CEOs playing games

Experimental economics is incredibly useful, because it allows economists to study decision-making in circumstances when basically all of the key parameters to the decision are controlled. However, one of the main problems with experimental economics is that the study population is often made up of students (see here and here for previous posts on this topic). So, it's particularly interesting when experimental economics makes us of samples made up of 'real people'.

For instance, in a new article (open access) published in the journal Experimental Economics, Håkan Holm (Lund University), Victor Nee (Cornell University), and Sonja Opper (Lund University), report on an experiment they conducted with Chinese CEOs and "comparable people in professional roles". Their sample size is quite large for this type of study - they have 200 CEOs and 200 other professionals.

Their experiment involves game theory - essentially, the research participants were asked to choose actions in three games: (1) the prisoners' dilemma (which I have written about before, most recently here); (2) a 'battle of the sexes' coordination game (I have written about coordination games too, see for example here); and (3) a chicken game (which I have also written about before, see here). They also asked the research participants about their beliefs about what the other research participants would choose.

Now, you might be thinking that CEOs have good strategic minds, and so they should be able to do well in game theoretic settings. You might also think that CEOs would be more selfish and more aggressive in these games. In those two hypotheses, you would only be partly correct. Holm et al. find that:

...substantial differences in behavior between the CEOs and the control group, but not in the way many would expect. The CEOs were not in general closer to the Nash equilibrium prediction (assuming selfish preferences). On the contrary, the average control group behavior was closer to the Nash equilibrium in the majority of the games and did not best respond less frequently to their beliefs. The most striking and consistent pattern was that the CEOs had higher expected earnings than the comparison group in all the games. The CEOs cooperated more and played less hawkishly compared to the control group, no matter how the game was framed (abstractly or with a narrative). Compared to the control group the CEOs’ also had significantly higher average beliefs that others would cooperate in the Prisoner’s Dilemma.

More specifically, the CEOs were between 13 and 25 percentage points more likely to choose the cooperative (prisoners' dilemma) or less aggressive (battle of the sexes, or chicken) option that the control group of professionals were. Because of (or perhaps in spite of) this, they earned more overall in the games. So, it appears that CEOs really do act differently than other (otherwise similar) people. Just not in the way that we might expect.

Holm et al. argue that this may be because less aggressive choices may be helpful because they allow the CEO "to mobilize support and loyalty from employees and business partners". I think we would need a lot more research before we can draw any conclusions about the mechanisms that explain these observed differences. Hopefully, there is more research on this to come.

[HT: Marginal Revolution, last year]

The disemployment effects of Canadian minimum wages

The minimum wage debate continues to rage on, despite the weight of recent evidence that supports the theory that minimum wages reduce employment (which is what we teach students in introductory economics) - see the bottom of this post for links to some of that latest research.

Much of the debate relates to methods of identifying the effects of minimum wages on employment. Case study methods (like those employed by David Card and the late Alan Krueger in their famous 1994 paper) tend to find that minimum wages have no effect, while panel studies (involving many minimum wage changes across many jurisdictions) tend to find negative effects of minimum wages on employment.

One of the latest studies using the panel method is described in this 2017 article by Kate Rybczynski and Anindya Sen (both University of Waterloo), published in the journal Contemporary Economic Policy (sorry, I don't see an ungated version online). Rybczynski and Sen use data from Canadian provinces that includes "185 minimum wage amendments enacted by 10 provinces over a 31-year time frame" (1981-2011), and look at how the real (adjusted for inflation) minimum wage affected the employment rate (the proportion of all people employed) in each province. They find that:

...amendments to the minimum wage result in lower employment rates for male and female teens, with an absence of statistically significant gender differences. Specifically, our estimates imply that a 10% increase in the minimum wage is significantly correlated with a 1%-4% drop in teen employment rates for both genders.

Their results are robust to various alternative specifications, and variations in the data, and they also get similar results using an instrumental variables (IV) analysis. Ordinarily, IV results would be presented as the preferred results. However, I don't find the IV results to be particularly convincing, because the instruments that they use are fairly weak (this has been a problem in most studies of the minimum wage thus far). Neither do Rybczynski and Sen put much stock in their IV results, because they relegate them to a later section and base most of their discussion on the results from the panel data model (as noted in the above quote). Overall, the results support a disemployment effect of the minimum wage.

