Uber as a substitute for ambulances

When a new, cheaper substitute to an existing good or service becomes available, we can expect the demand for the existing good or service to decline. Importantly though, 'cheaper' refers to the full cost of obtaining the good or service, not just the monetary cost. So in the case of ambulance services, the cost may partly be monetary (such as in the U.S.), but also includes the cost of waiting to receive treatment (which is probably a more important component of the cost in New Zealand, although in some cases ambulance services will charge for a call-out. For example, see here).

Are there cheaper substitutes for ambulances? In a country such as the U.S., where the monetary cost of calling an ambulance could easily be in the thousands of dollars, ride-hailing services like Uber or Lyft could easily be a less costly option overall. However in New Zealand, where the monetary cost of calling an ambulance is not as high, the evaluation is not quite as straightforward. If you call an ambulance for something serious, then you benefit from treatment from the ambulance officers as soon as they arrive at your location. But if you call an Uber, the driver probably arrives at your location quicker than an ambulance would (since they have less far to travel), but then you have to wait until you get to the hospital in order to receive treatment. So, for Uber to be cheaper than an ambulance in New Zealand, the monetary cost savings would have to offset the (likely) longer time to receive treatment.

So, we would expect to see Uber having some effect on ambulance services in the U.S., but less so in New Zealand. But how big an effect? In a recent paper, Leon Moskatel (Scripps Mercy Hospital) and David Slusky (University of Kansas) investigate the impact of UberX on ambulance call-outs. Using U.S. data on the timing of UberX's entry into various cities and the number of call-outs in each city, they find that there is:

...at least a 7% decrease in the ambulance rate from Uber entry into a city.

Moskatel and Slusky's paper is short and not particularly detailed. The analysis is fairly straightforward, and perhaps a little too much so. They claim that their analysis "follows a generalized difference-in-differences framework at the city-quarter level", but I don't think it does because they use only a simple dummy variable to test for the effect of Uber.

A 'difference-in-differences' analysis involves computing the difference between two differences (there's no mystery in the naming of this technique). Essentially, in this case you calculate the difference in ambulance call-outs between the period before UberX became available and the period after UberX became available (treatment cities), and then you calculate the difference in ambulance call-outs between the period before and the period after for control cities (where Uber did not become available). The problem with the analysis in this paper is that there are no control cities - all cities in their analysis had UberX become available. This doesn't bias their results, but it does affect how you interpret them, since they are really only testing for a difference in mean ambulance call-outs between cities with and without UberX.

If you have time series data but no control, you could run an interrupted time series analysis instead, which is very similar to difference-in-differences but simply tests whether the time trend in the data changes between the period before UberX became available and the period after. The results that they present in Figure 2 in the paper suggest to me that their analysis is probably under-stating the impact of UberX, since there appears to be a clear break in the time trends between the period before and the period after UberX became available.

Anyway, that is a fairly technical critique of a paper that tells us something interesting. Although, I wouldn't expect there to be as large an effect of Uber on ambulance call-outs in New Zealand.

[HT: Marginal Revolution]

Some further notes on rent increases

Rent increases have been in the news a lot recently, especially in Wellington (see my post from earlier in the week). Based on some discussions with students, I thought I would make a few notes.

First, some have suggested that rents have increased by $50 because student allowances and Student Loan living cost payments have increased by that much (e.g. Grant Robertson's Facebook post on this). This is possible, but unlikely. If our incomes increase, we will be willing to pay more for rental housing (rental housing is what economists call a 'normal good'). That shifts our demand curve for housing up and to the right, as in the diagram below (from D0 to D1). The equilibrium rent will increase from R0 to R1. How much more will be willing to pay, and how much will the equilibrium rent increase by? Certainly our willingness-to-pay will not increase by the whole additional $50 of our income, because when our incomes increase we are also willing to pay more for food, clothing, entertainment, and all of the other normal goods that we like to buy. Our willingness-to-pay for rent will increase by some proportion of the $50 increase in income. So, I think it's extraordinarily unlikely that an increase in demand, driven by the increase in incomes, is solely behind the increase in rent.

Second, prices increase when there is excess demand. Is excess demand driving the increase in rents by $50? I covered this in my post on Monday and Eric Crampton also covered it. It's possible that rents are currently below the equilibrium rent, as shown in the diagram below. At the rent R0, there are Qd tenants looking for a house, but only Qs houses available to rent. There is excess demand for housing. Some tenants are missing out on housing. Landlords and tenants both recognise the excess demand, and tenants might start approaching landlords and offering a bit more in order not to miss out, or landlords might increase rents knowing that tenants will be willing to pay a little bit more in order not to miss out. Either way, rents start to rise and eventually the market ends up at the higher equilibrium rent R1. However, we seem to be in a perpetual state of excess demand in the rental market (if you doubt that, look at any of my past posts on housing). I've mused that maybe landlords are offering 'efficiency rents' - rents that are deliberately below the equilibrium rent, because that allows them to have the pick of applicants. So, I think it unlikely that excess demand is a big factor in increasing rents.

Third, and something that I haven't seen anybody considering, is that the accommodation supplement will increase on 1 April. Landlords signing rental agreements now must know that the accommodation supplement will increase during the term of the tenancy agreement, and that this increase in subsidy works sort of like the increase in demand shown above. However, in the case of the accommodation supplement, we can be fairly sure that it does increase willingness-to-pay for housing by $50, because it can't be used for anything else. [*] Why adjust rents now, when the accommodation supplement doesn't change for two more months? Because the rent that is agreed now can't be changed for several months after April - it makes sense to build this increase in now. This is shown in the diagram below. The accommodation supplement is a subsidy, paid to the tenant, so we show this with the D+subsidy curve, which is above the demand curve (for simplicity, the diagram doesn't show an increase in an existing accommodation supplement, which is actually what is happening, but making the diagram a bit more complex doesn't change the story at all). Another way of thinking about this is that, once the accommodation supplement increases by $50, households are willing to pay the same as before (shown by the demand curve), plus the extra $50 of the increased accommodation supplement. The rent before the increase in the accommodation supplement is R0. After the increase in the accommodation supplement, the rent that households pay to the landlords increases to RL, and the effective rent (after subtracting the increase in the accommodation supplement) falls to RT. Notice that most of the benefit of the increased accommodation supplement is captured by landlords. This is because of the very steep (inelastic) supply curve in the rental market - when rents increase, there aren't a lot of additional landlords rushing to make their houses available for renting.

So, my feeling is that the increase in rents we are observing now is the effect of landlords recognising that the accommodation supplement will soon increase, and they are trying to capture that increase early. And not the effect of the increase in student allowances, or excess demand for rental housing. Or maybe it is a little bit of all three? Of course, the easiest way to find out whether this explanation is the right one would be to ask landlords. But given the potential for a media beat-up, would you really expect them to come clean about this?

