Wednesday, 31 March 2021

The market demand for a public good, and the optimal quantity to provide

The market demand for a good or service is determined by the sum of the demands for the good or service from each individual consumer. Essentially, you add up the individual consumers' demands to determine the market demand. For a rival good (a good where one person's consumption reduces the amount that is available for everyone else), it is as simple as adding up the quantity demanded at each price. So, if there are only two consumers, and at price P1 the first consumer demands Q1 units and the second consumer demands Q2 units, then market demand at the price P1 is (Q1+Q2).

However, when a good is non-rival, it is no longer quite that simple. Non-rival goods are those where one person consuming the good does not reduce the amount of the good or service available for everyone else. Disney+ is one example. If one person pays for a Disney+ subscription, that doesn't reduce the amount of Disney+ subscriptions that are left for other people. Another example of a non-rival good is a public good. Public goods are goods that are non-rival, and non-excludable (non-excludable means that if they are available for anyone, then they are available for everyone - we'll come back to this point later). Examples of public goods include street lights, or policing.

Now, if we want to know the market demand for street lights, we can't add up the quantity demanded at different prices. That's because two people can consume the same light - remember, it is a non-rival good. The market demand for a non-rival good is found by adding up the marginal private benefit that each consumer gets from the good, to give you the marginal social benefit.

To see how this works, consider the diagram below. There are three people (A, B, and C), and their marginal private benefits for street lights are shown by MPBA, MPBB, and MPBC respectively. The diagram is quite busy, so let's break it down and note what it shows. Person A benefits a lot from street lights. They receive a marginal benefit of P5 for the first little bit of street lighting, and continue to benefit from street lighting all the way out to a quantity of Q4 (this is their marginal private benefit curve, MPBA). Person B benefits less than Person A. The receive a marginal benefit of P3 for the first little bit of street lighting, and continue to benefit from street lighting up to a quantity of Q3 (this is their marginal private benefit curve, MPBB). Finally, Person C receives a marginal benefit of P4 for the first little bit of street lighting, and continue to benefit from street lighting only up to a quantity of Q2 (this is their marginal private benefit curve, MPBB).

What does that mean for the marginal social benefit - the benefit of street lighting to society? The first little bit of street lighting provides Person A with a marginal private benefit of P5, Person B with a marginal private benefit of P3, and Person C with a marginal private benefit of P4. So the marginal social benefit of the first little bit of street lighting is (P3+P4+P5), as shown in the bolder line on the diagram. Now, as the quantity of street lighting increases, the marginal private benefit for each person decreases, until we get to Q2. At that quantity, the marginal private benefit for Person C has fallen to zero. At that quantity, the marginal private benefit for Person A has fallen to P4, and the marginal private benefit for Person B has fallen to P1. So, marginal social benefit at the quantity of Q2 is equal to (P1+P3) - notice that is also equal to P4 (for no reason other than it made it a bit easier to draw the diagram!). Moving on, once we get to the quantity Q3, the marginal private benefit for Person B has also fallen to zero. At that quantity, the marginal social benefit is going to be made up only of the marginal private benefit to Person A, which is equal to P2. And at quantities up to Q4, the marginal social benefit curve is exactly the same as Person A's marginal private benefit curve, MPBA.

Now, we are in a position to consider what happens if we offer street lighting for sale. First, we need to know the price of street lighting. Let's assume that the cost of each unit of street lighting is constant, and equal to P4. That is represented by the marginal social cost curve (MSC) on the diagram below. If we set the price of street lighting equal to its cost (P4), then what would happen? At that price, notice that both Person B and Person C would choose not to pay for street lighting, because the price is above (or equal to) the highest marginal benefit that they receive for the first little bit of street lighting. They would simply opt out of paying for street lighting. Person A is willing to pay more than P4, but they will only be willing to pay for Q1 units of street lighting. The market will provide Q1 units of street lighting, entirely paid for by Person A.

That is a problem. The optimal quantity of street lighting is the quantity where marginal social benefit is equal to marginal social cost. That's the quantity Q3. This market isn't going to provide enough street lighting to maximise welfare for society. The problem here is that the good is non-excludable - you can't easily force Person B or Person C to pay for it. If the street lighting is available to anyone, then it is available to everyone. Person B and Person C will benefit from the street lighting paid for by Person A, and won't feel the need to pay for any additional lighting themselves. Person B and Person C are free-riders. This is the reason why public goods are usually provided by the government. [*] The private market would not provide enough. Consider what would happen if the cost of street lighting was higher than P5. Even though marginal social benefit is higher than that, if the cost (and price) of street lighting was higher than P5, nobody would be willing to pay for it!

Finally, let's consider the economic welfare implications of the public good in this example. If the market provides only Q1 units of street lighting, the consumer surplus (the difference between what society is willing to pay for the good, and what is actually paid for the good) is equal to the area ABDC. You may wonder why the consumer surplus isn't equal to the area FDC, which is the surplus that Person A (who is the only one paying for street lighting receives). [**] Remember the free riders Person B and Person C though - they receive benefit (and consumer surplus) from the street lighting, even though they aren't paying anything towards it. So, the consumer surplus is ABDC, not FDC. Moving on, there is no producer surplus (because price is equal to cost for every unit of street lighting). So, total welfare is equal to the area ABDC.

If instead the government provides street lighting, and provides the optimal quantity Q2, then consumer surplus increases to the area AEC. Again, because there is no producer surplus, the area AEC also represents the area of total welfare. There are welfare gains from the government providing street lighting. Or, another way of thinking about it is that if the market was providing street lighting, total welfare would be lower by the area BED - that is the deadweight loss of private provision of this public good.


[*] Of course, the government doesn't necessarily need to provide the public good itself. It can contract and pay a private firm to provide the lighting, up to a quantity specified by the government.

[**] This important question was raised in my ECONS102 class yesterday, so I thank them for the inspiration to address the point.

Monday, 29 March 2021

A lack of supply is not going to increase demand for timber

One of the most abused sayings in folk economics is that "supply creates its own demand", which actually dates back to John Maynard Keynes' summary of Say's Law in his 1936 book The General Theory of Employment, Interest and Money. There are two problems with this saying. The first is that applying the saying to the supply and demand of a single good isn't quite faithful to what Jean-Baptiste Say actually wrote, because Say was really talking about the whole economy. [*] Second, most people interpret Say's Law as supporting a build-it-and-they-will-come approach to business. The ruins of many businesses can trace their origins to a mistaken belief that if you have a cool idea, people will automatically buy it. The number one rule in business is that you actually need to provide something that people value.