Rybczynski and Sen also find that the minimum wage has no effect on prime-aged adults (to be expected as most prime-aged adults earn much more than the minimum wage), but the minimum wage does reduce employment among prime-aged immigrants (who tend to have less human and social capital, so might be expected to earn closer to the minimum wage).

Add this paper to the weight of evidence that the minimum wage reduces employment among vulnerable (young and immigrant) workers.

Read more:

• Jeffrey Clemens on the disemployment effects of the minimum wage
• The impact of an online minimum wage
• Seattle's minimum wage, revisited
• The latest evidence supports negative employment effects of the minimum wage

Book review: Globalization and Inequality

I just finished reading Elhanen Helpman's 2018 book Globalization and Inequality. The book is essentially a 175-page literature review on the topic. However, calling it a literature review is not an attempt to denigrate the book, which is excellent. Helpman does a great job of clearly outlining the evidence spanning over two decades of research on the relationship between trade and inequality. If I had one criticism, it is that narrowing of focus. As I note in my ECONS102 class, globalization is not synonymous with trade. To be fair though, Helpman makes this point himself in the first paragraph of the preface, saying:

...I will review the theoretical mechanisms through which foreign trade and offshoring affect earnings inequality and the evidence on their quantitative effects. Other aspects of globalization, such as international capital flows or migration, will be addressed only in passing.

I guess that addressing those other aspects would have led to a much longer book. If you are interested in the topic of trade and globalisation, and can handle the economic theory (since a lot of the trade literature is theory-heavy), then this book will be good for you. If you are interested but the theory is not for you, then the concluding chapter is essentially a condensed and non-technical review and will likely give you what you need.

So, what does the literature on foreign trade and offshoring, and their effects on earnings inequality, have to say? Helpman starts by outlining the recent experience of inequality over time - a topic which I have written about before (see here and here, and the links at the bottom of those posts, for examples). He then talks through the literature, more or less in chronological order. The ordering is for good reason. As he notes in the conclusion, the early studies (from the 1990s) set the scene, finding that:

...trade did not play a large role in altering inequality.

He then goes on to outline the many modelling and methodological extensions that have been subsequently added to those earlier studies. However, despite the innovations the conclusion has not really changed:

As is apparent from this short (and selective) review of the empirical findings, globalization in the form of foreign trade and offshoring has not been a large contributor to rising inequality. Multiple studies of different events around the world point to this conclusion.

This conclusion will not be palatable to all readers, of course. However, it is based on what I believe is a thorough and balanced review. I found it gratifying that the conclusion agrees with the findings of one of my PhD students, whose work used cross-country data on trade, migration, and inequality (more on that in a future post). Trade has an ambiguous effect on inequality - arguments can be made in both directions, increasing and decreasing. The theoretical and empirical studies that Helpman reviews in this book demonstrate clearly that the net effect of trade on inequality is only small.

Coronavirus contact tracing and conditional cooperation, Part 2

No sooner had I hit 'publish' on my post yesterday on coronavirus contact tracing, than I ran across this article in The Conversation by Richard Holden (University of New South Wales). I finished up my post by noting that enforcing contact tracing through punishment was unlikely to be effective (or at least, not as effective as enforcing a lockdown). Holden rightly points out that contact tracing can also be increased through positive incentives:

The obvious way to would be to mandate its use. That’s how compulsory voting works. But Morrison has ruled that out.

As an economist, I should observe that another obvious (if less effective) means would be to provide incentives.

Joshua Gans and I advocated such an approach earlier this week.

People who install and use the app could, for example, be given a A$10 rebate on their monthly phone bill (a carrot). People who do not could be denied access to public places such as shopping centres and parks (a stick)...

The prime minister has suggested relaxing containment measures might be conditional on a certain take-up rate, suggesting another, complementary, approach – group incentives.

Imagine that any relaxation of current containment measures required a 40% take-up rate. There would be peer pressure to “do the right thing” for the whole community.

The higher the take-up, the safer it would be to lift additional restrictions.

Maybe pubs could open, with four-square-metre social distancing rules in place, if the take-up was 60%.

Perhaps with evidence of the virus remaining under control for an extended period, social-distancing measures could be relaxed further at an 80% to 90% take-up rate.