Finally, some dimwits have been advocating for rent controls (see Anna Mooney of Renters United quoted here). No. Just no.

Read more:

• That January tradition... rent increases, Wellington edition
• This is what happens when you have shortages of rental property
• Students, rental shortages, and renting over the summer
• January tradition continued... Rent increases again
• A January tradition - complaints about rising rents
• Out-of-control rent increases in Auckland - why?

*****

[*] You may be thinking here that income is fungible (it can be used for other things besides housing). That means that, when the accommodation supplement increases by $50, households' willingness-to-pay for housing might not increase by $50, because they might re-direct some of their other intended spending away from housing. However, in a world where people are quasi-rational and affected by mental accounting, it turns out that fungibility may actually be reasonably low (I'm currently reading Richard Thaler's excellent book Misbehaving: The Making of Behavioral Economics - more on that when I review it soon). Quasi-rational decision-makers have a household budget for rent, and when the accommodation supplement increases by $50, they may be thinking that means they can spend $50 more on rent (rather than other things) and act accordingly.

That January tradition... rent increases, Wellington edition

It's January, so that means house rental increases are in the news (if you doubt me, here's my 2017 post on the topic, and 2016, and 2015). It starts with Dan Rowe's piece in the Spinoff a couple of weeks ago, in which the details are not at all surprising:

The nightmare that is renting in this country continues to bring new horrors, with reports from Wellington that landlords are explicitly operating tender processes on their rentals in a bid to drive up prices...

Because what tenants aren’t free to do is escape the market altogether – already flat viewings across the city are attracting hordes of applicants, thronging in the streets and clamouring for a place to sleep as much as a full month before university begins for the year.

“I was at one the other day and there were people everywhere streaming up and down the street. Someone came out and asked us what was going on on their street because apparently there’d been like a hundred people walking up and down. It’s been pretty hectic.”

When you have "hordes of applicants" that suggests to me that there is excess demand (a shortage), and when there is excess demand you would expect prices (in this case, rents) to increase (a point that I have made before). However, Eric Crampton has a slightly different take, explaining why we wouldn't necessarily expect the rent to rise so far that it would eliminate the excess demand:

Suppose it's hard to evict a bad tenant. It'll take a long time, it'll be a hassle, and the tenants might destroy the place while you're going through the tenancy tribunal. If you set a high price and if it's hard to monitor and police what's going on in the flat, you might have problems. The high bidder might be the one expecting this to be a short-term game.

Landlords would want to evaluate a potential tenant's bid across a pile of hard-to-specify and possibly illegal-to-specify (but impossible to police unless you're dumb enough to write it in the ad) non-price margins. If you want that, you want to have excess demand at the posted money price so that you can clear on the other margins.

This idea of landlords offering 'below-market' rents in order to have the pick of tenants could be termed an efficiency rent (the rental equivalent of an efficiency wage - see here for more on efficiency wages), which I wrote about back in 2016:

As noted above, there is a moral hazard problem for landlords - tenants' incentives (to look after the property) are not aligned with the landlord's incentive (to keep the property in top condition). If the landlord instead offered an efficiency rent (a rent below the equilibrium market rent), then they would have many potential tenants applying for the property, allowing the landlord to pick the best (the least likely to damage the property). It also gives the tenants an incentive to look after the property after signing the tenancy agreement, because if they don't they get evicted and have to find another place to live at a much higher cost.

Maybe landlords offer efficiency rents already and we just don't realise it? There is certainly plenty of evidence for excess demand for rental properties (see here or here for example), so maybe rents are below equilibrium (though they are rising quickly so it's possible that the observed below-equilibrium rents are simply in transition to a higher equilibrium level). Excess demand by itself is pretty weak evidence for efficiency rents. I'd want to hear landlords telling us they offer lower rents to attract good tenants before I found it believable. There's not a lot of evidence in the academic literature on efficiency rent either (see this paper by Basu and Emerson as one example, ungated here).

I'm still waiting for some clear evidence that efficiency rents are a good characterisation of what drives excess demand in rental housing markets. In the meantime, we are left to ponder the situation. What is clear though, is that by now no one should be surprised that house rents increase in January.

Read more:

• This is what happens when you have shortages of rental property
• Students, rental shortages, and renting over the summer
• January tradition continued... Rent increases again
• A January tradition - complaints about rising rents
• Out-of-control rent increases in Auckland - why?

Increases in the minimum wage are effectively paid by consumers, but they lower inequality anyway

This post includes some good news, and some bad news, about increases in the minimum wage. Tobias Renkin's (University of Zurich) job market paper, co-authored with Claire Montialoux (UC Berkeley), and Michael Siegenthaler (ETH Zurich), has the details. In the paper, Renkin et al. estimated the pass-through of increases in the minimum wage into grocery store prices. In other words, they estimate whether it is consumers (full pass-through), grocery stores (no pass-through), or some combination of the two, that faces the costs of increases in the minimum wage for grocery store employees. Why care about grocery stores? The authors explain:

Grocery stores employ a substantial number of minimum wage workers, and their marginal costs are therefore likely affected by minimum wage hikes. Moreover, groceries make up a large share of consumer expenditure, especially in poor households and grocery prices thus substantially affect the real incomes of workers.

Most studies of the minimum wage look at hospitality (e.g. restaurant) workers, so it's good to have an alternative. Their price data contains U.S. data on:

...weekly prices and quantities for 31 product categories sold at grocery and drug stores between January 2001 and December 2012. On average, the sample covers 1,916 stores and 60,600 products over this period... Stores are located in 530 counties, 41 states and belong to one of about 90 retail brands... The data covers 17% of US counties which are home to about 29% of the overall population.

Unlike previous studies though, the authors argue that the date at which grocery stores make their price adjustments is the date that the minimum wage increase is announced, rather than the date it takes effect (which is usually some time later). Their analysis seems to back this up, with statistically significant effects on and around the date of the legislation, and less so around the date of implementation, of minimum wage increases.

The key results are for the minimum wage elasticity of grocery prices. That is the percentage change in grocery prices divided by the percentage change in the minimum wage, and can be interpreted as the percentage increase in grocery prices that would result from a one percent increase in the minimum wage. The results suggest that this elasticity is around 0.02. That is, a 1 percent increase in the minimum wage would increase grocery prices by around 0.02%. That doesn't sound like a lot, but the authors explain that:

In our sample, the average minimum wage legislation increases the minimum wage by about 20% in several steps. Our estimates suggest that such an increase raises prices in grocery stores by about 0.4% over three months at the time when legislation is passed. By the time the minimum wage has actually risen to the level set in the new legislation, price adjustment is already long complete.

There are lots of robustness checks that demonstrate the result is fairly robust. To work out how much of the minimum wage increase is passed through to consumers though, we need to also know what the minimum wage elasticity of grocery store costs is. That is, we need to know how much grocery store costs increase by when the minimum wage increases by one percent, and then compare that to the minimum wage elasticity of grocery prices. They authors find that:

Our estimate for pass-through based on our baseline specification amounts to 1.1. We cannot reject the hypothesis that pass-through is equal to 1...