Anyway, today's example from the New Zealand Herald isn't quite Say's Law, but it's probably worse:

Carter Holt Harvey has stopped supplying structural timber to Bunnings, ITM and Mitre 10.

Master Builders president Kerry Archer said the move came as a surprise, and was probably because the export market was more lucrative.

Archer said while Carter Holt Harvey was not the only timber supplier, it could mean construction projects cost more as builders try to source supplies elsewhere...

"Timber's already gone a couple of times this year. Once again it's supply and demand, so if there's a lack of supply then demand goes up and unfortunately costs will go up with it."

It is supply and demand, but not in the way that Archer describes. A reduction in supply will not on its own cause demand to increase. At least, it won't cause demand of the same good to increase. Reducing the supply of structural timber will increase the price of structural timber, and that might cause builders to buy more steel framing, which will increase the demand for steel framing. But it's not going to increase the demand for structural timber. And that's supply and demand.


[*] Say, in his 1803 book Traité d'économie politique (A Treatise on Political Economy), wrote (in French, of course, but this is the English translation):

A product is no sooner created, than it, from that instant, affords a market for other products to the full extent of its own value.

Notice that this is about supply of one good creating demand for other goods, which is not how many people interpret it now.

Saturday, 27 March 2021

The beauty premium for economists

I've written a number of times about the beauty premium in the labour market (see the list of links at the end of this post). There is robust evidence that more attractive people get paid more. The evidence is neatly summarised Daniel Hamermesh's excellent book Beauty Pays (that I reviewed here).

In the latest contribution to this evidence base, Galina Hale (University of California, Santa Cruz), Tali Regev (Interdisciplinary Center Herzliya) and Yona Rubinstein (London School of Economics) look at the effects of attractiveness on the careers of recent PhD graduates from top PhD programmes in the U.S. They don't have data on these economists' earnings, but they are able to look at the quality of PhD programme they graduate from, where they get their first job (and later jobs), and the quality of their academic output (based on citations). Specifically, they have data on 752 PhD graduates from the top ten economics PhD programmes in the U.S, who graduated over the period from 2002 to 2006, and follow them up to 2017. They find that:

...appearance matters for individuals' academic success in persistent ways. First we observe that among the students in top PhD programs women are more attractive than men, suggesting that attractive women are more likely to get selected into these elite programs. For subsequent career outcomes we find that attractive individuals are more successful than plain looking individuals. They are more likely to be placed in higher-ranking PhD institutions, and upon graduating, they are more likely to be find jobs in the private sector than jobs in academia or the public sector. Within academia, attractive-looking PhD graduates are also more likely to be placed at higher-ranking institutions for the first job as well as subsequent jobs. Appearance doesn't only predict job placement but, more surprisingly, it also predicts actual research productivity on the job. More attractive economists are cited more overall and per publication. All these effects are rather substantial in magnitude, with one standard deviation increase in attractiveness score increasing the probability of an above-median outcome of job placement and citation count by 7-9 percentage points, depending on the outcome considered.

The significant effect on citations is the most difficult to understand theoretically, since in theory attractiveness shouldn't affect the underlying quality of the research. However, Hale et al. offer a suggested explanation, that:

...attractive people become more confident and therefore might be more likely to solicit constructive comments, and, as a result, may produce higher quality papers that are cited more. Due to higher confidence, they might be more likely to submit their papers to conferences and therefore their papers will get higher exposures. They might also be more charismatic when presenting their papers and therefore provide better marketing for their papers and, as \good presenters," might be more likely to be invited to seminars and future conferences.

All of that seems plausible, but I think we need some more research to demonstrate that this is the mechanism that underlies those results. It would also be interesting to know whether it applies to economists that are further down the pecking order, rather than just those who graduated from top-ten PhD programmes (I'm asking for a friend, really). In any case, add this research to the large (and growing) evidence for beauty premiums in labour markets.

[HT: Marginal Revolution]

Read more:

Thursday, 25 March 2021

Some notes on the NZ Government's new housing package

The big news in New Zealand this week was the announcement of the government's new housing package, which included:

  • A $3.8 billion fund to accelerate house building;
  • Extra support for first home buyers;
  • An extension of the 'bright-line' test to ten years, capturing a greater proportion of house sales within what is effectively a capital gains tax;
  • Removing tax deductibility of interest payments for residential landlords; and
  • Additional support for apprentices.

The goal of the package is to "increase the supply of houses and remove incentives for speculators, to deliver a more sustainable housing market".

The housing market is complex, and the problems associated with high house prices and rents defy simple solutions. A package was always going to be necessary, but the various parts of the package need to work in concert. Let's take a quick look through those five bullet points and think about the effects they might have on the housing markets. I say markets (plural) because the effects may be different on the market for homes (for owner-occupiers and investors) and on the rental market.

First, $3.8 billion to accelerate house building sounds good on the surface. However, remember that the government isn't a builder of houses, and that's not what this fund is for. The $3.8 billion is to fund infrastructure such as roads and water. This will (hopefully) make it less costly for local councils to zone additional land for development, and for developers to develop the land, since presumably it means that the developers will get to pay lower development contributions. At least, that's how I assume it will work, and if that's the case, then the costs of development will fall, and that should reduce the costs of newly built houses. Some of that reduction in cost will be passed onto new home buyers in the form of lower prices. However, if there is no change in development contributions, then any effect on new house prices is likely to be a lot smaller.

Lower house prices for new builds should lower house prices for existing homes as well, because the two types of homes are substitutes - if more people are buying new builds, there will be less demand for existing homes. Lower house prices mean lower costs for landlords (because their mortgage payments, as well as potentially insurance and rates, will be lower).

Second, extra support for first home buyers is going to undo some of the price effects of the infrastructure fund. Increasing home grants (as noted here) "from $85,000 to $95,000 for individuals and from $130,000 to $150,000 for two or more buyers" is essentially increasing the size of the subsidy for home buyers. Subsidies tend to push up prices, because more buyers are going to be looking for homes, and all the effects on prices noted above will work in reverse.

