Find this guy a girlfriend, for $10,000

Tyler Cowen occasionally posts something riotously funny (at least, to me!). Earlier this month, he posted:

This man is bidding 10k for a girlfriend, but I don’t think he understands where the adverse selection problem lies.

At the risk of dragging out the joke, I'll explain. From the linked article on Business Insider Australia:

This Alabama man has been on 30 unsuccessful dates in the past the past ten months — to remedy this situation, he created a website offering a $US10,000 reward to anyone who can find him a girlfriend.

Ren Lu You is a 29-year-old living in Birmingham, Alabama...

Even though he was going on plenty of dates, he wasn’t meeting the kinds of women he envisioned potentially spending the rest of his life with.

“With online dating you have this problem of adverse selection,” You explained. “Only the people who self-select into a particular dating website are the people you have access to.” 

Adverse selection arises when there is information asymmetry - specifically, there is private information about some characteristics or attributes that are relevant to an agreement, and that information is known to one party to an agreement but not to others. In the case of online dating, the 'agreement' is a relationship (or even a single date) and the private information is about the quality of the person as a potential date - each person with an online dating profile (the informed party) knows whether they are a high-quality date or not, but the others who might match with them (the uninformed parties) do not.

An adverse selection problem arises because the uninformed parties cannot tell high quality dates from low quality dates. To minimise the risk to themselves of going on a horrible date, it makes sense for the uninformed party to assume that everyone is a low-quality date. This leads to a pooling equilibrium - high-quality and low-quality dates are grouped together because they can't easily differentiate themselves. Which means that people looking for high-quality dates should probably steer clear of online dating.

Signalling is one way that markets have adapted to deal with adverse selection problems. With signalling, the informed party finds some way to credibly reveal the private information to the uninformed party. There are two important conditions for a signal to be effective: (1) it needs to be costly; and (2) it needs to be more costly to those with lower quality attributes. These conditions are important, because if they are not fulfilled, then those with low quality attributes could still signal themselves as having high quality attributes.

Now, consider Ren. Women don't know whether Ren is a high- or a low-quality date (this is the private information). He offers the $10,000 prize to try to signal he is high quality. Sure, this is costly. But a low-quality date can offer a $10,000 prize too - the prize doesn't distinguish Ren's quality as a future boyfriend. However, consider this - would a high-quality date have to offer $10,000 in order to attract a girlfriend? If Ren wants girls to believe he is a high-quality date, he is clearly providing the wrong signal.

Is sexual freedom a normal good?

In economics, a normal good is defined as a good where a consumer demands more of it as their income rises (in contrast, an inferior good is a good where a consumer demands less of it as their income rises). In other words, we say that normal goods have a positive income elasticity (while inferior goods have a negative income elasticity). For market goods, we can evaluate income elasticity by looking at how consumer purchases change as their income changes (controlling for other important variables, especially prices). For non-market goods such as sexual freedom, we can't look at consumer purchases but we might get some insight by looking at what happens as population-level income measures change (again controlling for other important variables, though as we are talking about non-market goods we can't control for price).

Which brings me to this recent paper (ungated earlier version here) by Feler Bose (Alma College), entitled "The determinants of sexual freedom from 1990 to 2010". To some extent it is disappointing that this paper was published in a short-form journal like Applied Economics Letters, as it doesn't give nearly enough detail on the methods. Briefly, Bose constructed a new sexual freedom index for U.S. states over the period 1990 to 2010, then regressed that index variable against median household income, as well as measures of ideology (of citizens, and of government), population density, median age, religion, and race. He finds a highly statistically significant and positive relationship between income and sexual freedom - states with higher median household incomes have higher sexual freedom. In other words, as incomes have increased people have demanded more sexual freedom, meaning that sexual freedom is a normal good.

However, I have a couple of gripes about the paper that lead me to doubt its conclusions. As mentioned above, there isn't enough detail on the new measure of sexual freedom. I have a real problem with this in particular:

This index codes sixteen variables that fall under two broad categories (marriage protection and sex crimes)... Each variable was coded on a four point scale (0, 1, 2, 3) with 3 indicating the most freedom. Further, each variable is given equal weight. To obtain the sexual freedom index value for a state during a year, each variable is added up. The higher the number, the broader the sexual freedom in that state.

I'm not sure how much validity you can assign to an index that is constructed in such a subjective manner. For instance, how were the values of 0-3 determined for each variable? Also, what is the basis for giving equal weight to "prostitution laws for pimp", "prostitution laws for prostitute", and "prostitution laws for John" (three of the variables included in the index), when these variables are likely to be closely correlated (or at least, there is no evidence provided to suggest that they aren't closely correlated). Moreover, the index used in this paper differs in construction from a similar index the author used in earlier work (described here). In that earlier paper, principal components analysis was used to construct the index (which is what I would have done, to ensure that variables that are closely correlated do not have undue influence over the index as a whole), and each variable was scored only 0 or 1 (rather than 0-3). In that earlier paper there were some odd results, with the first principal component placing a negative factor score on "age at consent" and "prostitution laws", making the overall index difficult to interpret. Perhaps that is why it wasn't used in the new paper?

It's a pity that the new index isn't available online and I can't see any follow-up work by the author. As he notes in his conclusion, some of his results (e.g. higher median age is associated with more sexual freedom) are difficult to justify. This may be simply due to a lack of robustness in the methods, which means that even though we have some results we can't say with any certainty whether sexual freedom is a normal good.

Can technology save the rhinos?

I've written several posts now on saving endangered species (see here and here and here). Mostly those posts are about the ineffectiveness of proposed interventions, like burning ivory (which increases the price of ivory, and leads to more poaching, not less).

This post is about two of the latest proposed technological solutions for saving rhinos. The first proposed solution is using 3D printing to create and flood the market with fake rhino horns:

A San Francisco biotech startup has managed to 3D print fake rhino horns that carry the same genetic fingerprint as the actual horn. It plans to flood Chinese market with these cheap horns to curb poaching...

Matthew Markus, CEO of Pembient says his company will sell rhino horns at one-eighth of the price of the original, undercutting the price poachers can get and forcing them out eventually...

Susie Ellis, Executive director of International Rhino Foundation says: "Selling synthetic horn does not reduce the demand for rhino horn [and] could lead to more poaching because it increases the demand for “the real thing.” In addition, production of synthetic horn encourages its purported medicinal value, even though science does not support any medical benefits."

This solution has some potential. Fake 3D-printed rhino horn will be a very close (but probably not perfect) substitute for authentic rhino horn (it won't be a perfect substitute because no doubt some buyers would retain a preference for the 'real thing'). Consumers tend to switch from higher-priced to lower-priced substitutes, which would mean introducing fake rhino horn into the market would reduce the demand for authentic rhino horn. Or maybe not.