In other words, all of the increase in the minimum wage is passed through to consumers. Grocery stores essentially pay none of the cost of the minimum wage increase. That is the bad news.

That might make you wonder then, since low income households spend the highest proportion of their income on food, and minimum wage increases are passed through in higher prices to those households (and richer households, of course), is the minimum wage increase entirely eaten up by higher prices? The authors address this question as well, and find that:

Expressing the costs as a percentage of annual household incomes reveals the regressive impact of the price response. The costs make up about 0.2% of annual income for households in the poorest bracket, and just one tenth of that, i.e. 0.02% for households in the richest bracket.

As a percentage of household income, the increase in grocery store prices are disproportionately borne by lower income households. However, the good news is that:

As expected, minimum wages reduce income inequality... In terms of nominal gains, households in this bracket gain an additional 1.5% of household income over an inequality neutral policy. Taking into account the price response in grocery stores reduces the additional gains to 1.34% and further taking into account restaurants reduces the gains to 1.15%.

Even though lower income households spend a higher proportion of their income at grocery stores than higher income households, they also benefit proportionately more from the increase in the minimum wage, and the increase in household income is not all eaten up by increases in grocery prices.

[HT: Marginal Revolution]

The economics of ticket scalping

In yesterday's post about the increasing role of economics in sports, I mentioned this 2009 article by Ross Booth (Monash University), published in the Australian Economic Review. In the article, Booth discusses some of the key topics he teaches in sports economics, one of which is the economics of ticket scalping, and how ticket scalping increases economic welfare. For example, this article from September published in The Conversation, by Paul Crosby and Jordi McKenzie (both Macquarie University) notes that:

...there is an argument that ticket scalping actually enhances the total welfare of concert goers and sports fans. Scalpers act to distribute tickets to those who value them the most, or, as economists’ would say, they increase the allocative efficiency of the market.

Secondary markets for tickets allow potential buyers to indicate how much they want to go to the event – their “willingness to pay”. If tickets can only be bought at a single price on a first come first serve basis, then some people who really want to go will be left out. Secondary markets permit these mutually beneficial exchanges to take place.

Online platforms for buying and selling tickets actually increase this allocative efficiency. 

However, this traditional view that is used by many economics teachers is not correct, as I have explained before (see here and here). However, this point bears repeating.

Consider the diagram below. The supply of tickets to some event S0 is fixed at Q0 - if the price rises, more tickets cannot suddenly be made available because the capacity of the venue is fixed (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 (a shortage) - the quantity of tickets demanded is Qd, while the quantity of tickets supplied remains at Q0.

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 venue or the seller) 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 increase total welfare - their actions don't affect total welfare at all, just the distribution of that welfare between the parties.

However, the above analysis allows us to think about what would be required for ticket scalping to increase total welfare. That would happen if the higher price induced more events (since each event has a fixed number of tickets, the only way to increase total welfare is to have more events). However, that would only happen if the sellers (not the ticket scalpers) received a higher profit from each event (incentivising them to schedule more events). As shown above, the action of the scalpers doesn't affect producer surplus (it stays P1CDO with and without scalping), and so those incentives for the sellers don't materialise.

Crosby and McKenzie do correctly note that online platforms for re-selling tickets:

...arm buyers and sellers with ever increasing amounts of information, and the time and expenses associated with the purchase of each resold ticket (known as “transaction costs”) are greatly reduced.

The main downside of ticket scalping is that some (previously very lucky) consumers could earn a huge consumer surplus by buying their tickets at a much lower price than what they were willing to pay for them, but must now pay a higher price. You might think this unfair, but as I pointed out in an earlier post:

...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.

Despite the actions of ticket scalpers having little effect on economic welfare (they just re-distribute it), governments do seek to clamp down on it. Crosby and McKenzie briefly discuss technology as a means of reducing scalping, but a more recent Conversation article by Keith Parry, Aila Khan, and Blair Hughes (all Western Sydney University) lays out the future of ticketing in more detail:

Internationally, there have been some interesting developments amongst teams, venues and ticketing companies that may eliminate scalping and improve the ticketing experience.

It may not be long before all fans can take advantage of innovations such as mobile-only tickets, biometric access, and even microchipped tickets...

Looking to the future, it may not be long until tickets are physically linked to individuals and our iconic sporting venues are accessed with the swipe of an appendage.

In such a world, paper tickets will become a thing of the past.

One cannot feel that something is lost without the physical memento of a sporting event provided by a ticket stub. The scalpers and bots have much to answer for.

It's not the scalpers or bots that have much to answer for, it's the ticket sellers who consistently under-price event tickets. If they didn't do so, then the scalpers and bots would have no opportunity to profit.

Read more:

• The Super Rugby final and ticket scalping
• Harry Potter and the chamber of scalpers

Locked in lecturers and out-of-control textbook prices

Yesterday I wrote a post about the upcoming change to our first-year economics papers at Waikato, where we will be adopting the CORE curriculum. One of the material considerations in our choice was the cost of textbooks, which have clearly gotten out of control. A recent Quartz article notes:

Seven Rhode Island universities, including Brown and Rhode Island College, will move to open-license textbooks in a bid to save students $5 million over the next five years, the governor announced Tuesday (Sept. 27).

The initiative is meant to put a dent in the exorbitant cost of college and, more specifically, college textbooks. Mark Perry, a professor of economics and finance at the University of Michigan Flint, and a writer at the American Enterprise Institute, estimated last year that college textbook prices rose 945% between 1978 and 2014, compared to an overall inflation rate of 262% and a 604% rise in the cost of medical care.

That is not the result of a general trend of higher costs in publishing, he notes: the consumer price index for recreational books has been falling relative to overall inflation since 1998.

“It begs the question, are we getting 1,000% more value?” asked Richard Culatta, the chief innovation officer for Rhode Island who was the director for the office of educational technology in the Obama administration.

On that last question, the textbook sellers would argue that yes, we are getting more value. However, it isn't clear to me that the 'we' that is getting the extra value is the students. Textbooks have barely changed in the last twenty years. The 'extra value' that the textbook providers believe they are generating is not through meaningful improvements in the quality of the textbook material. Instead, they have increasingly concentrated their efforts on creating supplementary online offerings, tying the textbook to additional online resources for students, but selling the value of those additional resources for lecturers. For instance, textbooks from the big publishers will often include online testing systems that automatically link to university learning management systems (not to mention those that work like learning management systems themselves), extra exclusive multimedia and online content that can be used in lectures or made available to students or used as part of assessment tasks, online data visualisation tools, and so on.

