are reasonably well-known within the domestic community. So, if a firm has a difficult manager, for instance, it would be less attractive to potential employees and again a premium would need to be offered. I'm not saying that's true in this case, but in theory it is a further source of compensating differentials in wages.

Overall, it appears that a $200,000 premium (plus whatever half of the GP practice is worth) is not enough to compensate potential employees (and co-owners!) for the negative characteristics of being a doctor in Tokoroa.

[Update 24/02/2016]: After the media coverage, many doctors are interested in the position. However they are international, not domestic, doctors. Perhaps the compensating differential for moving from Portugal or Brazil to Tokoroa isn't as large?

Also, the other practice in Tokoroa notes that the stress of owning a clinic is a factor that makes the job less attractive. See my second point above.