Would positive incentives work better than punishment? It's difficult to say with any certainty. However, while I like the suggestion of group incentives that Holden makes, maybe that just doubles down on the problems of conditional cooperation - if you think that you will miss out on the group incentive because not enough of the rest of the population is complying, then you will be much less likely to comply as well (and peer pressure be damned!).

Perhaps most effective would be a combination of carrot and stick? China has been using various apps to control movement of people - the apps track each person's status as being green (uninfected and free to move around), yellow (possibly infected, and restricted to home), and red (infected, and restricted to home). The app status is checked every time a person goes into or out of a building, etc. Of course, the main problem with such a system is the potential for it to worsen the digital divide - those without a smartphone (and hence, no ability to have the contact tracing app) are essentially excluded from anything that requires a green status. Perhaps then, we need government-issued smartphones?

Read more:

• The prisoners' dilemma, and why we all have to be kept in lockdown
• Coronavirus contact tracing and conditional cooperation

Coronavirus contact tracing and conditional cooperation

In a new article in The Conversation yesterday, Stefan Volk (University of Sydney) discusses coronavirus contact tracing in terms of the prisoners' dilemma (or what he terms a 'social dilemma'):

As governments look to ease general social-distancing measures and instead use more targeted strategies to stop coronavirus transmission, we face a social dilemma about the limits of cooperative behaviour...

Economists define a social dilemma as a situation where individual interests conflict with collective interests. More specifically, it is a situation in which there is a collective benefit from widespread cooperation but individuals have an incentive to “free ride” on the cooperation of others...

That is very similar to the point I made last month in relation to the coronavirus lockdown:

These people aren't stupid. They are selfish, and acting in their own self-interest. Which is why we needed to go into full lockdown, and early, if we wanted to curtail the spread of coronavirus. Any voluntary or partial measures would simply be subject to the prisoners' dilemma.

Lockdown or contact tracing, both are subject to the prisoners' dilemma. Volk then goes on to make a very interesting point in relation to real-world behaviour in prisoners' dilemma situations:

My research (with behavioural economist Christian Thöni of the University of Lausanne) confirms this.

Based on reviewing 17 social dilemma studies involving more than 7,000 individuals, we estimate no more than 3% of the population can be relied on to act cooperatively out of altruism – independent of what others do.

About 20% can be expected to act selfishly (i.e. free ride).

The majority – about 60% – are “conditional cooperators”. They cooperate if they believe others will cooperate.

Another 10% are so-called “triangle cooperators”. They behave similarly to conditional cooperators, but only to the point where they believe enough people are cooperating. They then reduce their cooperation.

The remainder – about 7% – behave unpredictably.

The majority of people are 'conditional cooperators'. In the context of a lockdown, they'll obey the rules if they believe most other people are obeying the rules. In terms of contact tracing, they'll download an app and give it access to their location, if they believe that many others are also doing so. Volk makes the point that this has implications for how the lockdown, or contact tracing, is executed. He notes that:

...we must be assured others aren’t getting away with uncooperative behaviour. In other words, free riding must be swiftly and visible punished.

Without these conditions, an expectation of widespread cooperative behaviour is merely a hope.

Punishment of the rule breakers during the lockdown appears to have been swift for some, but not all. And for the most part, New Zealanders appear to have been following the rules. However, it's hard to see how the government would enforce contact tracing - will we be fined for failing to keep a diary of all our daily contacts? It seems unlikely, which means that relying on conditional cooperation is going to be that much more difficult once the lockdown is lifted. That's why it's all the more important that the lockdown has been kept in place until the likelihood of further outbreaks has been reduced to near zero.

[Update: Read this follow-up post]

Read more:

• The prisoners' dilemma, and why we all have to be kept in lockdown

The gender gap in U.S. economics education

The gender gap in economics is a recurrent theme on this blog (see the list of links at the end of this post). This is for good reason - it is pervasive and has a number of negative effects, as noted in those earlier posts. The data outlining the gender gap is becoming more visible, including from this 2019 article by Amanda Bayer (Swarthmore College) and David Wilcox (Federal Reserve Board), published in the Journal of Economic Education (seems to be open access, but just in case there is an earlier ungated version here).