Call me cynical, but I see all those online extras as simple attempts to create and capture value through customer lock-in - exactly one of the things we discuss in ECON100 (and soon ECONS101). Customer lock-in occurs when customers (in this case the lecturers) find it difficult (costly) to change once they have started purchasing a particular good or service. In this case, the lecturers aren't purchasing anything, but the principle remains valid. Once a lecturer starts using these online 'extras' that are tied to a particular textbook, it is difficult for them to change because that would mean losing all of the work that they've put into designing their course around those extras, and starting over afresh with the extras available with the new textbook. That time and effort constitutes a switching cost, which lecturers would obviously try to avoid, thereby locking them into their current choice of textbook. Having lecturers locked in to using a particular textbook allows the publishers to raise prices, which has led us to where we are today, where the Australia-New Zealand edition of the Mankiw textbook Principles of Economics now costs about NZ$185.

Obviously, I'm keenly aware of the switching costs and try to avoid being locked in. So, I've always been reluctant to rely too heavily on the bonus material available from the textbook suppliers. I don't even use their default Powerpoint slides, but that's more because I see the textbook as just one resource among many that I use in my teaching, and not the centrepiece of each course.

Despite my efforts, we were somewhat locked into using the Mankiw textbook in ECON100, since part of the test bank we used was from that book (albeit an earlier edition) and our resources pointed its chapters. Changing to a new textbook would mean we had to develop a new test bank (although we could keep our own questions from the previous one), and re-writing the paper outline and other resources to link to the new textbook.

When we decided to renew and redevelop ECON100 into ECONS101, we were going to face a cost anyway, so the switching cost of adopting a new textbook at the same time was relatively lower. Our ECONS101 students will be the beneficiaries, since as I mentioned yesterday it means that we can adopt the new CORE curriculum. However, it's worth noting that the CORE textbook is free for students, but if we as lecturers want to change textbook, we will face another switching cost.

Goodbye to ECON100, hello to ECONS101

It's the time of year to be a little nostalgic, and that feeling was further promoted this week by the conclusion of the final semester of our ECON100 paper at Waikato. So it seemed fitting that I was the tutor for the final tutorial for ECON100 a couple of weeks ago, given that I was also the tutor for the very first ECON100 tutorial, way back in the second week of A Semester 2003.

We introduced ECON100 in 2003 as part of a revamped Bachelor of Management Studies, and at that time the paper was two-thirds microeconomics, and one-third macroeconomics. The first iteration was taught by Steven Lim and Dimitri Margaritis. Many others have contributed as lecturers over the years including Bridget Daldy, Dan Marsh, Mark Holmes, Pam Kaval, Steven Tucker, Susan Olivia, Matthew Roskruge and myself (plus some guest lecturers and visiting lecturers, and of course there have been many, many tutors).

I remember Steven and Bridget as being the real drivers of the development (or re-development) of the paper in the beginning (Steven especially), and ECON100 has had an identity as an introductory paper in business economics that has made it unique within New Zealand. While other universities have continued to teach principles of economics in first year (of various flavours), ECON100 has always had a much greater focus on business applications like game theory, strategy, and pricing.

I first lectured ECON100 in A Semester of 2005, teaching the macroeconomics section (yes, that is surprising given that I exclusively teach microeconomics now). After that, I taught it in the Summer School period in 2006 and 2007, then in A Semester from 2008 to 2017, as well as B Semester in 2011 and 2016-17. The paper format changed in 2008 to be all microeconomics (no macroeconomics) - a change that I agitated strongly for, in order to balance the way that ECON200 was taught (as all macroeconomics). This allowed us to introduce a wider range of interesting business content, and especially to extend our coverage of market failures.

Steven was kind enough (or tolerant enough) to allow me space to innovate in the paper (and everyone else just went along with my suggestions). We began using the Aplia online testing platform in 2009 (after a successful trial run by Dan Marsh that year in summer school), and have used it every semester for the last nine years. We ran quite a successful group video project assessment from 2011 to 2015 (although we eventually dropped it when students stopped putting sufficient effort into the videos and the quality dropped significantly). In 2016, we introduced extra credit marks that could only be earned by completing spot quizzes in lectures, which has substantially improved lecture attendance, particularly late in the semester (this follows my standard practice in ECON110 for many years to offer extra credit marks in lectures). These innovative assessments have drawn attention across the university and internationally, and as I have mentioned before our assessment and grading practices compare well with others.

So, what comes next? It might be the end of ECON100, but it is just the beginning for our new ECONS101 paper, which will be introduced from A Semester next year. The ECONS101 paper will look totally different, but at the same time it will retain some of the key features that make it distinct from offerings at other universities. The biggest change will be the adoption of the CORE curriculum, which has just received further support from the Royal Economic Society:

CORE, which stands for Curriculum Open-access Resources in Economics (www.core-econ.org), is an international collaboration of researchers that has created an online, free, introductory economics ebook called The Economy. It is already the basis of the first year of economics degrees offered by more than a dozen universities in the UK, including University College London, King’s College London, and The University of Bristol.

CORE is probably the most exciting new development in economics teaching in recent years, and we are excited to be offering it. And as you can see from the list above, we're going to be following some high quality international university programmes in doing so. However, ECONS101 will retain a focus on business economics as well, and so future students can expect to have to deal with applications of pricing strategy alongside their learning from the CORE textbook (which I will write more about later this week).

The new ECONS101 paper will return to the two-thirds microeconomics, one-third macroeconomics format that the original ECON100 paper had. I'm thrilled to have Les Oxley to share the paper with in both semesters next year, and we hope that the next generation of Waikato management students will get at least as good an experience with ECONS101 as past students have had with ECON100.

I'm looking forward to it. I can't wait!

*****

In case you're wondering, ECON110 will have a new life too, although only the paper code is changing (to ECONS102) and most of the content will remain similar to previous years (although, that paper is a bit of a chameleon as it has undergone constant redevelopment over the 13 years I've taught it).

Book Review: The Upstarts

I've been following the development of Uber for a long time, including writing a few posts (see here, and here, and here, and here, and here, and here, and here). I haven't followed the development of Airbnb nearly as closely (and only mentioned them once on the blog, and then only in passing), but I have used the service. So, I was interested to read The Upstarts, by Brad Stone. The subtitle is "How Uber, Airbnb, and the killer companies of the new Silicon Valley are changing the world".

In the book, Stone does an excellent job of chronicling the history of Uber, Airbnb, and to a lesser extent Lyft and the other minor players in those industries. The book covers their origin stories (both real and imagined), their growth and fights with both their competitors and regulators (especially in the U.S. and Europe), their missteps (like 'ransackgate', and Uber's failure in China), and the story so far up to about the end of 2016 (which is to be expected, from a book published in 2017). Stone seems to mostly get the inside story from the key players involved, but overall the book is more of a highlights (and/or lowlights, depending on your perspective) package than a deep dive into each company and their history. Stone himself is pretty upfront about this in the introduction:

It is not a comprehensive account of either company, since their extraordinary stories are still unfolding. It is instead a book about a pivotal moment in the century-long emergence of a technological society. It's about a crucial era during which old regimes fell, new leaders emerged, new social contracts were forged between strangers, the topography of cities changes, and the upstarts roamed the earth.