What if flooding the market with fake 3D-printed rhino horn turns authentic rhino horn into a symbol of high status? Since anyone can buy the cheap fake rhino horn, authentic rhino horn becomes even more valuable than before - essentially it becomes a Veblen good. Veblen goods are luxury goods where the price is a signal of the high status of the purchaser. In this case, when the price goes up people the good is an even more powerful signal of high status, and so consumers who are seeking status demand more of the good. However, one key characteristic of Veblen goods is that they rely on conspicuous consumption - it's no good buying the good if no one knows you bought it. This might be difficult if consuming rhino horn is made illegal, which China has just done.

The second proposed technological solution is attaching hidden cameras to rhinos:

A British team has developed a system to help protect wild rhinos, which could be extinct within the next ten years, because they are hunted by poachers for their lucrative horns.

By using a combination of GPS trackers, heart rate monitors and hidden cameras, wardens can be on site to foil an attack within seconds.

Cameras are embedded inside the horn of the rhino, in what researchers say is a painless procedure.

In theory, embedding GPS trackers and hidden cameras increase the costs for poachers, reducing the supply of rhino horns. However as I've noted before, reducing supply simply increases the price, and increases the incentives for poaching. The higher prices for rhino horn will likely spur innovation on the part of the poachers - how long before poachers would start tranquilising the rhinos so that the camera isn't activated? Or, since we're talking about technological solutions, maybe future poachers start using EMPs to disable the cameras and trackers? Either way, this wouldn't appear to be a long-run solution to rhino poaching.

For rhinos, or elephants, I'm still in favour of farming as a solution.

[HT: Marginal Revolution, here and here]

More on endangered species from my blog :

• Because crushing ivory is so much better than burning it
• Poisoning rhino horns to save the rhinos
• This couldn't backfire, could it?... Ivory burning edition

Be careful with producer surplus, because housing is different

One of the most important concepts I teach in ECON100 and ECON110 is the concept of economic welfare. In the simplest terms economic welfare is made up of the net benefits that sellers get from selling a product (the producer surplus), and the net benefits the consumers receive from buying the product (the consumer surplus). Producer surplus is the difference between the price that producers receive for selling the product, and what the product costs them to produce. The consumer surplus is the difference between the maximum amount the consumer is willing to pay for the product, and the price they actually pay. Since it is made up of the benefits to sellers and the benefits to buyers, economic welfare therefore demonstrates the overall benefits that arise from the operation of a market.

Which all sounds fairly simple, but sometimes it isn't quite so easy to apply these concepts. Take owner-occupied housing for instance. In the New Zealand Herald on Wednesday, former Act Party leader Jamie Whyte writes:

To see why banning foreign buyers is a bad policy, start with the benefit to New Zealanders that occurs when one Kiwi buys a house from another Kiwi. Suppose Kiwi John buys a house from Kiwi Jane for $800,000.

John must value the house at least a little more than $800,000, otherwise he would have been unwilling to pay this much for it. Suppose the maximum he would have paid is $810,000.

Then he benefits $10,000, this being the difference between the $800,000 he paid and the value of the house to him. (Economists call the difference between what someone is willing to pay and what they actually pay the "consumer's surplus".)

Similarly, Jane must have valued her house at less than $800,000, otherwise she would not have been willing to accept this amount. Suppose she would have sold it for no less than $790,000. Then she benefits $10,000 from the sale.

So, the total benefit of the transaction to Kiwis is $20,000, split evenly between the buyer and the seller.

Now suppose instead that a foreigner, Fritz, had out-bid Kiwi John. To do this, he must have paid at least $810,001 since, by hypothesis, John was willing to spend up to $810,000. What is the benefit to New Zealanders in this case?

John is where he started, still with his $800,000 and without Jane's house. He gets no benefit from the sale of Jane's house to Fritz. But Jane's benefit has risen from $10,000 to at least $20,001. Which means the total benefit to New Zealanders has increased by at least $1. (In reality, the net gain will usually be in the thousands.)

There is a problem with the scenario above, in the calculation of Jane's producer surplus. If Jane is a owner-occupier and she sells her house, she then has the money from selling her house but has nowhere to live. She either has to buy a new house, rent, or live in her car or under a bridge. Let's ignore the latter three options for the moment.

Given Jane was willing to sell her house for no less than $790,000, that suggests that she can get a new replacement home for that cost. That's why she would be $10,000 better off (her consumer surplus), since she still has a home and has $10,000 left over in her bank account.

However, once Fritz is operating in the market, houses are now more expensive. He has increased the price of Jane's house by $10,001. If other houses had increased by less than $10,001, Fritz would prefer to buy one of those other houses. So, all houses must have increased in price by $10,001, including the house that Jane is intending to buy. So even though Jane might get $810,001 from Fritz for her house, to find somewhere new to live is now going to cost Jane $800,001 instead of $790,000. So, Jane's producer surplus is still $10,000, regardless of whether the purchaser is John or Fritz. Essentially, this is just a convoluted explanation of why buying and selling in the same market doesn't make you any better off on average, irrespective of prices.

Another way of thinking about this is in terms of the 'real value' of the economy. In this simple example, there is one house irrespective of whether that house is being transferred from Jane to John, or Jane to Fritz. Adding Fritz into the pool of potential buyers doesn't increase the total amount of real value in the economy (which is still just one house being sold), so in net terms having Fritz involved can't enrich Jane.

So, a government concerned about maximising benefits for New Zealanders should prefer the house transfer from Jane to John ($20,000 economic welfare = $10,000 consumer surplus for John + $10,000 producer surplus for Jane) over the house transfer from Jane to Fritz ($10,000 economic welfare for New Zealanders, since Fritz's consumer surplus doesn't count). Unless Fritz is moving to New Zealand perhaps?

Of course, if Jane is a property developer and not the homeowner, then things are different. Since she doesn't have to replace the house with another (or face living in her car), then the producer surplus doesn't change regardless of whether she sells to John or to Fritz. In this case, presumably the $790,000 minimum she is willing to accept for the house represents her costs of building (and financing, etc.). In this case the sale to Fritz does increase economic welfare by an additional $10,001 (or more). In terms of real value, because Jane built and sold a new house, it does increase the real value of the economy (by one new house).

Which I guess suggests that we should be in favour of following a similar policy setting to Australia, where foreigners can buy newly-constructed houses, but not existing homes?