Bayer and Wilcox summarise the differences in the proportions of students studying economics by gender and ethnic group at U.S. universities. If you believe that these proportions should be anywhere near similar, it makes for depressing reading:

Women and students from historically underrepresented race/ethnicity groups graduate with a major in economics at distinctly lower rates than do their counterparts. The pattern is observed both in aggregate and within gender and race/ethnicity categories. For example, among whites, 3.0 percent of men graduate with a major in economics, whereas only 0.8 percent of women do. Among underrepresented minorities, 2.2 percent of men graduate with a major in economics, compared with 0.6 percent of women. Similarly, among both men and women, whites major in economics at higher rates than do [underrepresented minority] students.

Looking individual at each university, they find that:

At every institution in the nation where more than about 3 percent of white men graduate with a major in economics, white women graduate with a major in economics at a lower rate. URM women are similarly underrepresented at almost every institution. The underrepresentation of URM men is less stark than it is for either white women or URM women, but still notable.

Bayer and Wilcox then present a measure of inclusion that they calculate for each institution. However, while their measure is intuitive, I don't believe that it stands up to much scrutiny. They would have been much better off using a proper diversity index like Shannon's evenness index. All of the data that they use is available for you to play with at the New York Fed website, so in principle anyone can go in and calculate a 'better' index based on the data.

Probably the best contribution of this article though, is the recommendations that Bayer and Wilcox make for teachers (to "recognize their sway over the situation"; and to "think intentionally about the implications for diversity and inclusion of the mentorship that they provide"), for textbook authors and publishers (to "commission critical reviews of their own materials, with the goal of identifying how those materials can be made more inclusive along gender, race/ethnicity, and socioeconomic lines"), and for department chairs (to "give careful consideration to maximizing demographic balance among instructors, especially at the introductory level"; to "help recruit and train a diverse set of student teaching assistants"; and to "work actively to improve the culture of their departments, expressed both in formal policies and in the everyday practices of faculty and students"). They also make recommendations for university and college administrators, employers, foundations (e.g. those that fund scholarships), and for the American Economic Association.

Finally, in the conclusion they provide an interesting counterpoint to the argument that differences in choice of major by gender or ethnicity simply represents the optimising behaviour of rational students (including consideration that students act on the basis of comparative advantage):

It is counterproductive to hold an unexamined assumption that the choice of major in college or university is just an example of consumer sovereignty.

It would be nice to see our assumptions about student choices examined in more detail. I don't think we have a very good understanding at all about why many capable students do not choose to follow through on an initial interest in economics.

Read more:

• The gender gap in reviewing and editing for top economics journals
• A sobering report on the culture in the economics profession
• Could closing the gender gap in economics be as simple as providing students with information?
• Why we should care about the gender gap in economics
• Justin Wolfers on why we should care about the gender gap in economics
• Female representation in economics
• CORE on 'missing women in economics'
• More on the gender gap in economics
• The gender gap in economics

Book review: The Long Tail

When I first started teaching my ECONS102 class in 2005 (it was ECON110 in those days), one of the topics was media economics. It was interesting to teach media economics then, in particular because the media industry had been going through years of change. One of the substantial changes was the bifurcation of the market into a small number of large media firms, creating mainstream content designed for widespread consumption, and a large (and seemingly growing) number of small media firms, focused on niche sub-markets. The interesting thing was how a large number of small firms could manage to co-exist alongside the media behemoths.

Essentially, that idea of a 'long tail' of niche products or services is the topic of Chris Anderson's 2006 book, The Long Tail, which I just finished reading. The book got a huge amount of press at the time of its release, and was based on a widely acclaimed 2004 article by the same title published in Wired. I wish I had read it at the time, as it would have added a substantial breadth to the arguments in my ECON110 class. However, now in 2020, the arguments haven't been superseded (if anything the opposite), but they seem very much mainstream. So much so that a book devoted to them seems mostly unnecessary - this is why the content on media markets in ECONS102 focuses much less on the bifurcation of the market.

I still found the book to be an interesting read nonetheless, and found myself nodding along with many of the ideas. However, some of the examples seemed a little strained. For instance, the claim that the Dewey Decimal System is no longer fit-for-purpose because it makes it too difficult to find the book you want, may be true, but in a digital world it kind of irrelevant. It ignores the fact that any categorisation of products (including barcodes, or RFID tags), requires an accompanying search technology. In fact, the move to digitisation essentially makes the particular categorisation that is used unimportant, but it doesn't mean that the Dewey Decimal System could not be the categorisation of choice.