I guess we'll have to wait and see if the old regimes actually fall, or whether they just stumble a little bit and continue to be propped up by regulators. This is exemplified in the final section, where Stone asks Travis Kalanick (the CEO of Uber):

When would Uber get to profitability?

Kalanick's response was pretty evasive (teaser - you'll have to read the book to find out!).

The book has a lot to offer the student of economics, with interesting discussions about Uber's introduction of surge pricing (which I hadn't realised was introduced relatively late, in 2012), Uber's pricing experiments in Boston, the price elasticity of demand for Uber (which I've written about before here), and the impact of Uber on the value of a taxi medallion in New York (which fell by more than half between 2013 and 2016, from a starting value of US$1.2 million). I realise that all of those examples relate to Uber and I'd say that is either a fair reflection of the book or my prejudices. The chapters alternate between the stories of Uber and Airbnb, but I found the Uber story much more engaging. The Airbnb story is interesting, but it doesn't have quite the same drama or the same depth of content.

The Boston pricing experiments in particular are interesting, since they directly led to the rollout of surge pricing everywhere:

...[Uber's general manager in Boston, Michael] Pao started running experiments. For a week he held fares steady for passengers but increased payments to drivers at night. In response, more drivers held their noses and stuck around for closing hours. It turned out drivers were in fact highly elastic and motivated by fare increases. Pao then spent a second week confirming the thesis by breaking Boston's Uber drivers into two groups. Some saw surging rates at night while others did not. Again, drivers with higher fares during peak times stayed in the system longer and completed more trips.

Pao now had something that the previous unfocused tests of surge pricing hadn't yielded - conclusive math... Kalanick was convinced, and surge pricing became orthodoxy inside Uber...

Overall, if you're looking for an easy read and to understand how Uber and Airbnb became the monsters they are today, this book is a good place to start. I enjoyed it, and I'm sure you would too.

Lobbyists, rent seeking and deadweight losses

The rise of lobbying in New Zealand has been in the news recently, as Bryce Edwards explained in his regular Political Roundup column in the New Zealand Herald a couple of weeks ago:

Political lobbying is a growth industry in New Zealand. And lobbyists are going to be particularly busy over the next year.

Edwards charts the rise of 'hyper-partisan' lobby groups Hawker Britton and its right-wing counterpart Barton Deakin. It's an interesting read, along with the many links to other articles embedded within it.

Of course, lobbyists are ultimately being employed by firms that are seeking favourable policy settings. Perhaps they are looking for lighter-handed regulation for themselves, or more regulation of their competitors. Economists refer to this sort of activity as rent-seeking, and in ECON100 and ECON110 I discuss it as one of the key reasons that we might consider monopolies (or firms with market power more generally) to be unfavourable for society. Those firms make large profits, and therefore have a large incentive to use some of those profits to protect their market position through lobbying. If government is seeking to regulate their industry or to open it to more competition (or the firms are worried that the government might contemplate doing so), then those firms will employ lobbyists to dissuade governments from those policies that won't favour the firm.

When I was an undergraduate student, I struggled to see how rent seeking was negative for society. Obviously, it seems ethically problematic. But if you take a general equilibrium framework, then if the firm spends some of its profits on lobbyists, that simply becomes income for the lobbyists, and total welfare remains effectively the same (or maybe it even increases due to the producer surplus in the labour market for lobbyists).

However, that position forgets that the market operates across multiple periods. The firm with market power is generating a deadweight loss (for an explanation of why, see the first part of this earlier post). That deadweight loss arises because the firm with market power is able to price above marginal cost. If the government was to open the market to more competition or to regulate prices, then that would force the price down and increase total welfare in the market. Therefore, if the actions of the lobbyists prevents the regulation or the competition, then it has a cost to society that can be measured by the future deadweight losses that continue to accrue. So, lobbying does potentially have real negative consequences for society, and so as a society we should care about the actions of lobbyists and their interactions with our politicians.

The value of exams as a signal

Exams have been in the news this week for all the wrong reasons. However, last week Michael Lee (University of Auckland) wrote an article in the New Zealand Herald on the real value of exams as a teaching tool rather than just an assessment:

We use exams as an encouragement tool to compel greater engagement with the material. That is actually where the real value of an exam is. When students feel the stakes are high and are unsure of what exactly will be asked, they are incentivised to take a look at everything seriously.

That's why teachers should never tell students exactly what will be examined, because 99 per cent of students will then focus only on that material, which defeats the true purpose of the exam.

In exams and in the real world, the first step to topic mastery is a general overview of key concepts and facts with as much detail as one can remember. Clearly, exams reward students that can do these things in a relevant way to answer a specific question.

A more advanced stage of mastery is the ability to creatively apply, integrate, and challenge the knowledge you have been taught. But it is difficult to get to that level if you haven't got enough base material to work with.

I have a slightly different take on the value of tests and exams. I agree with Lee that they are useful as learning exercises, especially if organised well. I disagree that we shouldn't tell students what will be examined (although I will admit that when asked what will be examined my usual answer is "everything we have covered", which is true!). However, I see tests and exams as having another important function for students, as an important signal that students can give to future teachers and employers. This relates to solving the employers' adverse selection problem that I have written about before:

Students are engaging in a sophisticated array of signals, on multiple levels. It's not possible to avoid signalling in this case, since trying not to provide a signal is itself a signal. The problem that this signalling is trying to avoid stems from private information about the quality of the student - students know whether they are high quality (intelligent, hard working, etc.), but employers don't. Employers want to hire high-quality applicants, but they can't easily tell them apart from the low-quality applicants. This presents a problem for the high-quality applicants too, since they want to distinguish themselves from the low-quality applicants, to ensure that they get the job. In theory, this could lead the market to fail, but in reality the market has developed ways for this private information to be revealed.

One way this problem has been overcome is through job applicants credibly revealing their quality to prospective employers - that is, by job applicants providing a signal of their quality. In order for a signal to be effective, it must be costly (otherwise everyone, even those who are lower quality applicants, would provide the signal), and it must be costly in a way that makes it unattractive for the lower quality applicants to do so (such as being more costly for them to engage in).

Qualifications are an effective signal (they are costly, and they are more costly for lower quality students, who face having to expend more time and effort to complete the qualification). Exams are also an effective signal for exactly the same reason (though not at the same level as the whole qualification). Because exam performance is an effective signal, high quality students can use their performance in exams to separate themselves from lower quality students, because it is very difficult for lower quality students to pass themselves off as higher quality students in the exam format. The quality of the signal is much lower for other types of assessment such as take-home tests, assignments, or group projects, where lower quality students can easily get additional help (often from the high quality students!) to boost their grades.