More from my blog on Auckland housing:

• More on stamp duty for Auckland - why it should apply to all buyers
• The winner's curse and the Auckland housing bubble
• Matthew Goodson agrees with me on stamp duties
• Bring back stamp duty for Auckland!
• Out-of-control rent increases in Auckland - why?
• Housing policy: Subsidy vs. Supply

Students are more selfish and rational than non-students

Experimental economics is one of the really exciting growth areas of empirical economics - several universities in New Zealand now have experimental economics laboratories, including the Waikato Experimental Economics Laboratory (WEEL) which is run by my colleague Steve Tucker. Experimental economics is attractive because it allows researchers to test economic theories, and the effects of economic institutions, in an environment where other factors can be carefully controlled. Most of the participants in these economic experiments are students, because students are a conveniently available sample to university researchers, and can be easily incentivised to participate in experiments. However, this raises an important question that has implications for the external validity of experiments - do samples of students differ systematically in their actions in laboratory experiments from non-students?

A new paper published in the Journal of Economic Behavior and Organization (ungated version here; PDF) by Michele Belot (University of Edinburgh), Raymond Duch (Oxford) and Luis Miller (University of the Basque Country) looks to address this question. The authors conducted a series of classic economic experiments with three samples (one students only; one non-students only; and one comprising a mix of students and non-students), and compared the responses of the two groups (students and non-students).

The results suggest that there are substantial differences:

In all games, with the exception of the auction game, we find that students are significantly more likely to behave as selfish and rational individuals.

Starting with the dictator game, we find that 57 percent of the students donated nothing. In contrast, only 17 percent of our non-students donated nothing...

Turning to the binary trust game, we find that only 35 percent of our student trustors trust in comparison to 82 percent of non-student trustors...

We also find significant differences in the rates of reciprocation: 56% of the student population and 87% of the non-student population reciprocated...

Our third game involving other-regarding preferences is the public good game... students are considerably more likely to free-ride: in the first round of the public goods game, 24 percent of the students contributed nothing to the public good while only 9 percent of the non-students were strictly non-cooperative.

Turning to the beauty contest game... Thirty percent of our non-student subjects made choices consistent with at least level 1 iterative reasoning compared to 56 percent for the student subjects.

Without going into detail about the experiments themselves (you can read about the dictator game here; the trust game here, the public good game here, and the beauty contest here), it demonstrates that students are more selfish (less other-regarding) and more rational decision-makers. The authors do note that "students are younger and smarter" than non-students, but the results persist even after controlling for cognitive ability, age and gender.

The results should give pause before we draw grand conclusions on the basis of laboratory experiment results. However, as the authors (and others) have suggested, laboratory experiments may still be useful for identifying qualitative effects. For example, they may tell us whether threat of punishment will induce less free-riding in the public goods game, but won't give robust information about how much less free-riding there will be.

[Update: Added in some links that I had forgotten to add first time!]

Why paid parking is a good idea... sometimes

To some people, it sounds like a bad joke: "You know your vice-chancellor is an economist when... paid parking is being implemented at your university campus". But it's no joke - paid parking will be implemented at the University of Waikato from the start of 2016. This is in spite of a fairly large amount of opposition from students, both current and former. It might be contagious too - Wintec is also introducing paid parking at its Rotokauri campus across town, while the costs of parking rise elsewhere as well with commuters in Auckland looking at paying more for parking.

Here's why paid parking is a good thing. If you've ever tried to get a parking on campus during the A or B Semester, you know it is almost impossible to find a space in the Gate 1 car park after 8:45am. Gate 2B isn't much better, and Gate 10 (near the Management School) is often full as well (and far from most lecture theatres unless you are a management student). Clearly there is a shortage of parking at these peak times.

This shortage can be easily demonstrated as in the diagram below. The supply of parking (S) is fixed at the number of available parking spaces (at QS), while the demand curve (D0) is downward sloping (there would be less demand for parking spaces if the price of parking increased). At the current zero price, the quantity of parking spaces demanded (QD) is larger than the available supply. There is excess demand for parking spaces - some drivers miss out on parking spaces, and resort to parking on nearby streets.

However, that isn't the end of the story. These 'free' parking spaces aren't free at all. In order to ensure that you get one of the free parking spaces, you have to leave home early since otherwise you may miss out on a space. Not only that, you might have to spend some time driving around the car park looking for a spare space. Or you might miss out and have to park further away on a side street. All of these situations cause drivers to incur an opportunity cost of parking. They are giving up time in order to get a parking space, and that time is costly to them. So, while there might not be a monetary cost on parking spaces, that doesn't mean they are zero cost to drivers.

The response of the University to the excess demand for parking spaces is to introduce paid parking from next year. At $2 a day, that probably isn't enough to raise the price all the way to equilibrium (Pe), but let's say that the price increases to P1. This reduces the quantity of parking spaces demanded (from QD to QD1), because some students (and staff) will choose to leave their cars at home and walk or cycle or take public transport to the campus instead. The quantity of parking spaces supplied remains constant (at QS), and the excess demand (or shortage) of parking spaces reduces. This means that drivers will find it easier (less costly in terms of time) to find a parking space in the morning, and they might not have to leave nearly as early in the morning to secure a parking space. So, while there may be a monetary cost to parking from next year, the non-monetary cost will be lower.

So, paid parking might be a good idea. But not always. Now consider the situation when it is not A or B Semester, i.e. when there are fewer students on campus. Demand for parking spaces is much lower in off-peak times (D1), and this is demonstrated in the diagram below. Notice that the quantity of parking spaces demanded at the zero price (QD2) is lower than the number of available parking spaces (QS). There is excess supply of parking spaces, i.e. parking spaces are not scarce. Notice there is no equilibrium price because there is no non-zero price that brings supply and demand into balance. In this case, when the university imposes the $2 per day charge (P1), the quantity of parking spaces demanded falls even further below the quantity supplied (to QD3). the car park becomes even emptier (the excess supply of parking spaces increases). This clearly makes drivers worse off, because there are no offsetting savings in non-monetary costs.

I've been asked by a few students (and the union) if I'm in favour of paid parking. I am in principle, but with a caveat - it should only apply to peak teaching and parking time, i.e. during the A and B Semester. That would seem a sensible way to manage the excess demand for parking spaces during these peak times, while not imposing unnecessary costs on staff and students during off-peak times. What would be even better would be to use the car park revenue to lower the costs of alternative means of transport - for example, Massey University is currently celebrating ten years of free buses for students and staff.

Safer roads and offsetting behaviour - Tauranga Eastern Link edition

The New Zealand Herald reports:

Motorists are driving in excess of 125 km/h on the new Tauranga Eastern Link road and police, who fear someone could be killed, say the road is "not a racetrack".

The stretch of State Highway 2 between Te Maunga and Domain Rd opened in May and since then motorists have been caught driving at excessive speeds.

While the construction was underway the stretch of SH3 was narrow and has speed restrictions, Senior Sergeant Ian Campion said...

On Monday four motorists were caught driving in excess of 125 km/h and ranged from a male learner driver, through to an experienced female driver in her 40s. Police would not be disclose the precise speeds or the top speed.

The highway is due to be completed shortly with the opening of the remainder of the road, and police are encouraging everyone who uses the road to make safety their number one priority.