Third, the extension of the 'bright-line' test to ten years will make a difference at the margin for some existing home owners. They will be more reluctant to sell within ten years, if their home has been rented out at any time. This will reduce some speculator demand in the house market, and act to reduce house prices. However, most speculators were probably being captured by the previous five-year bright-line test anyway.

Fourth, removing tax deductibility of interest payments for residential landlords possibly has the biggest effect, and is considered by many people to be the most consequential of the changes (e.g. see here). This change will reduce the 'profitability' of being a residential landlord. Investors will want to get out of the market, shifting some houses out of the rental sub-market and into the owner-occupier sub-market. This will reduce house prices, but increase residential rents because landlords will now need to cover more expenses across the year as they will be paying more tax (or, more likely, paying tax as opposed to offsetting rental losses against their other income, or carrying losses forward to future years).

Alternatively, some landlords might seek to shift their residential properties into the commercial market, especially if they are zoned in mixed-residential or commercial zones. If you rent a house out to a business to use as an office and/or workshop, it is likely that this is a commercial rental and interest would still be tax deductible. Similarly, landlords might shift their houses onto Bookabach or AirBnB, accelerating an existing trend. That is particularly likely as borders re-open and tourist flows resume. Again, that makes the house rental commercial rather than residential and interest would likely be tax deductible. It will be interesting to see what (if anything) the government tries to do to prevent this type of activity. However, to the extent that landlords move houses out of the residential and into the commercial or short-term accommodation markets, the supply of rental houses will reduce and residential rents will increase.

Finally, additional support for apprentices will only have a small effect on the housing market. More apprentices now isn't going to make much difference to the number of builders and tradesmen available now, but will do in the future.

Overall, what can we conclude? On balance, house prices are probably going to fall a little, but it depends on how much demand is stimulated by first home buyers, and how many landlords look to exit the market, rather than shifting their houses into commercial uses. Residential rents are almost certainly going to increase.

Who really benefits from this package? The government wanted to help first home buyers, and this package will likely succeed. Property developers also benefit (if the development contributions that they would usually be required to pay are reduced).

Who is paying the costs? The taxpayers is picking up some of the cost, including the increased support for home buyers and apprentices, and the $3.8 billion infrastructure package. Landlords are going to be worse off due to their higher tax liability, and many of them will no doubt be seriously considering exiting the market. However, the group that may be most hurt by this package will be low income renters. Families whose income is too low to be able to contemplate saving a house deposit are almost certainly going to be paying higher rents.

Of course, as I said earlier, the housing market is complex, and there is a lot going on. The local and global economies are recovering from the pandemic, interest rates are currently at all-time lows, and international migration (inward and outward) has slowed to a trickle. None of those situations are going to persist forever, and as they change they will also have effects on the housing market. It will be interesting to see how it all plays out.

Monday, 22 March 2021

Relative prices and charging for park-and-ride in Wellington

The New Zealand Herald reported this morning:

A Wellington pro-transport lobby group is proposing to charge commuters to park at the city's bus and train stations - while some mayors say this will drive people away from public transport.

The proposal is part of the draft Regional Transport Plan 2021, aimed at increasing public transport usage by 40 percent within 10 years.

But Kāpiti Coast mayor K Gurunathan says while he understands the intention, adding an extra cost to park at train stations will backfire and deter commuters from using public transport anywhere on their journey.

He believes when the Transmission Gully State Highway 1 bypass opens in September more people will already be tempted to drive to Wellington. Without first providing better suburban buses to the railway stations, driving to Wellington will become the most attractive option...

But Living Streets Aotearoa spokesperson Mike Mellor says free carparks at train stations subsidise car-use, and the plan is the right idea.

"Park and ride is actually a very expensive way of increasing public transport usage by not that much. Even a full car park is barely a trainload of passengers, for instance.

"It costs a lot of money, it encourages local car use, and it means that that land is not available for productive purposes like transit-oriented development where you build productive buildings round transport hubs. And it also often makes a really unpleasant environment to access the station by any other means." 

The Kāpiti Coast mayor has this right, and Living Streets Aotearoa needs to check their assumptions. Relative prices matter. When the relative price (or cost) of something increases, we tend to do less of it. So, when you make park-and-ride more expensive (increasing its relative price), people will do less park-and-ride. They will do more driving to Wellington instead. That doesn't mean that every public transport user will switch to driving, only that some will now find it to be relatively less attractive to use the trains (because of the park-and-ride charges), and relatively more attractive to drive into downtown Wellington instead. To claim that free car parking encourages car use, when it probably encourages short car rides to the train station rather than long car rides into downtown Wellington, is misleading at best.

None of this is to say that the proposal to charge park-and-ride customers for parking isn't a good idea. Free car parking for public transport users seems to me to be a bit of an oxymoron. If you coupled charging for park-and-ride with better bus links to the train stations, you might end up in a situation where more people use public transport, rather than fewer. However, you could also have achieved that if you had better bus links and no charging for car parking. Again, it's all about relative prices, and better bus links lower the cost of getting to the rail stations (and the relative price of using public transport). It all rather depends on how much discouragement of public transport use you are willing to tolerate.

Rather than heading off into leftfield and arguing about land availability while seemingly ignoring how public transport users would respond, Living Streets Aotearoa would have been better to focus on the relative prices.

Sunday, 21 March 2021

Book review: Common Sense Economics

I have an intense dislike of the caricatures that some people have of economists as libertarian free-market fundamentalists. While it is true that there are some economists, possibly many, who genuinely believe that markets are the best and only way to organise economic activity, and the government should just get out of the way, that view is by no means universal.

So, I was extremely disappointed to read Common Sense Economics, by James Gwartney, Richard Stroup, Dwight Lee, and Tawni Ferrarini. A book with that title has set itself a high bar, but this book simply paints a picture of an economics that is out of touch with the importance of understanding market failure, the limits to rational behaviour, and the necessary role of government as more than simply an impediment to growth and prosperity. Nowhere is there a hint that the 'common sense economics' portrayed might not be the view of most economists.

To be clear, the economics in the book is not bad. It just fails to consider that the purely rational, full-information, complete-markets model of the world is not the one that we observe around us. While it is important for economists and economics students to understand the ideal model of markets, a common sense approach to economics needs to be grounded in the real world and recognise the limitations of the theory.