To me, that is one of the key reasons why we shouldn't eliminate high-stakes tests and exams from student assessment. Take-home or open-book tests, online tests, group projects, and the myriad of other assessment types that are used all have their place, and can all be valuable as learning exercises if used well. But they'll never be able to provide the same quality of signal of student quality as a test or exam.

Read more:

• Why all students need to understand adverse selection and signalling

[HT: David, one of my ECON100 tutors]

Raising the minimum wage to $20

The new New Zealand government has proposed raising the minimum wage from $15.75 to $16.50 next April, and eventually to $20 by 2021. Eric Crampton at Offsetting Behaviour covered the main points on this last month:

This isn't an end of the world bad idea, but it isn't a good idea.

The government has been targeting a minimum wage of about 66.7% of the median wage. That's already very high by international standards. If we assume median hourly wage growth continues at 3.4%, then the median wage in 2021 would be $27.43. A $20 minimum wage in 2021 would be 72.9% of the median wage...

That would put New Zealand way out in front in the OECD in terms of the ratio of minimum wage to median wage. Crampton argues that Working for Families is a better option as it is better targeted at those in need (to which I would add that there are a whole lot of middle class teen hospitality workers who will benefit from the higher minimum wage, but I don't think that's who the government really wants to benefit), and it is better supported. On the latter point, Crampton explains:

The burden of minimum wage increases is shared among disemployed workers, purchasers of the goods and services produced by minimum wage workers, and owners of firms employing minimum wage workers. The burden of WFF falls heavily on households in the 8th, 9th and 10th deciles. Both versions will have negative effects on the overall economy, but spreading it through the tax system at least tries to minimise the overall deadweight costs of raising that next dollar of wage subsidy.

A higher minimum wage isn't going to result in Armageddon (but equally, in contrast to Branko Marcetic's take, it won't be all unicorns and rainbows either). I'll be interested to see how it plays out. However, I will reiterate that the latest international research (including research on youth minimum wages in Denmark, and the recent increase in the minimum wage in Seattle) suggests that minimum wages do lead to decreases in employment (see here and here). That contrasts a lot of earlier work that called into question the simple labour market supply-and-demand model.

At least though, there is some policy consistency. If you believe that higher minimum wages are a good thing (because presumably you believe that any resulting decrease in employment will be small), you should also be in favour of reducing immigration to boost the wages of unskilled or semi-skilled workers (see my post on that point here). And on that score, the new government is making the right noises (albeit with inconsistency between the Labour and New Zealand First party positions).

Read more:

• The latest evidence supports negative employment effects of the minimum wage
• Latest research suggests the minimum wage DOES reduce employment

Regal Cinemas to introduce dynamic pricing for movies

I've written a couple of times before about pricing at movie theatres (see here and here). On the surface, movie theatre pricing seems to defy basic economic theory. The price of movies doesn't differ between high-demand movies (where we would expect higher prices) and low-demand movies (where we would expect lower prices).

Although, as I wrote in both those earlier posts there probably is some element of this dynamic (or variable) pricing, it just isn't obvious. It is hidden by the choices the movie theatre makes, about which movies are "no complementaries" and the size and configuration of the theatre in which each movie plays (where some have a greater proportion of premium seating). These choices allow movie theatres to ensure that the average movie ticket price differs between high-demand and low-demand movies.

Now, Regal Cinemas in the U.S. is about to make the variable pricing more obvious, as Bloomberg reported last month:

Regal Entertainment Group is testing demand-based pricing for films, potentially leading to higher prices for top hits and low prices for flops, a big change for an industry that typically uses a one-size-fits-all approach.

Working with app maker Atom Tickets LLC, which has lobbied theaters to try dynamic pricing, Regal plans to test the concept in early 2018 and see if it boosts revenue and fills more seats at non-peak times...

Industry executives are debating whether dynamic pricing will increase attendance. Some object to a system that would involve charging higher prices for hit movies and lower prices for unpopular movies.

In that last paragraph, it might seem obvious that dynamic pricing will increase attendance for the low-demand movies. However, it isn't at all clear whether it will be offset by lower attendance at high-demand movies (because these consumers could go to a cheaper low-demand movie instead, and some of them may choose to do so). Total attendance is of course made up of the higher attendance at low-demand movies that will now be cheaper, and possibly somewhat lower attendance at high-demand movies that will now be relatively more expensive (even if the price remains the same as before). Industry executives shouldn't be focusing on the effect on attendance though. Instead they should be looking at total revenue. In this case, the effect on total revenue could be negative, since more tickets at a lower price might not offset fewer tickets at the original price (although that seems unlikely, since the high-demand movies tend to also have fairly inelastic demand, since they have few substitutes). That potential for lower revenue would be grounds for objection from the executives, and I guess we will see in due course whether Regal Cinemas benefits from this change - they movie consumer almost certainly will.

[Update]: David Sims in the Atlantic points out the negatives of Regal's dynamic pricing approach.

Read more:

• We probably are paying more for better movies, but it's not obvious
• Pricing at movie theatres still defies logic. Or does it?

School uniform monopolies

I recall many years ago having an argument with a school administrator about uniform requirements (if I recall correctly, this was about school shorts that were the correct colour, but were not allowed because they didn't have the school logo embossed on them). My side of the argument was that the school was using its market power over uniforms to create a monopoly (there was only one uniform provider who sold the school shorts with that particular logo) and unfairly price gouge parents. So, I was interested to read this story in the New Zealand Herald last week:

The new Education Minister has planned action to stamp out "covert" fundraising by schools such as marking up uniforms to make a profit.

Chris Hipkins told the Herald the new Government's overall objective was to make sure a state school education in New Zealand was free...

"At the moment, particularly around things like the big mark-ups on uniforms, schools are finding ways of getting around the rules that they shouldn't be asking parents to pay. We are going to be taking a much firmer line on that..."

A Weekend Herald price comparison carried out earlier this year found parents with a boy and girl at secondary school could pay $700 for just the uniform basics.

The Commerce Commission has received complaints about the costs of uniforms and stationery and issued procurement guidelines, recommending schools make the supplier-selection process transparent and tell parents why deals were entered into. It is illegal to enter an agreement that substantially lessens competition in a market.

With school uniforms, there are few substitutes. If your child is going to School A, you need the appropriate uniform for School A. This gives the school considerable market power (the ability for the seller to set a price above the marginal cost of the uniform). Since most schools are not uniform producers or sellers themselves, they instead transfer that market power to a uniform provider. Usually this takes the form of an exclusive deal with the uniform provider, where that provider is the only one that can sell the school's uniforms, and in exchange the school receives some share of the profits. This creates a monopoly seller of the uniforms, and the monopoly maximises its uniform profits by raising the price. The result is that parents must pay higher prices for uniforms, which must be purchased from the exclusive uniform provider.