This is yet another example of the Peltzman effect (which I've written about in the context of driving here and here) - if driving is made safer, people will drive faster. The basic explanation goes like this: Rational (or quasi-rational) drivers will weigh up the costs and benefits of driving faster. The benefits include less time wasted on the roads (an opportunity cost - you give up some time you could spend doing something else). Moreover, the marginal benefits probably decrease the more a driver speeds (because opportunity costs increase the more time is wasted). The costs of driving faster include an increased risk of a serious car accident - this cost is made up of two parts: (1) the probability of a serious accident occurring; and (2) the health and other costs of the accident itself. The marginal costs increase as speed increases, because the probability of an accident and its seriousness both increase.

If they are optimising, the driver will choose to drive at the speed where the marginal benefit (MB) of driving faster is exactly equal to the marginal cost (MC0). This occurs at S0 in the diagram below. At this point, driving a little bit faster entails a higher additional cost than the benefit they would receive (which is why they will drive no faster than S0).

When driving is made safer (such as by replacing a narrow road with a wide and straight multi-lane highway like the Tauranga Eastern Link road), this changes the incentives that drivers face. The cost of driving fast falls (since the chance of being involved in a head-on collision on the bridge is reduced). So, in the diagram above, marginal costs of speed are lower (MC1). This increases the optimal driving speed to S1. What we would observe then is drivers driving faster because of the perceptions of greater safety. 

So, the road may be safer, but the driving behaviour changes to offset some of that additional safety. That isn't to say that safety isn't the drivers' number one priority - only that they are weighing up increased safety against the benefits of additional speed.

Previously on my blog:

• Safer driving and offsetting behaviour - Golden Gate Bridge edition
• Safer cars and offsetting behaviour: NASCAR edition

How Jetstar takes advantage of your quasi-rationality

You may have seen that Consumer NZ is leading a campaign against Jetstar's practice of pre-selecting optional extras like travel insurance and seat selection in its online booking form:

"Jetstar's practice of pre-ticking boxes for optional extras risked misleading customers on both sides of the Tasman into paying for services they didn't want," Ms Chetwin said.

"In both markets, it uses the same sneaky practice of ticking boxes for travel insurance, seat selection and extra bags. It's high time Jetstar stopped confusing its Kiwi and Aussie customers and ditched the ticks."

What Jetstar is doing is taking advantage of our quasi-rationality. But how?

A purely rational buyer of airline tickets from Jetstar would evaluate the cost and expected benefits of travel insurance and make a fully-informed decision - and if the expected benefits outweighed the cost, they would choose to purchase travel insurance. However, few people are purely rational.

In their book "Nudge", Thaler and Sunstein point out that the selection of default options can affect people's choices. The examples they use to illustrate include default retirement savings plans (most people don't actively select plans, which is why most people remain in the default plan - which has also been observed in New Zealand), and organ donation (if the default is opt-out rather than opt-in, then more people donate organs - see this excellent paper (PDF) by Johnson and Goldstein for example).

So, even though the choice not to purchase travel insurance involves simply un-ticking a box, fewer people will choose not to purchase if the box is pre-selected. And this leads to higher profits for Jetstar.

One way of explaining this surprising behaviour (not ticking a box to avoid the cost of travel insurance is almost a no-brainer if you don't think it's worth it, surely?) is to think about the choice itself. The decision about whether you will need travel insurance or not is not straightforward. If you were purely rational, you would need to weigh up the risks of all catastrophic (and not-so-catastrophic) events that could befall you on your travels, and the costs associated with those events, in order to evaluate the benefits that insurance could provide. That evaluation is hard, meaning there is a cognitive cost associated with making the decision. So, because the decision in itself is costly, rather than making the decision you might choose to make no decision (and avoid the cognitive cost involved). This results in the box remaining ticked (if it started out pre-selected), and you end up paying for travel insurance. Whereas if the box was not pre-selected, you wouldn't buy the travel insurance.

Plenty of firms make money from our less-than-pure rationality (or quasi-rationality as Richard Thaler terms it), but note that this is quite different from the actions of an un-named smartphone app creator as described in this post by Linnea Gandhi. As she notes, changing the 'buy' button to look exactly the same as the previous 'do not buy' button isn't so much taking advantage of our behavioural biases as it is taking advantage of our inattention to detail.

More on stamp duty for Auckland - why it should apply to all buyers

Back in May I advocated for stamp duty for Auckland. Then last week, Matthew Goodson wrote a piece in the Herald that agreed with me (which I blogged on here). Yesterday, Chinese-based financial advisor Rodney Jones also wrote an article in the New Zealand Herald that discussed stamp duties:

Fortunately, Singapore and Hong Kong - and some cities in China - have been down this path before. We can draw on their experience. Singapore imposes a 15 per cent stamp duty on non-resident purchasers of residential property, as does Hong Kong. In China, in order to restrain the property boom in 2011 cities such as Beijing and Shanghai - amongst others - imposed a blanket ban on non-resident purchases of residential property, which in practice blocked purchases by Chinese residents from other provinces.

I believe we should take the lead from Singapore and Hong Kong and impose a 20 per cent stamp duty on non-resident purchases of Auckland property...

The proceeds of the stamp duty could stay within the Auckland economy, with the duty receipts contributing to a sinking fund for Auckland infrastructure. As the Chinese leadership likes to say, this would create a win-win for Auckland - and for New Zealand.

Now I didn't argue for a 20 percent stamp duty, but a much more modest 2.5 percent (similar to Australia), which I think is much more feasible and less costly on the economy to collect. For instance if foreign buyers make up 40% of Auckland buyers (Labour suggested 40% of buyers had Chinese ethnicity, but some of those will be New Zealanders; this will be offset by foreign buyers from other countries, so 40% may be illustrative), then a 20% stamp duty on 40% of the market raises about three times as much revenue as a 2.5% stamp duty on the entire market (ignoring for simplicity the decreased demand that would result from the stamp duty raising prices). However, the deadweight loss (the loss of economic welfare) generated by the tax is likely to be much more than three times larger. Consider the diagram below (the diagram shows a specific tax, which is a constant per-unit amount of tax, rather than an ad valorem tax, but the principle is much the same in either case). Without the tax, the price is P0 and quantity Q0. There is no deadweight loss. With a small tax (tax1), the per-unit value of the tax is the vertical distance AB, and the deadweight loss is the triangle AEB. With a tax that is three times larger per unit (tax2), the per-unit value of the tax is the vertical distance CD (about three times the vertical distance AB), and the deadweight loss is the triangle CED. It is clear that CED is much more than three times larger than AEB (with linear demand and supply curves and a specific tax, the deadweight loss is nine times larger when the tax is three times larger).