With the markets-first approach to economics given primacy, a very strong libertarian narrative persists throughout the book. Take this quote:

Government is a little bit like food. Food is essential, but when consumed excessively, it leads to obesity, energy loss, and other health-related problems. Similarly, when constrained within proper boundaries, government can be a powerful force for prosperity. But when it expands excessively and undertakes activities for which it is ill-suited, it undermines economic progress.

Now read that paragraph again, substituting "the market" in place of "government". It makes just as much sense, and is just as accurate. The authors present these sorts of libertarian ideas as 'common sense', but it mostly comes across as unconvincing. They could make a stronger case if they provided adequate support for some of their assertions, but that support is sorely missing. Take this example:

The political process will favor older firms, even if they are economically weak, over newer growth-oriented firms.

That might be true, but is left as an assertion with no empirical or even anecdotal examples, let alone theory, to support it. There are many similar examples.

The book isn't all bad, however. The last section is devoted to personal finance, and contains mostly good advice. However, it is an abrupt change of pace from the rest of the book and seems a little out of place. From my perspective, this section goes some way towards redeeming a book that otherwise seems to exist to paint an enormous target on economists. However, even though the personal finance section is good, there are much better books around that are devoted purely to personal finance.

Overall, I don't recommend this book for any lay reader who wants to understand economics. The only people who will get substantial value out of the book are those who (unfairly) want to paint economists as out of touch with the real world.

Saturday, 20 March 2021

Apple device repairs and customer lock-in

It seems somewhat obvious, but firms benefit from generating a long-term relationship with their customers. It is much less costly to retain an existing customer than to attract a new customer (e.g. see here). However, some firms take this to the next logical step - locking their customers into buying from them. That might be through long-term contracts that have penalties for switching to an alternative seller. Or it might be as simple as making the process of switching difficult or cumbersome. Or, as in the case of mobile phones, the customer just doesn't buy a new one very often, so they are locked in (for a while at least) once they have a new phone.

Once they have customers locked in, firms can then benefit from setting a higher price than they could get away with if their customers were not locked in. This is why mobile phone companies give away phones for free, or heavily subsidised, or why you can sometimes get a few months free on a new broadband internet connection (if you sign up to a 24 month contract). Alternatively, firms can benefit from selling complementary goods or services. Elevator companies may install elevators in new high-rise buildings for a low cost, because they know that they will benefit from 75 or more years of elevator maintenance fees (either by doing the maintenance themselves, or by having accredited services do the maintenance, and then charging for the accreditation).

A related example comes from mobile phones and repair services, as Ritesh Chugh (Central Queensland University) described in The Conversation last week:

If Apple and other tech companies have their way, it will only become harder to have our phones and other devices repaired by third-party businesses.

Smartphones and many other tech devices are increasingly being designed in ways that make it challenging to repair or replace individual components.

This might involve soldering the processor and flash memory to the motherboard, gluing components together unnecessarily, or using non-standard pentalobe screws which make replacements problematic...

The right to repair refers to consumers’ ability to have their products repaired at a competitive price. This includes being able to choose a repairer, rather than being forced by default to use the device manufacturer’s services.

But it seems Apple doesn’t want its customers to fix their iPhones or Macbooks themselves. The company has lobbied against the right to repair in the United States and has been accused of deliberately slowing down iPhones with older batteries.

Opposition against the right to repair from tech companies is to be expected. Cornering consumers into using their service centres increases their revenue and extends their market domination.

In its defence, Apple has said third-party repairers could use lower quality parts and also make devices vulnerable to hackers.

It also defended its battery warning indication as a “safety” feature, wherein it started to alert users if their phone’s replacement battery hadn’t come from a certified Apple repairer. 

Apple can scream 'protecting our customers from hackers and unsafe practices' as much as it likes. This is a clear case of locking customers into buying repair services only from Apple, or accredited repairers. And as if to illustrate this point further:

Apple has hiked its repair charges for iPhone 12 by more than 40%, compared with the iPhone 11. It is charging more than A$359 to fix an iPhone 12 screen outside of warranty and A$109 to replace the battery.

There can be nothing better than selling complementary services to locked-in customers, and charging them a premium price for the privilege. No one would argue that Apple isn't a savvy business operator - extracting the maximum value from Apple customers is their business strategy.

Read more:

Thursday, 18 March 2021

The Financial Markets Authority doesn't understand basic barriers to entry

Market power is the ability of a seller (or sometimes a buyer) to have some control over the price. At one extreme, a seller in a perfectly competitive market has no market power at all, because there are so many other sellers all selling the same good or service, that the firm couldn't raise its price without losing all of its customers. At the other extreme, a monopoly has a high degree of market power, because the consumers have no other options buy to buy from the monopoly firm, if they really want the good or service. The monopoly firm can raise its price up to the point where it is maximising profits - a much higher price than the perfectly competitive firm would receive.

Sellers can get market power in various ways. One is to sell a differentiated good or service - something that the consumers perceive as different from other goods or services. That leads to a market that we refer to as monopolistically competitive, and the sellers in that market will have a small amount of market power.

To get a lot of market power, the seller would want to be a monopoly - the sole seller of its good or service, which has no close substitutes. To become (and remain) a monopoly, there needs to be some barriers to entry into the market, that prevent other firms from entering the market and competing. If there are no barriers to entry into the market, then a highly profitable monopoly seller would find that other firms enter their market and sell in competition with them, driving the price (and the seller's profits) down.

Barriers to entry can arise in various ways, one of which is where the government grants a firm an exclusive right to sell the good or service. Patents are a good example of this type of barrier to entry. The existence of a patent means that only the patent holding firm can sell the patented good, and other firms can't compete by selling the same product (although, they might sell similar products).

Another way that the government can create a barrier to entry is through occupational licensing. There are some occupations (dentists, doctors, nurses, teachers, etc.) where you have to be licensed in order to operate (literally, in the case of surgeons). While this doesn't create a monopoly, it does grant some degree of market power to those who have licences, because it prevents unlicensed people from entering the market. Unlicensed doctors or dentists would face stiff penalties for offering their services without a licence.

So, part of this article (probably gated) from the National Business Review yesterday struck me as surprising:

A KiwiSaver provider is concerned the new licensing regime for financial advice will reduce the number of advisers and therefore make it harder for people to access those services, as has been seen in other countries.

But the Financial Markets Authority said there is no indication the changes have, or will, result in a reduction in advisers, with the sector “fully embracing” the changes.