There were a few other foibles, like characterising demand curves incorrectly (they show quantity demanded against price, not sales against ranking) and arguing that the world is moving away from scarcity (it isn't - something will always be scarce, like time, or energy, or social status), which put me off. On the other hand, the sections on mass customisation were not only interesting but remain very relevant today. A sequel to this book could easily build on that material, and as it turns out, Anderson's 2014 book Makers appears to do just that.

Overall, if you were looking for a starter book to explain "market fragmentation and consumer demand for niche products", this might be a good place to start.

You wouldn't want to have a company named 'Corona' right now

Over the last year, I've written a couple of posts about the naming of companies (see here and here). In both cases, those posts highlighted the effect of naming a company after 'blockchain', and the positive effects that has on share prices (albeit temporary). Now, we are seeing the opposite effect for companies with names related to 'corona'.

A new working paper by Shaen Corbet (Dublin City University) and co-authors (including my colleagues Greg Hou, Yang Hu, and Les Oxley) looks at the effect of the coronavirus pandemic on the share market returns for three companies: (1) Constellation Brands (the owner and importer of Corona beer in the US); (2) Corona Corp (a Japanese seller of air conditioners and other household items); and (3) Coronation Fund Managers (South African financial services firm). Using hourly share price data from March 2019 to March 2020, they find that:

...all of the analysed companies exhibit strong negative hourly returns in the period after the announcement of the existence of the COVID-2019 pandemic. Further, there is an exceptionally large significant increase in hourly volatility for each of the analysed companies... There is clear evidence that Constellation Brands (STZ) and Corona Corp (5909:JP) experienced a sharp and sustained deterioration in share prices outside of that expected through market-driven forces. The reasons for so would be deemed somewhat irrational, but mostly very unfortunately driven by name association.

As was the case for blockchain-named companies in the earlier research I blogged about, company names can have seemingly irrational effects on share prices (in this case, a negative effect). As I note in my ECONS101 class when we talk about the efficient markets hypothesis, asset prices (like share prices) can deviate substantially from what would be expected based on 'market fundamentals'. Those deviations can be persistent, if market participants believe that other market participants are going to continue to act irrationally. Eventually though, there will be a return to normality. Perversely then, this might actually be a good time to buy shares in Constellation Brands, if you believe that they can weather the coronavirus pandemic storm without bankruptcy.

[HT: Les Oxley was interviewed about this research on Newshub earlier this week]

Read more:

• The share market effects of naming companies after blockchain
• Cryptocurrency company name changes; and the energy costs of bitcoin mining

Online auction sites' 'Buy now' option as price discrimination

If you've ever used an online auction site like Trade Me or EBay (and even if you haven't), you're probably familiar with the 'Buy now' option. For what is usually a higher price than the current bid, you can secure your purchase immediately, without having to wait for the whole auction to play out. You probably end up paying a higher price, but you get the goods immediately (or at least, more immediately than if you waited for the auction to finish).

This is an example of price discrimination, very similar to the example of Amazon's Super Saver Shipping that I blogged about earlier in the week. Here's what I said in that post:

In the case of Super Saver Shipping, consider two groups of consumers (impatient, and patient), and two options (Super Saver Shipping, and standard shipping). The first group of consumers is impatient, and they want their goods as soon as possible. This group can be said to have a short time horizon for their purchases. This short time horizon makes their demand for goods less elastic (less sensitive to price), so Amazon can charge this group a higher price. The second group of consumers is more patient, and they are willing to wait. This group can be said to have a longer time horizon for their purchases, which makes their demand for goods more elastic (more sensitive to price). So, Amazon should charge the second group a lower price.

The problem here is that Amazon doesn't know (for sure) which group any particular consumer belongs to. So, adjusting the price of the goods themselves isn't going to work. Instead, by offering different shipping options, the customers sort themselves into the impatient (less elastic demand) group and the patient (more elastic demand) group. Then, Amazon can charge the two groups different shipping rates, meaning that the impatient group pays more in total for the product than the patient group pays.

The principle with 'Buy now' is the same, except that instead of charging different shipping rates, 'Buy now' allows the seller to directly charge a higher price to the impatient buyers. Impatient buyers use 'Buy now' and pay the high price, while patient buyers wait for the auction to play out, and probably end up paying a lower price.