Neither did I suggest that stamp duty should only apply to non-residents. Taxes that generate the same income but apply to only some sub-markets also generate larger deadweight losses than taxes that apply to the market as a whole. Again, thinking about the diagram above a tax that generates the same income from only one sub-market would need to be larger in per-unit terms, leading to a larger deadweight loss (even when you consider that there would be no deadweight loss on the sub-markets that are left un-taxed).

Moreover, I'm not convinced that the distinction between residents and non-residents is so easy to enforce in practice - many foreign buyers will have contacts (or children) in New Zealand that can execute purchases for them. Applying stamp duty to only some purchasers will increase the bureaucratic costs associated with its collection.

However, I do agree with Jones that the proceeds of a stamp duty should be used for infrastructure provision, or housing development. An increase in supply would act to dampen house price increases in Auckland. Bring on stamp duty!

Is it time to ban laptops from lectures?

Students are increasingly using laptops in lectures, for 'note-taking'. It is surprising (to me, at least) that this has been a relatively recent (and noticeable) trend in my classes. However, since I spend a good portion of my lecture time walking around the class, I can see the potential for distraction that open laptops provide - although students usually get back on-task after being the subject of jokes about updating their Facebook status to tell their friends about how awesome economics is.

Distraction aside though, it has been an open question as to whether note-taking on laptops is more effective for study purposes than note-taking by hand. Students argue that, since they can type faster than they can write, they can make more notes on their laptop than by hand. However, quantity of notes is not necessarily a substitute for quality of notes.

Back in March, Joseph Stromberg wrote an article on Vox about a study by Pam Mueller (Princeton) and Daniel Oppenheimer (UCLA) entitled "The pen is mightier than the keyboard: Advantages of Longhand Over Laptop Note Taking" (gated, ungated here), published in the journal Psychological Science. In the study the authors attempt to disentangle whether (and why) longhand note-taking is superior to note-taking on laptops.

Mueller and Oppenheimer conducted three studies with students in experimental settings. In the first study, the authors projected selected TED talks onto a screen and asked the participants to take notes (randomised to be either by hand, or on a laptop), using "their normal classroom note-taking strategy". To eliminate distraction as a factor, none of the laptops had internet access. After 30 minutes:

...participants responded to both factual-recall questions (e.g., “Approximately how many years ago did the Indus civilization exist?”) and conceptual-application questions (e.g., “How do Japan and Sweden differ in their approaches to equality within their societies?”) about the lecture...

In terms of results, participants who took notes by hand wrote significantly less than those using laptops, and wrote fewer verbatim notes. There was no statistically significant difference in terms of factual-recall question performance, but students who took notes by hand did significantly better than laptop users on conceptual-application questions.

In the second study, the authors ran a similar task but this time with three groups: (1) note-taking by hand; (2) note-taking using a laptop; and (3) note-taking using a laptop, but this third group was specifically told to take notes in their own words. The results were similar - the group taking notes by hand performed best, and the 'non-intervention' laptop group (group 2) performed worst. The group note-taking on laptops that was told to take notes in their own words performed somewhere in-between (but not statistically significantly differently from either of the other two groups).

In the third study, the authors repeated the first study but tested recall after one week (instead of 30 minutes), and allowed some of the participants to spend 10 minutes before the test studying their notes. So in this case there were four experimental groups: (1) handwritten notes without studying; (2) laptop notes without studying; (3) handwritten notes with studying; and (4) laptop notes with studying. In this study, participants who took handwritten notes and had the opportunity to study performed better than the other three groups, both in factual questions and conceptual questions.

The authors conclude:

Although more notes are beneficial, at least to a point, if the notes are taken indiscriminately or by mindlessly transcribing content, as is more likely the case on a laptop than when notes are taken longhand, the benefit disappears. Indeed, synthesizing and summarizing content rather than verbatim transcription can serve as a desirable difficulty toward improved educational outcomes... For that reason, laptop use in classrooms should be viewed with a healthy dose of caution; despite their growing popularity, laptops may be doing more harm in classrooms than good.

So, perhaps students would be better off without their laptops in class, even if they are using them diligently for note-taking rather than watching the NBA finals (as I saw one student doing in class last semester).

[HT: Marginal Revolution]

Banning the bottle leads to more bottles sold

Every now and again there is a call to ban bottled water from my university campus. The call comes from the environmental lobby, and points to the amount of plastic bottles entering the waste stream (even though recycling is available and fairly prominent on campus). The expectation is that, if bottled water were not available, students and staff would make use of refillable bottles and/or bring their own water from home.

Last month Timothy Taylor pointed out an interesting and pertinent article from this month's American Journal of Public Health, by Elizabeth Berman and Rachel Johnson (University of Vermont, Burlington), entitled "The Unintended Consequences of Changes in Beverage Options and the Removal of Bottled Water on a University Campus" (gated; I don't see an ungated version anywhere). The authors evaluate the impact of two policy changes at the University of Vermont at Burlington, that were designed to improve the health of the university community, and to reduce plastic waste:

First, in August 2012, all campus locations selling bottled beverages were required to provide a 30% healthy beverage ratio in accordance with the Alliance for a Healthier Generation’s beverage guidelines. Then, in January 2013, campus sales locations were required to remove bottled water while still maintaining the required 30% healthy beverage ratio.

Fortunately the authors didn't attempt to disaggregate the effects of the healthy beverage ratio separately from the ban on bottled water - this would have been difficult to do, given that there could be other differences in beverage consumption between fall and spring (the baseline data were collected in the fall 2012 semester, and the final data in the fall 2013 semester, with data from the spring 2013 semester occurring in-between the introduction of the healthy beverage ratio and the ban on bottled water).

The results they obtain are especially interesting, and illustrate the unintended consequences of the combined policies:

Per capita shipments of bottled beverages did not change significantly between spring 2012 and spring 2013 (P=.71) but did increase significantly from 21.8 bottles per person in fall 2012 to 26.3 bottles per person in spring 2013... Calories, total sugars, and added sugars shipped per capita also increased significantly between fall 2012 and spring 2013...

So to summarise, the number of plastic bottles going to landfill increased following the ban on bottled water. And to make matters worse, consumers were purchasing more unhealthy beverage options. This was in spite of the best efforts of the authorities:

The university made several efforts to encourage consumers to carry reusable beverage containers. Sixtyeight water fountains on campus were retrofitted with spouts to fill reusable bottles, educational campaigns were used to inform consumers about the changes in polity, and free reusable bottles and stickers promoting the use of reusable bottles were given out at campus events.

The university authorities assumed that by banning bottled water, consumers would switch to tap water from water fountains. However, tap water need not be the beverage option that provides the next highest utility (satisfaction) for the consumer - for many consumers, it appears to be flavoured water (which was not affected by the ban), sugar-free drinks, or sugar-sweetened drinks. As Timothy Taylor explains in his blog post:

This finding is not an enormous surprise, because a reasonable amount of survey data suggests that many people switch from sugar-sweetened drinks to bottled water, and that if bottled water isn't available, many of them will switch back.