On Monday, a new licensing regime went live requiring anyone who gives regulated financial advice to retail clients to either hold, or operate under, a Financial Advice Provider licence.

Just because there has been no immediate effect on the number of financial advisors, it doesn't mean that there won't be fewer of them long term. The new rules have created a barrier to entry into the financial advisor market, because advisors must now be licensed. Whatever the merits of the licensing regime, it is highly likely that the result is fewer financial advisors, charging higher fees for their advice.

Financial advisors is one occupation where licensing might provide a net benefit for society. Clients don't engage with their advisors very often and financial literacy in the general population is not great (e.g. see here), so many clients won't know whether they are getting good advice, or bad advice. And the consequences of getting bad advice, in terms of reduced savings or retirement income, are likely to be quite high (and there are no do-overs). However, not all occupations are like that. For instance, it beggars belief why some countries require licenses for beekeepersfortune tellersdog groomers, or librarians. But, in all cases, occupational licenses reduce the number of people working in those occupations, and increase their market power.

Monday, 15 March 2021

Spotify and the musicians' dilemma

Yesterday I posted an example of the prisoners' dilemma, applied to supermarkets' pricing behaviour in New Zealand. These are strategic situations where each player (decision maker), acting in their own self-interest, creates an outcome (and payoffs) that are worse for all of the players. There are many real world examples of the prisoners' dilemma (such as this one, or this one). However, I want to concentrate on an example from this January article in The Conversation, by John Hawkins, Ben Freyens, and Michael Walsh (all University of Canberra):

Streaming now accounts for more than half of recorded music revenue. Spotify has about a third of the subscribers paying for music streaming. Playlists overtook albums as the preferred way of listening to sequences of songs about five years ago.

Appearing on a prominent Spotify playlist is therefore a big deal...

With so much power, what will Spotify do next?

The answer, apparently, is to run a pay-to-play “experiment”, dropping Spotify’s “crystal clear” commitment in 2018 that “no one can pay to be added to one of Spotify’s editorial playlists”. But now there’s this:

In this new experiment, artists and labels can identify music that’s a priority for them, and our system will add that signal to the algorithm that determines personalised listening sessions.

The catch is musicians must accept a lower payment — a “promotional recording royalty rate” — on any song streamed as a result.

So, essentially, Spotify is asking musicians so accept a lower royalty rate in exchange for having their music promoted more intensively. Why does this provide an example of the prisoners' dilemma? Hawkins et al. explain:

The musician’s dilemma is that the best cooperative outcome is all artists refusing Spotify’s offer. No one gains, but no one loses either.

But who’s going to organise that, given the understandable fear of repercussions for going against Spotify?

Best placed to resist are Spotify’s superstars — the likes of Eilish, Taylor Swift, Ariana Grande, Ed Sheeran, Drake and Bad Bunny, with billions of streams between them. They have diversified marketing and revenue sources, and are cash cows Spotify doesn’t want to lose.

The most likely outcome is many or most musicians accepting lower song payments from Spotify, putting the squeeze on struggling musicians who refuse while making little difference to the prominence super streamers get from Spotify’s algorithms.

In other words, all of the musicians could work together and disagree with Spotify's generous offer of promotion. However, every musician then has an incentive to sign up to the programme, knowing that their music would have greater visibility while every other musician's music would not. So, even if there was an agreement between the musicians, the agreement would quickly break down. This is the problem that all cartels face - all of the members of the cartel have an incentive to 'cheat' on their agreement to get themselves a better deal.

Cooperation is hard. As I note in my ECONS101 class, it requires trust between the players. And trust usually requires developing a reputation for being trustworthy. And each musician would need to be able to trust all (or at least most) of the other musicians, before it would be worthwhile agreeing to forego the deal with Spotify. That seems unlikely.

The musicians' dilemma is clearly something that Spotify has thought through. Spotify might back down for any of the superstars (see above), but the average musician will just have to take what they can get, which already isn't a whole lot.

Saturday, 13 March 2021

New Zealand's supermarket duopoly and coordinated behaviour

The National Business Review reported yesterday (probably gated):

Consumer and food manufacturer representatives say accommodating behaviour between the two dominant supermarket groups is a “major risk”,  that it is “highly likely”,  and that growth in private label products should be thoroughly investigated.

Foodstuffs and Woolworths, meanwhile, have played down any concerns in the hundreds of pages of submissions made on the Commerce Commission’s proposed scoped of its study into the country’s retail grocery market, saying it is “intensely competitive”...

A key feature of the preliminary issues paper was the proposed investigation of whether the country’s grocery sector is vulnerable to “accommodating” or “coordinated” behaviour, which it cites as a potential outcome in oligopolies.

The commission said such conduct does not necessarily require an explicit agreement or express coordination.

“Coordinated behaviour involves firms recognising that they can reach a more profitable outcome if they act to limit their rivalry when taking each other’s actions into account (such as by following a rival’s price increases),” the paper said.

The two Foodstuffs cooperatives have more than 400 retail stores nationwide predominantly under the New World, Pak’n’Save and Four Square banners, serving more than three million customers a week...

A market with two firms is a duopoly (and when there are more than two firms, but not many, the market is an oligopoly). The thing about duopoly markets (and oligopoly markets) is that the firms can more easily act to coordinate their behaviour, in terms of pricing or 'market splitting', to lower competition. Lower competition means higher profits for the firms.

To see how this works, consider the game laid out in the table below. There are two players (firms) - Foodstuffs and Woolworths. Each player has two strategies - price high, or price low. If both firms price low, then there is a price war and both are worse off. If both firms price high, then both are better off. The outcomes and payoffs are illustrated in the table (the payoff numbers represent profits, but are just made up to illustrate this example).

To find the Nash equilibrium in this game, we use the 'best response method'. To do this, we track: for each player, for each strategy, what is the best response of the other player. Where both players are selecting a best response, they are doing the best they can, given the choice of the other player (this is the definition of Nash equilibrium). In this game, the best responses are:

  1. If Woolworths chooses to price low, Foodstuffs' best response is to price low (since 50 is a better payoff than 25) [we track the best responses with ticks, and not-best-responses with crosses; Note: I'm also tracking which payoffs I am comparing with numbers corresponding to the numbers in this list];
  2. If Woolworths chooses to price high, Foodstuffs' best response is to price low (since 180 is a better payoff than 80);
  3. If Foodstuffs chooses to price low, Woolworths' best response is to price low (since 50 is a better payoff than 25); and
  4. If Foodstuffs chooses to price high, Woolworths' best response is to price low (since 180 is a better payoff than 80).