One might argue (as the Herald article does) that this is a covert way of increasing school fundraising, in the absence of the ability for schools to do so through higher school fees. A rational school would want to maximise this source of revenue, and they can do that by ensuring that there are few substitutes for the uniform (because, when a firm has market power, the mark-up over marginal cost can be greater if there are fewer substitutes for what they are selling). When I was at school, any shorts of the correct colour were acceptable for my school uniform. However, one way that rational schools can ensure that there are few substitutes for uniform items is to require each item to have the school logo printed or embossed on it. So now, every child must wear not just the correct colour item, but the correct colour item endorsed by the school (and sold by the exclusive monopoly uniform provider).

However, you might not be concerned with high uniform costs if you believe that the additional money you pay is going to the school. But this is probably not the case at all, because schools probably cannot capture all of the excess profits that they create through this market power. If there are many potential uniform providers, then ultimately the school can probably receive the entire profits from the market power, since they could play uniform providers off against each other until they get the best offer (equal to the entire profits from selling uniforms). But if there are few potential providers, this is not the case, and the successful bidder will capture at least some of the profits. And that is what my argument with the school administrator was about, all those years ago. I had no problem with giving the school extra money, but objected to enriching the exclusive monopoly uniform provider.

An idealistic solution to this problem would be to 'adequately' fund schools, so that they don't feel the need to create market power in the uniform market in the first place. However, that would ignore the fact that any school would be better off with a little bit more funding, and so a rational school would always engage in this practice regardless of the level of government funding they receive. The only way to prevent this practice then is to regulate against it. Labour has pledged to draw up 'guidelines' for schools. If they are enforceable, then that might be the best we can hope for, unless school uniforms were abolished entirely.

Reducing excess demand at the Great Barrier Reef

Late last year, I wrote a post about excess demand for New Zealand's Great Walks:

When a good or service has no monetary cost, there will almost always be excess demand for it - more consumers wanting to take advantage of the service than there is capacity to provide the service. Excess demand can be managed in various ways - one way is to raise the price (as suggested by Sanson). Another is to limit the quantity and use some form of waiting list (as is practiced in the health sector). A third alternative is to degrade the quality of the service until demand matches supply (because as the quality of the service degrades, fewer people will want to avail themselves of it).

The Great Walks are not the only tourist attractions that are subject to excess demand. As Michael Vardon (ANU) wrote recently in The Conversation, the Great Barrier Reef is another example:

The Great Barrier Reef is one of the world’s finest natural wonders. It’s also extraordinarily cheap to visit – perhaps too cheap.

While a visit to the reef can be part of an expensive holiday, the daily fee to enter the Great Barrier Reef Marine Park itself is a measly A$6.50. In contrast, earlier this year I was lucky enough to visit Rwanda’s mountain gorillas and paid a US$750 fee, and the charge has since been doubled to US$1,500...

I understand that some people instinctively object to the idea of trying to put monetary values on things like the Great Barrier Reef. But I think valuation helps, on balance, because it offers a way to assimilate environmental information into the economic processes through which most decisions are made. Money makes the world go around, after all.

However this should be done on the proviso that the valuation is systematic and based on sound environmental and economic data.

Vardon's article is mostly about environmental accounting (and is worth reading if you want to learn a little more about non-market valuation of natural resources). That is, it is about placing a value on the Great Barrier Reef to justify a higher visitor fee. However, it isn't necessary to estimate the Reef's value in order to reduce the tourist pressure on it. If you are worried about there being too many visitors, you simply need to raise the visitor fee. Higher prices reduce excess demand. It is really as simple as that, and if we want to protect these natural resources (Great Walks, Great Barrier Reef, or other natural resources with names that don't start with Great), then higher prices are a simple and reasonably effective way to do so.

Principal-agent problems among Sicilian firefighters

In the first week of ECON110, we talk about unintended consequences. One of the examples I ask students to consider in class is what would happen if firefighters were paid for each fire they start, rather than bulk funded. Inevitably, someone always suggests that the firefighters might start fires themselves, in order to increase their funding. I always point out that seems unlikely, and that firefighters would more likely simply spend less effort on prevention activities. It turns out though, maybe those students were right. The Guardian reported back in August:

Fifteen volunteer firefighters have been arrested in Sicily on suspicion of starting wildfires and reporting non-existent blazes so they could earn €10 (£9) an hour for putting them out.

Police in Ragusa province, in the south of the Mediterranean island, said the fire department became suspicious when it emerged that the auxiliary brigade had responded to 120 incidents compared with just 40 tackled by other volunteer teams over the same period...

Most of the team were under investigation for fraud, with several also suspected of arson, Ansa said. The island is plagued by fires in summer and auxiliary firefighters are paid €10 an hour by the state to help extinguish them.

This is also a good example of a principal-agent problem (a type of moral hazard). In this case, the fire department is the principal, and it engages the volunteers (its' agents) to fight fires. However, the fire department probably doesn't want more fires, so the incentives of the fire department (less fires) and the volunteers (more fires, so that they get paid more) are in conflict. The agents will take advantage of the fact that they are not being closely monitored by the principal, in this case by lighting fires themselves.

There are four main ways to deal with moral hazard problems (including principal-agent problems):

1. Better monitoring of the agent (just keeping an eye on the volunteers to make sure they aren't up to no good, I guess - this appears to be what has happened in this case)
2. Efficiency wages (paying a wage that is higher than the equilibrium wage, so that if the agent is up to no good, then have an incentive to behave themselves or else they lose the higher-paying job and have to work somewhere else for a much lower wage)
3. Performance-based pay (paying based on some metric of output - probably this is where things went wrong in this case, since the volunteers were paid for each fire they fought!)
4. Delayed payment (holding back some part of the agent's wages until it is clear whether they did a good job - this works for contractors, but it might not be appropriate in this case).

Performance-based pay is not always the right solution to every moral hazard problem. In this case, it might well have been the cause of the problem in the first place!

[HT: Marginal Revolution]

You might be an economist if... Butter price edition

You might be an economist if a headline like this one from the New Zealand Herald on Thursday, "NZ butter now so expensive Kiwis are turning to French butter for baking", makes you angry. But not because you're asking "how dare they raise the price of New Zealand butter so that French butter is cheaper?", but because you're asking "how can anyone think that this is newsworthy enough to turn into a headline?".

New Zealand butter and French butter are substitutes. When one substitute increases in price, consumers will buy less of the now-relatively-more-expensive substitute (New Zealand butter), and more of the now-relatively-less-expensive substitute (French butter). Simple, yes. Headline stuff, not even on a slow news day.

Are we New Zealand butter consumers supposed to rise up against the oppression of New Zealand butter sellers as a result of this article? You know what? The dairy companies selling New Zealand butter don't care. They're receiving a higher price for selling their butter on the world market. If New Zealand consumers want to buy French butter instead because it's cheaper, then that's fine by the dairy companies.