Perhaps the university should wind back the ban on bottled water and stick with the healthy beverage ratio alone - at least through a spring semester so that it can be compared like-with-like to examine its effects. And perhaps my university should take note the next time this sort of policy is considered.

The winner's curse and the Auckland housing bubble

The New Zealand Herald ran a couple of stories on house auctions in Auckland this week. In the first, Ray White Mission Bay owner Wayne Maguire gave his tips on how to win an auction:

Last week Mr Maguire staged a How to Bid and Buy at Auctions seminar for more than 130 house hunters, providing tips on the auction process designed to make bidders more competitive and help blow rivals out of the water.

Auckland property sales are dominated by auctions, with nearly half the region's May transactions done under the hammer.

Mr Maguire said competition for scarce property listings was cut-throat and serious buyers needed to turn up mentally focused and ready to perform...

Mr Maguire said it was important to have a financial plan and know your limit.

Buyers should jot down a running list of price thresholds - starting from the likely opening bid (usually around CV) and ending with the final price limit they are prepared to pay.

"You've got to stop when you hit your limit."

In the second article, Lane Nichols reported on a subsequent auction, and quoted one bidder:

Ms Flavell-Neville agrees the auction process pits buyers against each other, with the potential to induce reckless spending.

"You want to be the winner. I think I would have kept going for a bit longer just to win. But you have to have a hard limit.

"From what we've seen it seems the less people who are bidding the better because they just egg each other on."

The standard English auction really is a suckers' game. They're great for sellers, but not so much for buyers. Why? Because of the winner's curse.

Consider a group of potential buyers for a particular house. Rational buyers with the same preferences would all have the same valuations (or willingness-to-pay) for the house. However, not all potential buyers have the same preferences, and the potential buyers may make random errors in determining their valuations for the house, so all of the potential buyers will have different willingness-to-pay for the house. For buyers with similar preferences, these differences in willingness-to-pay arise randomly - some will overestimate the quality (and value) of the house, and some will underestimate. Probably, if we believe in the wisdom of crowds, the 'true' value of the house will be close to the average willingness-to-pay of all of the potential buyers.

Now take this group of potential buyers and subject them to an English auction for the house. In the English auction format, bids start low and each subsequent bid increases the price that the house would be sold for. The buyers who have underestimated the quality (and value) of the house will quickly drop out of the auction, because the bids will soon exceed their willingness-to-pay for the house. However, the buyers who have overestimated the quality (and value) of the house have an incentive to remain in the auction longer, since higher prices will remain below their willingness-to-pay. The chances are high that, if there are enough potential buyers bidding in the auction, the eventual winner will have overestimated the quality (and value) of the house, and hence will pay too much for their house relative to its 'true' value, making them worse off. In other words, as the bidder above is quote, when there are more bidders it is more likely that some of them have overestimated the value of the house, and they will egg each other on to higher prices - not good for the eventual winner.

The solution is to add one further tip to Wayne Maguire's set of tips - in your list of price thresholds, your final price limit you should be prepared to pay should be somewhat less than the maximum you are willing to pay for the house (engaging in what is termed 'bid shading'). This would help ensure you aren't cursed as a winner.

One final important point - if (as stated in one of the articles) around half of Auckland houses are being sold at auction, and auctions are well-attended with many bidders, then many Auckland houses are being sold subject to the winner's curse. So their selling price of many houses will be above their 'true' value. That means that conventional measures of the value of Auckland housing, such as the median house price, will be based on house sales that include all of these 'cursed' homes. Thus the median house price will most likely tend to overstate the value of houses in Auckland.

That's not the end of this story though. Rational buyers have complete information about the house they are buying and will make their assessment of its value (and their willingness-to-pay) based solely on the house's characteristics (location, construction quality, number of bedrooms and bathrooms, land area, views, etc.). However, most of us are subject to an anchoring bias when valuing things we want to buy - they first price we see will tend to affect our valuation (and our willingness-to-pay). Chances are that potential house buyers will have the median house price for an area (or for Auckland as a whole) in mind when they evaluate their willingness-to-pay for houses they are looking at (it would be hard not to - the median house price is probably the most widely reported measure of housing value, and if you're a house hunter it would be hard to avoid seeing the median house price). So future buyers are likely anchoring their valuations on over-estimated median house prices. Some of them will further over-estimate, win the subsequent auction (with associated winner's curse), and boost the median house price further. Rinse and repeat. Could the winner's curse and subsequent anchoring of willingness-to-pay explain part of the housing price bubble in Auckland?

Why study economics? PhD edition...

Back in January, Scott Jaschik reported in Inside HigherEd about the robust market for economics PhD graduates in economics in the U.S.:

In the 2014 calendar year, the American Economic Association listed 3,051 jobs, an increase of 9.4 percent from the total in 2013. (The AEA has made slight changes in its calendar, but has tried to account for them to make year-to-year comparisons possible, if likely off by a few jobs.) While many academic jobs aren't listed with disciplinary groups such as the AEA, the trends in these totals are seen as a reliable indicator on the state of the job market in the field.

This is the first time in 14 years covered by the association's report that the total has exceeded 3,000 jobs. Last year's total of 2,790 represented a 4.2 percent drop from the previous year.

Now it turns out that an economics PhD is also one of the most attractive graduate programmes in the U.S., as reported on the 80000hours.org website:

An economics PhD is one of the most attractive graduate programs: if you get through, you have a high chance of landing a good research job in academia or policy – promising areas for social impact – and you have back-up options in the corporate sector since the skills you learn are in-demand (unlike many PhD programs).

80000hours also notes that the PhD in economics is attractive because of the excellent job prospects, advocacy potential, high degree of autonomy, and:

You gain a broad set of tools for understanding how the social world works, which is helpful for evaluating causes and interventions. This may help you better evaluate your future career options to have more impact.

I'd second that, and add that you have the chance to work on some really cool projects. I did my PhD here at Waikato, not in the U.S., but while completing my thesis I also got to work on projects on productivity and economic growth in New Zealand vs. Australia and Ireland, landmine clearance in Thailand (gated), air pollution preferences, and developing projections of subnational population in New Zealand. An economics PhD can be a really rewarding experience.

[HT: Marginal Revolution]

Previously on this blog:

• Why study economics? It could make you rich...
• Why study economics? Sheepskin effects edition
• Why study economics? NZ graduate earnings edition
• Why study economics?

Matthew Goodson agrees with me on stamp duties

Back in May I wrote a post on house prices in Auckland. My conclusion was that there should be a geographically-limited stamp duty (or a land sales tax) on house sales in Auckland, excluding owner-occupiers buying their first home. It would capture foreign purchasers (not covered by the RBNZ rules), and include both speculators and investors, and would be hard to avoid. Key to my suggestion though was ring-fencing the tax income, to be used to increase housing supply and supporting infrastructure development like water and roading.