As I often say in my ECONS101 class, once you know what to look for, you realise that price discrimination is actually everywhere.

What shareholder activism and lighthouses have in common

In economics, we categorise goods as being either excludable or non-excludable. Goods are excludable if a person can be prevented from having access to them (and therefore benefiting from them). Access can be prevented through laws (property rights) that define who can access the good. A common form of access is a price - everyone who is willing and able to pay the price, can purchase the good. Goods are non-excludable if, when they are available to anyone, then they are available to everyone. In other words, there is no mechanism for preventing any person from benefiting from the good, even if they haven't paid for it.

Non-excludable goods present a problem for a market economy, because if no one can be prevented from benefiting from the good even if they haven't paid for it, then it would be difficult for any private firm to produce the good for profit. The problem here is that some people will be free-riders - people who benefit from the good without paying anything for it. It would cost a private firm to provide the good, but if few people are willing to pay for it (because they can free ride instead), then the firm may not even be able to cover its costs. The good would then not be provided - this is an example of market failure.

This is the case for public goods (goods that are non-excludable, but also non-rival, meaning that one person's use of the good doesn’t reduce the amount of the good that is available for everyone else). A classic example of a public good is a lighthouse. The light from a lighthouse is available to every ship if it is available to any ship (it is non-excludable), and one ship benefiting from the light doesn't diminish the amount of light available to other ships (it is non-rival). However, because the lighthouse light is non-excludable, it would be difficult for a private lighthouse firm to operate, because ships could easily free ride. That is why lighthouses were typically funded by the local government, often through taxes or levies on ship traffic.

Another example of a public good with a free-rider problem is shareholder activism, as explained in this article from The Conversation last year, by Salvatore Ferraro (RMIT University):

Shareholder activism... involves shareholders directly engaging with directors and executives of companies to effect change from within.

To date, little activism has been motivated by altruistic purposes. That’s partly to do with a fundamental problem that limits the ability of activism to influence corporate behaviour for non-financial reasons.

Economists call it the free-rider problem. In essence it’s the problem of individuals having little incentive to contribute to a collective resource when they can enjoy its benefits even if they don’t.

How this applies to shareholders was first outlined by Harvard academics Adolf Berle and Gardiner Means in their seminal 1932 book The Modern Corporation and Private Property.

Ownership of public corporations is generally diffused between a significant number of shareholders. Individual shareholders have little incentive to monitor senior management, because of the cost they bear while others reap benefits.

So, while shareholders (and society, depending on the proposal) could benefit from more shareholder activism, most shareholders are free-riders - preferring to receive the benefits of activism, without incurring any of the costs. Because shareholder activism is also non-rival, it is an example of a public good.

Ferraro's solution to the free-rider problem in shareholder activism is:

Big institutional shareholders in particular could be more active in ensuring boards have skilled, competent directors. They could also foster a culture of openness by supporting directors to challenge senior management without fear of putting their tenure at risk.

The problem with Ferraro's solution is that even big institutional shareholders have an incentive to free ride, unless the benefits of activism are so large that they outweigh the institutional shareholder facing all of the costs of engaging in the activism themselves (which could be true, and indeed we do see examples of activist institutional shareholders). However, that won't work where individual institutional investors have only a small stake in the company. And even if it does work, the activism will likely be limited to proposals that benefit the large institutional investors (and not necessarily those that benefit smaller shareholders, or society more generally).

In such cases, we need some other mechanism, such as an independent shareholder activist organisation that can act on behalf of all shareholders. For instance, New Zealand has the New Zealand Shareholders Association. However, these organisations are currently limited by their voluntary membership. If we were serious about encouraging shareholder activism, we would need to fund it in the same way as a lighthouse - taxes or levies on shareholders, used to fund an activist shareholder organisation.

Would that lead to the 'right' amount of shareholder activism? That depends on what you think the right amount of activism is. One thing is clear though - free-riding is not helping the cause of shareholder activism in the status quo.