Note that Woolworths' best response is always to choose to price low. This is their dominant strategy. Likewise, Foodstuffs' best response is always to choose to price low, which makes it their dominant strategy as well. The single Nash equilibrium occurs where both players are playing a best response (where there are two ticks), which is where both firms choose to price low.

Notice that both firms would be unambiguously better off if they chose to price high. However, both will choose to price low, which makes them both worse off. This is a prisoners' dilemma game (it's a dilemma because, when both players act in their own best interests, both are made worse off).

So, it makes sense for the firms to try and find some way to avoid the bad (low price) outcome, and come to an 'arrangement' that ensures they get the better (high price) outcome. The NBR article gives suggestions of how this might be playing out:

Consumer NZ’s submission said it believed accommodating behaviour was a “major risk” in the market, particularly regarding price.

It detailed investigations it had made comparing prices between Woolworths’ private label brands sold at Countdown here and Woolworths in Australia, and found that New Zealand consumers paid 30% more for the same basket of 20 items...

Note that this type of behaviour doesn't actually require the two firms to collude. They can coordinate their actions even if they aren't directly communicating with each other. However, the structure and payoffs of the game haven't changed, so there will always be an incentive to 'cheat' on this sort of arrangement, and throw in a low price occasionally. Interesting, even that behaviour seems that it may be baked into the 'arrangement':

Consumer NZ’s supermarket price surveys, meanwhile, found that stores appeared to have ‘turns’ offering specials on the same products – for example, a particularly brand of cheese might be on special at one supermarket one week and then be on special at another the following.

Notice that in the game above, players colluding to set a high price would get a payoff of 80 each. However, if the game was played over and over again, and the two firms alternated who would have the low price, each firm would get 180 in the low price week, and 25 in the high price week, for a total of 205 (compared with 160 for sticking with high prices all of the time).

And this brings us to the idea of a repeated game. In a repeated game, the outcome may differ from the equilibrium of the non-repeated game, because the players can learn to work together to obtain the best outcome. And this could be what is happening. If Woolworths and Foodstuffs work together to alternate their low prices, both firms benefit. Both firms have a short-term incentive to 'cheat' (by setting a low price when the other firm does), but if they were to do so the arrangement could break down and both firms would end up back at the low price Nash equilibrium.

This is one of the aspects that the Commerce Commission is investigating as part of its market study into the grocery sector. Unsurprisingly, the supermarket firms are denying that any of this is going on. Maybe it isn't, or maybe it is and they just think that everyone is naive enough to believe them.

Friday, 12 March 2021

How not to measure the long term consequences of the Hiroshima atomic bomb

In a new article published in the Journal of the Japanese and International Economies (sorry, I don't see an ungated version online), Satoshi Shimizutani (Nakasone Yasuhiro Peace Institute) and Hiroyuki Yamada (Keio University) look at the long-term impact of the Hiroshima atomic bomb blast in 1945. They use data from the 2011-12 and subsequent waves of the Japanese Study on Aging and Retirement (JSTAR), along with a supplementary survey conducted in 2017. Their sample includes 653 people living in Hiroshima in the JSTAR sample, 297 of whom are defined as 'affected' by the Hiroshima bomb (primarily either because they were survivors of the Hiroshima bomb, or because they parents were). Comparing those two groups across a wide range of socio-economic variables, they find that:

...more than 60 years after the tragic event, survivors and their children are not seriously disadvantaged in marriage status or educational attainment but some significant distinctions between the affected and the non-affected group is observed in such aspects as combination of married couples, work status, mental health, and expectations.

Specifically, they find that affected people are more likely to have inherited their house, affected women (but not men) are more likely to be self-employed, work in small firms, and hold managerial positions, while affected men (but not women) report a lower subjective probability of living to age 85, and more depressive symptoms. There are a whole range of variables where the differences are not statistically significant.

There are a couple of problems with this study. The first is that they studied a wide range of socio-economic variables, but made no adjustment for the multiple comparisons that they made. Simply by chance, five percent of all comparisons are likely to be 'statistically significantly different' at the five percent level of significance. The fact that they don't really observe any effects that are consistent for both men and women should also be a big red flag here. Why would there be employment effects for affected women, but not men? Shimizutani and Yamada don't provide a strong theoretical reason to support their results, and fail to acknowledge the big limitation on them that the multiple comparisons creates.

The second, and probably more serious, problem is survivorship bias. The majority of the worst-affected people won't have survived to 2011, in order for their data to be included. Only the long-term survivors are included in the sample. So, at best this study can say that it looks at the long-term consequences of the Hiroshima atomic bomb, for those that survived to at least 2011. The long-term effects on the whole population affected in 1945 or thereafter were likely much greater, and much of those effects are unobserved. Again, this limitation wasn't acknowledged by Shimizutani and Yamada.

The short-term and long-term health consequences of the atomic bombings in 1945 have been extensively studied. The socio-economic consequences have received much less research attention. Unfortunately, this study doesn't do an adequate job of filling that gap.

Tuesday, 9 March 2021

Public toilets and unintended consequences

In my ECONS102 class last week, we spent a bit of time considering unintended consequences. Sometimes, a policy unintentionally creates exactly the opposite effect to what was intended, such as this example I wrote about in 2015:

The government was concerned about the number of snakes running wild (er... slithering wild) in the streets of Delhi. So, they struck on a plan to rid the city of snakes. By paying a bounty for every cobra killed, the ordinary people would kill the cobras and the rampant snakes would be less of a problem. And so it proved. Except, some enterprising locals realised that it was pretty dangerous to catch and kill wild cobras, and a lot safer and more profitable to simply breed their own cobras and kill their more docile ones to claim the bounty. Naturally, the government eventually became aware of this practice, and stopped paying the bounty. The local cobra breeders, now without a reason to keep their cobras, released them. Which made the problem of wild cobras even worse.

Now, if you've ever been to the U.S., then you may have noticed the absence of public toilets. Unlike New Zealand and many other countries, there are simply no public toilets to be found. If you are caught short, you need to find a Starbucks or McDonalds or the like. Why is that? John Cochrane provided the answer yesterday:

Answer: Because it's illegal to charge for toilets. There were once abundant public toilets in America, as there are in many other countries. And you pay a small fee to use them. A small fee that everyone in Nicholas' stories would have been delighted to pay...