The article does leave one mystery open though, when it explains why New Zealand butter has increased in price:

According to ASB economist Nathan Penny, demand for butter skyrocketed worldwide after scientists debunked the link between animal fats and heart disease.

That makes sense. When consumers preferences shift towards a good (like butter), then demand increases, and the equilibrium price increase. What makes less sense is, why hasn't the increase in global demand for butter led to an increase in the price of French butter as well?

David Roberts on why he avoids talking about overpopulation

In the last week of ECON100 lectures, we talked about economic sustainability and, among other things, the economics of climate change. So, this recent article by David Roberts caught my attention. In the article, Roberts (an environmental journalist) explains why he avoids talking about population:

Anyone who’s ever given a talk on an environmental subject knows that the population question is a near-inevitability (second only to the nuclear question). I used to get asked about it constantly when I wrote for Grist — less now, but still fairly regularly.

I thought I would explain, once and for all, why I hardly ever talk about population, and why I’m unlikely to in the future...

It is high risk — very, very easy to step on moral landmines in that territory — with little reward.

And where talk of population control is rarely popular (for good reason), female empowerment and greater equality are a) goals shared by powerful preexisting coalitions, b) replete with ancillary benefits beyond the environmental, and c) unquestionably righteous.

So why focus on the former when the latter gets you all the same advantages with none of the blowback? That’s how I figure it anyway.

I've blogged before about my research on climate change and population, but from the alternative angle - how climate change affects the population distribution, and not how population affects climate change. Roberts operates in a more fraught space, and appears to negotiate it in an intelligent way. I encourage you to read his article, and follow up especially on the Drawdown Project (which Roberts has written about here), which "maps, measures, models, and describes the 100 most substantive solutions to global warming". You can jump straight to the rankings here. Spoiler: You may be surprised at which solutions rank #6 and #7, but potentially more surprised by the solutions that rank in the bottom five.

[HT: Marginal Revolution]

Trade and the Atlas of Economic Complexity

Last week in ECON100 we covered the gains from trade. The simple model we employ is essentially a model based on Ricardian trade, which assumes that each country specialises in producing (and exporting) goods that they have comparative advantage in producing (goods that they can produce at a lower opportunity cost), and imports goods that they have comparative disadvantage in producing (goods that they produce at a high opportunity cost). However, the real world is significantly more nuanced than this simple model, as Noah Smith noted recently:

Most academic models of international trade are pretty simplistic. Some of these models are surprisingly effective for making certain types of predictions -- for example, economists are very good at predicting how much different countries will trade with each other. But they’re not so good at predicting what kind of things the countries will specialize in, which country will have a trade deficit or surplus, how trade will affect growth, or which workers and businesses will benefit from trade...

Now, a number of economists are working on new empirical approaches that take into account the huge variety and complicated connections between the products and services that get traded across international borders.

Two such economists are Ricardo Hausmann of Harvard’s Kennedy School and Cesar Hidalgo of Massachusetts Institute of Technology. They and their research team have a theory that the more different products a country makes, the better positioned it is to grow. This idea runs counter to the conventional wisdom -- and the predictions of many standard models -- that different countries hyperspecialize in only a few goods and services. According to Hausmann and Hidalgo, countries are better off when they can make a multitude of things. Countries such as Saudi Arabia that rely on a single product will perform worse, all else equal, than countries such as Japan that can make almost anything they want.

The economists claim that their so-called economic complexity index is much better at predicting long-term economic growth than other forecasting methods based on things like the level of regulation or the amount of investment in education. They recently put out a report predicting that China’s growth will slow over the next decade, while India’s will remain rapid.

Hausmann and Hidalgo's Atlas of Economic Complexity is well worth looking at. There is a wealth of trade data, and excellent visualisations (if you click on 'Visualizations' in the top bar). For instance, here's New Zealand's exports by category for 2015 (it's much easier to see at the website):

I was surprised that raw aluminium was as much as 1.7% of exports. And here's a similar visualisation of export destinations (again for New Zealand in 2015; here's the direct link):

No surprises about China, Australia, the United States and Japan being the biggest export destinations, but Algeria (1.2%) and Egypt (1.0%) were a bit surprising to me. Anyway, there's lots more to explore on the site, and lots of surprises (try playing the 'which country is the biggest exporter of *some random product*?' game with your family or friends). Minutes of fun, guaranteed. Enjoy!

The magicians' dilemma and repeated games

Marginal Revolution University's latest video covers game theory, which is timely given that we covered this only a couple of weeks ago in my ECON100 class:

Unfortunately, like most treatments of game theory in principles of economics classes, it stops well short of what is possible. So, I want to take it further. The video does a good job of explaining dominant strategies, and correctly identifies the one Nash equilibrium. To confirm that this is the only Nash equilibrium, we should 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). Here's the game from the video (but note that I've made the payoffs easier to track by making more explicit which player gets which payoff):

And here are the best responses:

1. If Al cheats, Bob's best response is to cheat (since $6000 is better than $1000) [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 Al promises, Bob's best response is to cheat (since $15,000 is better than $10,000);
3. If Bob cheats, Al's best response is to cheat (since $6000 is better than $1000); and
4. If Bob promises, Al's best response is to cheat (since $15,000 is better than $10,000).

Note that Al's best response is always to cheat. This is her dominant strategy. Likewise, Bob's best response is always to cheat, which makes it his 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 magicians choose to cheat.

However, that still isn't the end of this. That solution is for a non-repeated game. A non-repeated game is played once only, after which the two players go their separate ways, never to interact again. Most games in the real world are not like that - they are repeated games. In a repeated game, the outcome may different from the equilibrium of the non-repeated game. In this case, the two magicians probably make their choices every week, interacting with each other many times.

The 'best' choice for each magician in a repeated game may be to promise. That makes both magicians better off. However, this outcome relies on each magician being able to trust the other. How would they ensure trust? By agreeing to play the promise strategy, and then following through on the agreement. Each magician would develop a reputation for cooperation, and the other magician would then trust them. However, if either magician were to cheat, that trust would then be broken.

Robert Axelrod wrote, in The Evolution of Cooperation, about repeated prisoners' dilemmas (like the game presented in the MRU video). He found that the optimal strategy to ensure cooperation was a tit-for-tat strategy. That involves a player initially cooperating in the first play of the game, then copying the strategy of the other player from then onwards. So, if the other player cheats, you would then cheat in the next play of the game, thereby punishing them. And if they cooperate, you cooperate in the next play of the game, thereby rewarding them.

If you don't think rewards provide enough incentive, you might try and alternative - the grim strategy. This starts off the same as tit-for-tat (with cooperation), but when the other player cheats, you start cheating and never go back to cooperating again. This maximises the punishment for cheating. Of course, it only works if the other player knows (and credibly believes) that you are playing the grim strategy.

So, while the MRU video alludes to more nuance in game theory, you can now see there is a lot more to it than a simple Nash equilibrium.