In the New Zealand Herald this morning, Matthew Goodson (managing director at Salt Funds Management) wrote a long piece on "What to do about Auckland's housing bubble". He writes:

A simpler way to deal with investors' privileged tax position would be to re-introduce stamp duty on any house that is not purchased by an owner-occupier. The duty could be controlled by the RBNZ so that the rate does not move with the election cycle. It might even be made region specific. Whether levied on the buyer or seller or both, it would lower investors' expected return and should therefore lower the price they are willing to pay for a house.

A stamp duty also has the happy side-effect of raising income which could be used to build infrastructure to support new supply. Australian State Governments are raking in stamp duty proceeds at present and this is giving them a far greater capability to invest for growth than is the case in Auckland.

Which is pretty much what I said (it's good to hear someone else say the same thing, even if it makes you vulnerable to confirmation bias). Goodson concludes that "Stamp duty, possibly on investors rather than all dwellings, would tick many boxes". So, again I wonder why this possibility has not seen much airing in the policy debate on Auckland housing affordability?

More from my blog on Auckland housing:

• Bring back stamp duty for Auckland!
• Out-of-control rent increases in Auckland - why?
• Housing policy: Subsidy vs. Supply

Why kids should play more Minecraft, but only on PC

Video games are often portrayed as dulling the senses and making gamers dumber. However, a recent paper in the journal Economic Inquiry (gated, earlier ungated version here) by Agne Suziedelyte of Monash University might have just busted that myth.

Suziedelyte argues that:

In order to win a video game, players need to plan their actions, find relevant and discard irrelevant information among all information given to them, and remember their previous actions. Thus, video game playing is most likely to improve such skills as problem solving, abstract reasoning, pattern recognition, and spatial logic, which are part of fluid, or general, intelligence...

In the paper Suziedelyte uses data from the Child Development Supplement to the Panel Study of Income Dynamics to investigate "how game playing affects two skills, the ability to solve practical mathematics problems (mathematics reasoning) and the ability to correctly read English words (reading recognition)". She employed a variety of techniques to overcome endogeneity (time spent playing video games might be correlated with other determinants of cognitive skills), and measurement error in the time spent playing video games.

While similar to the paper I discussed yesterday where the sign on some statistically insignificant coefficients was discussed (when they are not different from zero), in the preferred model specification an additional hour spent playing video games was found to be associated with mathematics reasoning tests scores that were on average higher by 9.3% of a standard deviation. To put this in context, the effect was similar in magnitude to an additional hour spent on "educational activities" (like school or homework), which was associated with scores on average 9.1% of a standard deviation higher. Importantly, video games had no statistically significant effect on reading recognition (a placebo test), which suggests that more video gaming affects problem solving specifically and not cognitive skills more generally (and allays concerns about omitted time-varying variables driving the results).

Before you encourage your kids to spend all day constructing elaborate replicas of Hogwarts using Minecraft, consider these two additional results. First, there were diminishing returns to time spent on video games:

The estimated effect on an additional hour of video game playing on mathematics reasoning ability is largest (21.7% of a standard deviation) when a child does not play any video games... Video game time is found to no longer affect mathematics reasoning ability, when the number of hours played reaches 5.5 hours per day.

So, in other words limit children's video game time to most of their waking, non-school hours. Second:

The effect of computer game playing is estimated to be 6.2% of a standard deviation (significant at the 1% level), whereas the effect of console game playing is smaller (1.1% of a standard deviation) and not significantly different from zero. The difference between the two effects is statistically significant at the 5% level.

So, make sure your children are playing Minecraft on PC, not on XBox.

[HT: Marginal Revolution, back in April]

More sex might increase happiness, but not if an economist tells you to

I couldn't let this one pass without comment. Quartz highlighted an article in the next issue of the Journal of Economic Behavior and Organization by George Loewenstein, Tamar Krishnamurti, Jessica Kopsic, and Daniel McDonald (all from Carnegie Mellon University), entitled "Does increased sexual frequency enhance happiness?" (gated, I don't see an ungated version anywhere).

The literature to date on the relationship between happiness and sexual activity has been purely correlational - no study has been able to demonstrate the causal links between sexual activity and happiness. Understanding the difference is important, because if we observe that happier people have more sex this could be caused by any of three things: (1) more sex makes people happier; (2) happier people tend to have more sex; or (3) some other variable both increases happiness and increases sexual activity (Loewenstein et al. suggest 'liking for sex' as one candidate variable). Alternatively, even if the correlation is observed maybe there is no relationship between sex and happiness, and the observed correlation arises because of random chance (although given the number of studies showing this correlation, this explanation seems the least plausible). So, teasing out the causal effects is important in terms of working out which of these alternative explanations is most correct.

Loewenstein et al. set out to do this using a field experiment:

Couples... were then stratified by age and sexual frequency before being randomized to one of two groups: the control group, who received no instructions on sexual frequency during the 90-day experimental period, and the treatment group, who were asked to double their baseline weekly frequency of sexual intercourse.

The main outcome variable was a 'positive mood scale', which was composed of a number of positive and negative emotion items from the PANAS (Positive and Negative Affect Schedule), combined into a single variable. The expectation is that, if more sex increases happiness then the treatment group should be happier at the end of the treatment period than the control group.

Loewenstein et al. found that the treatment group did increase their sexual frequency, but did not quite double frequency (sexual frequency increased by 40% on average). So far, so good. However, in terms of happiness:

...those induced by the experimental condition to have more sex displayed a lower mood during the course of the experiment than those in the control group. The point estimate of the negative impact of treatment condition on mean mood was 0.2 S.D.s.

So, you might conclude that if an economist tells you to have more sex, this makes you less happy. However, that conclusion would be based on incomplete analysis, and I have to raise one gripe with this paper. In further analysis, they go on to state:

Specification IV controls for years married, a key variable that was imbalanced between the two groups. With the addition of this control, the coefficient on treatment is still negative, but no longer significant at the 0.1 level.

If a variable is not statistically significant, then by definition you can't tell whether the 'true' coefficient value is positive or negative (or zero), and hence the sign of the coefficient is meaningless. So, rather than concluding that the treatment (more sex) made participants less happy, it is more correct to conclude that it had no significant effect. Thanks to my former colleague Bridget Daldy, who drummed that point into me over many years.

The overall conclusion then? More research needed. One last point: Loewenstein et al. have offered to provide all of the data from their research to anyone interested in investigating further. I don't have the time, but it might make for an interesting honours or Masters dissertation project...