The absence of pay toilets is in fact a delightful encapsulation of so much that is wrong with American economic policy these days. Activists decide free toilets are a human right, and successfully campaign to ban pay toilets. For a while, existing toilets are free. Within months, upkeep is ignored, attendants disappear, and the toilets become disgusting,  dysfunctional and dangerous. Within a few years there are no toilets at all. Fast forward, and we have a resurgence of medieval diseases that come from people relieving themselves al fresco.

Cochrane's post is worth reading in its entirety. His blog is called The Grumpy Economist, and you can see why. Anyway, the point is that, in an effort to make public toilets more affordable and accessible, by making them all free, government policy eliminated the incentives to provide public toilets at all, meaning that none are now provided. Classic unintended consequences.

[HT: Marginal Revolution]

Monday, 8 March 2021

Book review: Hello World

Algorithms, artificial intelligence, and machine learning are more than techno-babble, or buzzwords to use to make you seem like you are in the know. They are key terms that are necessary for understanding how our data are being used (or abused) to recommend things to us, sell us things, advertise to us, and make decisions about us. It could be argued that there is a minimum level of understanding of these terms that is necessary in order to effectively negotiate our way in the modern world. Or at least, to negotiate our way while perhaps avoiding some of the worst potential outcomes.

Hannah Fry's book Hello World is a good source of material to help you achieve that minimum level of understanding. The subtitle is "Being human in the age of algorithms". The book covers key developments in algorithms in a variety of areas including justice, medicine, crime and policing, autonomous vehicles, and even the arts. Many readers will be surprised at the sheer breadth and depth of applications to which algorithms have been applied. Even though there are whole fields in science and business that Fry doesn't explore (see for example Prediction Machines, which I reviewed here), for many readers those omissions will not be noticed.

There was little in the book that was new to me, but Fry has an easy writing style that still made it a pleasure to read. She also does an excellent job of distilling the key points in explaining otherwise dry models such as random forests, neural networks, or genetic algorithms. While those are terms that you are unlikely to encounter in everyday living, it is helpful to understand at least at a basic level what it is that those types of algorithms are doing.

Although, what exactly it is that algorithms are doing remains and always has been the problem with machine learning algorithms. From outside the 'black box', it is difficult if not impossible to determine what associations the algorithm is using or how it is using those associations. I think Fry skims lightly over this key issue, although she does pay lip service to at least one potential solution:

Thankfully, the calls are getting louder for an algorithmic regulating body to control the industry. Just as the US Food and Drug Administration does for pharmaceuticals, it would test accuracy, consistency and bias behind closed doors and have the authority to approve or deny the use of a product on real people.

The FDA hasn't exactly covered itself in glory during the coronavirus pandemic (e.g. see here), but given the potential negative consequences of algorithmic bias, it seems increasingly clear that some oversight is warranted. Fry does highlight negative consequences of algorithms throughout the book, but stops well short of Cathy O'Neil's Weapons of Math Destruction (which I reviewed here). O'Neil expresses much stronger negative views on the use of algorithms, and O'Neil's calls for reform are all the more forceful for that.

Disappointingly for me, Hello World didn't get really interesting until the concluding chapter, which was consequentially too brief. For instance, I really liked this quote, which was buried in a footnote on page 199:

There's a trick you can use to spot the junk algorithms. I like to call it the Magic Test. Whenever you see a story about an algorithm, see if you can swap out any of the buzzwords, like 'machine learning', 'artificial intelligence' and 'neural network', and swap in the word 'magic'. Does everything still make grammatical sense? Is any of the meaning lost? If not, I'd be worried that it's all nonsense. Because I'm afraid - long into the foreseeable future - we're not going to 'solve world hunger with magic' or 'use magic to write the perfect screenplay' any more than we are with AI.

Brilliant, and an antidote to the hype that constantly gets heaped on algorithms. The book could have done with more of that dose of realism in amongst the anecdotes of how algorithms are being used, for good or ill. In particular, the difference between correlation (which algorithms identify) and causality (which they cannot) is important and often ignored. All of which should lead us to conclude that algorithms are not perfect, as Fry notes (again in the conclusion):

Algorithms will make mistakes. Algorithms will be unfair. That should in no way distract us from the fight to make them more accurate and less biased wherever we can - but perhaps acknowledging that algorithms aren't perfect, any more than humans are, might just have the effect of diminishing any assumptions of their authority.

Fry concludes that perhaps the best algorithms are those than enhance, or support, human decision-making, rather than those that replace human decisions. That seems fair, at least until the algorithms can do real magic.

Sunday, 7 March 2021

Performance-based scholarships and incentives

There are fundamentally two different types of scholarships that can be awarded to university students. First, scholarships can be awarded with no strings attached. Essentially these are grants that the students can use for any purpose (or sometimes they are linked to tuition or accommodation), but there is no need for students to do anything further to retain their scholarship. Second, scholarships can be performance-based, in which case students must attain a minimum grade point average (or similar) in order to remain eligible and continue to receive their scholarship. The idea behind a performance-based scholarship is that it increases the incentives for students to maintain a high level of performance, compared with a scholarship with no performance requirement.

The theory underlying a performance-based scholarship is simple. It relies on the assertion that people respond to incentives. When economists say that, they mean that when the costs of doing something increase, we tend to do less of it. And if the costs of doing that thing decrease, we tend to do more of it. The reverse is true of benefits - when the benefits doing something increase, we tend to do more of it, and when the benefits decrease, we tend to do less of it. In the case of the performance-based scholarship, the benefits of studying hard are increased, because the reward for studying is that the student has a higher probability of retaining their scholarship. [*]

Does it work in practice? In a 2018 article published in the journal Education Finance and Policy (ungated earlier version here), Lisa Barrow (Federal Reserve Bank of Chicago) and Cecilia Rouse (Princeton University) provide some evidence that it does. They used data on the California Scholarship Program. As they describe it:

High school seniors in California were randomly assigned to treatment and control groups where the treatments (the incentive payments) varied in length and magnitude and were tied to meeting performance, enrollment, and/or attendance benchmarks...

The incentive varied in length (as short as one semester and as long as four semesters), size of scholarship (as little as $1,000 and as much as $4,000), and whether there was a performance requirement attached to it.