Amazon's Super Saver Shipping as price discrimination

Last year I reviewed Brad Stone's book The Everything Store, about the rise of Amazon. At one point in the book, Stone talks about Super Saver Shipping as an example of price discrimination. Price discrimination occurs when a firm sells the same product to different customers for different prices, and where the difference in price doesn't arise from a difference in costs. In this case, Super Saver Shipping was made available for customers who were willing to wait a little longer for their goods to arrive, and they would end up paying a lower total price (once you factor in the shipping costs). So, essentially consumers were buying the same product, but some were paying more (and receiving the good faster) than others.

For price discrimination to work though, three conditions have to be met:

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

In the case of Super Saver Shipping, consider two groups of consumers (impatient, and patient), and two options (Super Saver Shipping, and standard shipping). The first group of consumers is impatient, and they want their goods as soon as possible. This group can be said to have a short time horizon for their purchases. This short time horizon makes their demand for goods less elastic (less sensitive to price), so Amazon can charge this group a higher price. The second group of consumers is more patient, and they are willing to wait. This group can be said to have a longer time horizon for their purchases, which makes their demand for goods more elastic (more sensitive to price). So, Amazon should charge the second group a lower price.

The problem here is that Amazon doesn't know (for sure) which group any particular consumer belongs to. So, adjusting the price of the goods themselves isn't going to work. Instead, by offering different shipping options, the customers sort themselves into the impatient (less elastic demand) group and the patient (more elastic demand) group. Then, Amazon can charge the two groups different shipping rates, meaning that the impatient group pays more in total for the product than the patient group pays.

This is an example of menu pricing (or second-degree price discrimination) - where the consumers are presented with a menu of options, and they select the one they prefer. Crucially, the seller knows that some menu options appeal to consumers with more elastic demand, and other options appeal to consumers with less elastic demand. In this case, Super Saver Shipping appeals to the impatient consumers, who have less elastic demand.

To see how this works in a bit more detail, and why Amazon should price differently for these two groups of consumers, consider the diagrams below. Both diagrams show a firm with market power (Amazon), and each diagram corresponds to one of the sub-markets. The sub-market on the left represents the patient buyers, who have more elastic demand - notice that the demand curve D1 is relatively flat (which means that a change in price will have a big effect on the quantity that these consumers demand). The sub-market on the right represents the impatient buyers, who have less elastic demand - notice that the demand curve D2 is relatively steep (which means that the same change in price would have a smaller effect on the quantity that these consumers demand, than it would for the patient consumers). The marginal cost (MC) is the same in both sub-markets - it doesn't cost Amazon any more to sell a product to an impatient buyer than what it costs them to sell that same product to a patient buyer. [*]

Amazon will maximise profits by selling the quantity where marginal revenue (MR) is equal to marginal cost (MC) - this is the standard short-run profit-maximising condition (as I discussed last week). In the impatient sub-market, the profit-maximising quantity occurs where MR2=MC, which is Q2. In order to sell that quantity in the impatient sub-market, Amazon should set the price equal to P2. The problem with that high price P2 is that in the patient sub-market, no consumers would be willing to buy the good at all. Amazon can increase profits if it charges a different price in the patient sub-market, from the price it charges in the impatient sub-market. In the patient sub-market, the profit-maximising quantity occurs where MR1=MC, which is Q1. To sell that quantity in the patient sub-market, Amazon should set the price equal to P1.

So, profit maximising across both of these sub-markets would require Amazon to sell to the patient sub-market at a low price (P1), while at the same time selling the same product to the impatient sub-market at a high price (P2). And Super Saver Shipping allows them to do just that.

*****

[*] Notice that we are drawing a constant-cost firm here (so marginal cost is equal to average cost, and all units cost the same to produce and sell). That makes our explanations a little easier than the case where marginal cost is increasing.

Player bargaining power and protests in the NFL

According to the Associated Press, the biggest sports news story of 2017 was the protests by NFL players, bringing attention to (among other things) police brutality and racism. The entire Dallas Cowboys team knelt for the national anthem before one game, while all but one of the Pittsburgh Steelers refused to leave the locker room for the national anthem in another game. However, not all players engaged in protest. Not even all African American players engaged in protest.

A 2019 article by David Niven (University of Cincinnati), published in the journal Social Science Quarterly (sorry I don't see an ungated version online), looks at the factors associated with protest amongst players in the 2017 NFL season. Using data on all 2196 players who appeared on an NFL roster that season (of whom 317 engaged in protest at least once), he found that:

...African-American players were 86 percent more likely to engage in protest than white players. This distinction is nearly matched by the effect of draft status, with first rounders 77 percent more likely to protest than seventh-round draft picks. Adding to the security effect, those with at least $1 million guaranteed in their contracts were 29 percent more likely to protest and those who had ever made a Pro Bowl were 34 percent more likely to protest.