[HT: Marginal Revolution]

The principles of (behavioural) economics, and Gary Becker as a teacher

The annual Papers and Proceedings issue of the American Economic Review (gated) is always a treasure trove of interesting papers. This year was no exception, but two papers in particular caught my eye.

The first was "Principles of (Behavioral) Economics", by David Laibson (Harvard) and John List (University of Chicago). Laibson and List, along with Daron Acemoglu (MIT) have a new principles textbook that integrates behavioural economics throughout (I have just received a review copy of the text, but haven't had a chance to have a decent read of it yet). However, rather than outline an entire principles-course-worth of material, this article outlines six key principles that can be covered in one (or two) lectures. The principles are:

1. People try to choose the best feasible option, but they sometimes don't succeed;
2. People care (in part) about how their circumstances compare to reference points;
3. People have self-control problems;
4. Although we mostly care about our own material payoffs, we also care about the actions, intentions, and payoffs of others, even people outside our family;
5. Sometimes market exchange makes psychological factors cease to matter, but many psychological factors matter even in markets; and
6. In theory, limiting people's choices could partially protect them from their behavioral biases, but in practice, heavy-handed paternalism has a mixed track record and is often unpopular.

Laibson and List illustrate each concept with interesting examples. One of the key things they point out though, is that behavioural economics is not a replacement for traditional economic theory, it complements the traditional theory.

I was grateful for reading the paper, because it helped me to work out a puzzle that arose during the last University of Waikato Open Day. I gave the economics mini-lecture for Open Day, and as part of it I ran a short experiment designed to illustrate the gains from trade. In the experiment, I randomly give a small (free) gift to each of ten volunteers from the audience, then ask each of them to rate their gift on a scale from zero to ten. The total of the volunteers' ratings give a measure of welfare gain from the gifts. Then I invite the volunteers to trade their gift with any of the other volunteers. Usually around half of them exchange gifts. Then we re-rate the gifts for those who made an exchange, and voila! An increase in welfare (thus neatly illustrating the gains from trade). However, this time the experiment didn't go to plan, as none of the volunteers wanted to exchange their gifts. I should have realised at the time it was the result of the endowment effect. Making an exchange of gifts entails both a loss (giving up the original gift) and a gain (the exchanged gift) for each volunteer, but since losses are valued much higher than gains it takes a substantial improvement for both volunteers before a trade will make both of them better off. Mystery solved.

Anyway, if you have access to the Laibson and List paper (or their textbook with Acemoglu) I encourage you to read it.

The second paper that caught my eye was Kevin Murphy's (University of Chicago) article on "Gary Becker as a Teacher" (also gated). Also well worth a read if you have access - in addition to being a leading light in applying economics to a wide range of social phenomena, Becker was clearly an inspirational teacher as well. Murphy concludes his paper by saying:

In general, in many ways Becker taught a very traditional view of economics. He emphasized the maximization of stable preferences, the importance of understanding the underlying constraints, and the incorporation of markets into virtually every analysis. But he did it in his own special, unique, and most importantly, unapologetic way. He taught a course that was pure economics. It just took longer for many of us to realize that such an unabashed approach to economics was the way to go. It is a tremendous loss that future cohorts of students will not be able to get the full Becker treatment.

Read more on Gary Becker through the links here.

The Super Rugby final and ticket scalping

With the Super Rugby final coming up this weekend, ticket scalping has been in the news again. This New Zealand Herald editorial says:

Steven Joyce, the Economic Development Minister, has made it clear that he is unhappy tickets for the Super 15 final in Wellington are fetching up to $1500 online. He is not alone. It is never pleasant to watch scalpers cash in on the desperation of genuine fans who missed out during regular ticket sales. But Mr Joyce does not favour changing the law. That, he says, would be an over-reaction. Rather, event promoters should be thinking more about how to ensure tickets reach the public.

Ticket scalping is an old favourite of economics teachers, since it helpfully illustrates the concepts of consumer and producer surplus, and what happens when there is excess demand. Consider the market for tickets to the Super Rugby final in the diagram below. The supply of tickets S0 is fixed at Q0 - if the price rises, more tickets cannot suddenly be made available, because the capacity of Westpac Stadium is 34,500 - that is the maximum number of tickets that can be sold, regardless of price (note the diagram assumes that the marginal cost of providing tickets up to Q0 is zero).

Demand for tickets is high (D0), leading to a relatively high equilibrium price (P0). However, tickets are priced at P1, below the equilibrium (and market-clearing) price. At this lower price there is excess demand for tickets - the quantity of tickets demanded is Qd, while the quantity of tickets supplied remains at Q0.

At this lower price, there are many people who want to buy tickets, but there are not enough tickets to go around. There are some people who are willing to pay more than P1 for a ticket, but have missed out on purchasing one. It is that fact that encourages the actions of ticket scalpers. The scalper purchases a ticket at the low price (P1), and finds someone who was willing to pay a higher price to sell the ticket to, pocketing the difference in prices as profit. If there are enough scalpers in operation, then the price the scalpers receive will eventually get to P0.

Moreover, the actions of the ticket scalpers doesn't change total welfare at all. It simply re-distributes it. With the low ticket price P1, the consumer surplus (the difference between the price the consumers are willing to pay, and the price they actually pay) is the area ABCP1. Producer surplus (essentially the profits for the rugby union) is the area P1CDO. Total welfare (the sum of producer and consumer surplus) is the area ABCDO. At the higher price P0 due to the actions of scalpers (buying at P1 and selling at P0), the consumer surplus decreases to ABP0, while producer surplus remains unchanged. The scalpers gain a surplus (or profit) of the area P0BCP1, and total welfare (the sum of producer and consumer surplus, and scalper surplus) remains ABCDO. So the ticket scalpers don't reduce total welfare - their actions don't result in a deadweight loss.

So there is no change in economic welfare, but isn't the action of scalpers unfair? Perhaps, but notice that the actions of the scalpers will eliminate the excess demand for tickets. At the higher price P0, the quantity of tickets demanded is equal to the quantity of tickets supplied - no one who wants to buy a ticket at the higher price is missing out on a ticket. And scalpers wouldn't want to raise the price above P0, or else they would be left holding tickets that they are unable to sell. You might think this is unfair on consumers, but then you probably also think that the high price of milk is unfair, the high price of petrol is unfair, the high price of electricity is unfair, etc.

The reality is that when there is excess demand, prices increase. You might be thinking that the price of Super Rugby tickets is set, and it is true that the face value ticket price is set by the rugby union. But you need to take into account the difficulty of getting one of the scarce tickets. If it takes a 15-hour overnight stay to get your hands on a ticket, you need to factor that into the cost of a ticket. The cost of a ticket is clearly already much more than the face value ticket price. And given that it is becoming increasingly popular to hire others to sit in queues for you (see my earlier post on this here), you can't argue that it is necessarily fairer because the time cost is being paid by the person who ultimately uses the ticket.