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