The randomisation allows Barrow and Rouse to compare students who did receive the scholarship with those who didn't. The randomisation across performance-based scholarship (PBS) and not performance-based scholarship, and different durations and values, allows Barrow and Rouse to test whether a performance-based scholarship increased the incentive to study hard, and whether higher scholarship amounts increase the incentive further. They have data on about 6600 students (who were seniors in high school at the time of randomisation), across two cohorts (2009 and 2010). They find that:

PBS-eligible students were 5.2 percentage points more likely than the control group to report ever enrolling at a postsecondary institution, a difference that is statistically significant at the 1 percent level. Further, the PBS-eligible students reported studying about eight minutes more per day than those in the control group, were 7.3 percentage points more likely to have been prepared for class in the last seven days, and were 6.7 percentage points more likely to report attending all or most of their classes in the last seven days.

All of those results seem to suggest an increased incentive to study hard, as PBS recipients were spending more time studying than students who received no scholarship at all. However, when comparing PBS recipients and non-PBS scholarship recipients:

We generally find the impacts are larger for those eligible for a PBS than for those offered a non-PBS, however, in most cases we are unable to detect a statistically significant difference.

In other words, the incentives appear to be the same for performance-based and non-performance-based scholarships. The question then becomes, do PBS recipients study smarter, rather than harder? It appears that might be the case:

...PBS eligibility may induce participants to concentrate more on their studies by encouraging them to employ more effective study strategies, making the time devoted to educational activities more productive. Similarly, by raising their academic self-efficacy the scholarships may also induce students to be more engaged with their studies... We estimate that eligibility for a PBS had positive and statistically significant impacts on these dimensions that range from 12 to 22 percent of a standard deviation. Note as well that the impacts on learning strategies and academic self-efficacy for those selected for a non-PBS were substantially smaller than those selected for a PBS, consistent with increased academic effort on the part of PBS-eligible individuals.

So, the PBS recipients were using more effective study strategies than non-PBS recipients, even if they weren't studying harder. Coming back to the comparison with students who didn't receive any scholarship, the extra time spent studying arises because:

...participants accommodated increased time spent on educational activities by spending (statistically) significantly less time on leisure activities, including reducing the number of nights out for fun during the past week.

Moving on to the size of the scholarship, the results are much less clear-cut:

Interestingly, we do not find large differences in the effect of PBS eligibility related to the size of the scholarship. Students who were eligible for a $500 per semester scholarship responded similarly on most outcomes to students who were eligible for a $1,000 per semester scholarship, suggesting that larger incentive payment amounts did not lead to larger impacts on student effort.

This may seem a little surprising. However, Barrow and Rouse suggest some explanations for the lack of increased incentive associated with larger scholarships:

First, the result may suggest that students need just a small prompt to encourage them to put more effort into their studies but that larger incentives are unnecessary. Further, it is possible that as the value of the incentive payment (external motivation) increases, students’ internal motivation declines at a faster rate such that negative impacts on intrinsic motivation increasingly moderate any positive impacts of the incentive on educational effort.

Not all incentives are monetary, and the intrinsic motivation to study hard is important. Extrinsic motivations can sometimes over-ride intrinsic motivations, creating negative unintended consequences. For one (famous) example, read this study by Uri Gneezy and Aldo Rustichini about incentives in Israeli day-care centres (also described in Gneezy's book co-authored with John List, The Why Axis, which I reviewed here). In that example, day-care centres began fining parents who showed up late to pick up their children, but this new system replaced the existing norm of picking up children on time, and actually resulted in more late pick-ups.

In the case of students, studying hard may be a norm for some students, and a small performance-based scholarship payment appears to reinforce the norm. However, if the payment is larger, then the intrinsic motivation to study hard may be eroded, leading to no further gains in study performance. People respond to incentives, but sometimes the incentives work in ways we don't anticipate. This is one area where more research is needed to fully understand why it is that the incentives don't scale with scholarship payments.


[*] Alternatively, you could think of it as increasing the costs of not studying, since the student loses the scholarship if they fail to achieve the minimum performance standard. Regardless, the effect on incentives is the same - the student receiving a performance-based scholarship has an incentive to study harder.

Saturday, 6 March 2021

The impact of the proposed Indonesian alcohol ban on price and quantity

In my ECONS102 class, we will be introducing the model of supply and demand this coming week. It's a pretty powerful tool for understanding the qualitative changes in price and quantity that can arise from policy changes. Here's one example, as reported by the New Zealand Herald back in November:

Indonesia's House of Representatives will resume debate on a controversial bill that would see consumption and distribution of alcohol banned across the country, including in the tourist mecca Bali.

Politicians linked to the Islam-based United Development Party have filed a request with Parliament to resume deliberation on the Prohibition of Alcoholic Drinks Bill which was first introduced in 2015 but has stalled.

Consider the market for alcohol in Indonesia, as shown in the diagram below. Initially, the market is operating at equilibrium, where the demand curve D0 intersects the supply curve S0. The equilibrium price is P0 and the equilibrium quantity of alcohol traded is Q0. If the alcohol ban is introduced, that would make the consumption of alcohol illegal. That would make at least some consumers less willing to consume alcohol (the net benefit of consumption would decrease because of the risk of penalties for engaging in illegal behaviour, which could be quite severe), so the demand for alcohol would decrease to D1. The ban would also make distribution of alcohol illegal. Alcohol sellers would face higher costs (due to the risk of getting caught and punished), and this would decreases the supply of alcohol to S1

The new equilibrium after then ban is introduced occurs where the demand curve D1 intersects the supply curve S1, The equilibrium price is P1 and the equilibrium quantity of alcohol traded is Q1. The quantity of alcohol traded definitely decreases. However, the change in the price of alcohol is ambiguous. As shown in the diagram, the price could decrease - that happens if the decrease in demand is bigger than the decrease in supply. However, if the decrease in demand was smaller than the decrease in supply, the equilibrium price would increase. And, there is a small chance that the decreases in demand and supply exactly offset each other, in which case the price would remain at P0.

The ambiguous effect of the alcohol ban on price might seem surprising, and many people would probably expect price to increase. However, that potentially ignores the role of lower demand in suppressing the price. One of the important lessons to learn from the model of supply and demand is to never reason from a price change. The price (and quantity) are the outcomes of the supply and demand model, so they usually are the end point, not the beginning.