He concluded that:

...for highly successful NFL players with guaranteed contracts, there is simply less risk associated with engaging in activism and they responded by engaging in protests during the National Anthem at far higher rates.

Players engaging in protest were risking their future career security. For those players whose career was more secure (Pro Bowlers, first round draft picks, those with guaranteed contracts), engaging in protest was less risky than players further down the roster, whose future was already uncertain.

One of the interesting things about this case is that it highlights the bargaining power (or lack thereof) that individual players are able to wield with their employers. Consider the difference between NFL and NBA players. NBA players seem to be able to get away with much more in terms of protest action than NFL players, because NBA players have more bargaining power.

NBA rosters have many fewer players (17) than NFL rosters (53 players), and fewer players are on court at a time compared with an NFL team. So, excluding a player from playing because of their protest action is likely to have a more detrimental effect on an NBA team than excluding a single player would have on an NFL team. That gives NBA players more bargaining power than NFL players, and allows NBA players to engage in more action that their employers may not agree with. And relatedly, the NBA player collective agreement is arguably more generous than the corresponding agreement for NFL players, again because of differences in players' bargaining power.

Coming back to the NFL players, players with more career security (because they are higher quality players) have more bargaining power. So, even though Niven doesn't highlight this point in the article, bargaining power is likely a key underlying explanation for differences in protest activity between players. Bargaining power really matters in the labour market, including the labour market for top athletes.

[HT: Marginal Revolution, last April]

Why are airlines in the US offering $13 cross-country airfares?

We have moved all teaching online, and my (now fully online) ECONS101 class is marching ahead. The last couple of weeks we have been covering the behaviour of firms with market power (that is, firms that have the power to set their own price). Firms with market power maximise their profits in the short run by setting the price at whatever level allows them to sell the profit-maximising quantity. As we discuss in class, this is the quantity where marginal revenue (MR) is exactly equal to marginal cost (MC). However, next week in my ECONS101 class we'll be looking in more detail at pricing strategy, and in particular we'll be talking about circumstances where it may be better for firms not to operate at the quantity where MR is equal to MC. Often, firms do this for strategic reasons (for example, as I discussed in this post a few weeks ago, about discounted toilet paper).

One strategy that firms may employ is to sell at a much lower price than the short-run profit-maximising price. So, it was interesting to read this article on View from the Wing recently:

One Mile at a Time noted $16 one way fares on American Airlines between Miami and Los Angeles. These are ‘basic economy’ fares that usually aren’t changeable (although they are right now to encourage bookings) and don’t allow advance seat assignments (but with planes empty you can more or less have any seat you wish).

These aren’t even the lowest cross country flights that are out there. For the next 30 days you can buy Fort Lauderdale – Los Angeles for just $12.89. (After that the lowest fare jumps to almost $27.)

As the article notes, those prices are below marginal cost (which is estimated at $20-$25). Why would the airlines offer airfares at below marginal cost? This is clearly not short-run profit-maximising behaviour (and is clearly not the price where MR=MC, since by definition that price must be equal to, or greater than, MC). Even if you take the view that having some consumers is better than none if the flight is going to fly anyway, selling tickets at below marginal cost would still make the airlines worse off than keeping the seats empty (because the cost of providing that seat, MC, is less than the price).

So, the airlines must be making a strategic play here. The article offers six possibilities, but I find these two the most persuasive:

1. Avoid shutdown. They want to show they still have some passengers, that people still need to get around, so that the federal government doesn’t order total shutdown of airlines. A shutdown is itself costly because it means parking planes and prepping them for storage, and pilots lose their ‘current’ status without enough takeoffs and landings.

2. Persuasive for a bailout. Consumer demand will be part of their application for bailout funding. The legislation has been passed but airlines still have to apply and their applications need to be approved.

If airlines are looking to profit-maximise and taking a long run perspective, then both of these options make sense. After all, for most airlines right now, they are concerned about their very survival. Even though they may be making losses on every passenger in the short run, avoiding being shut down completely and strengthening their case for a government bailout may result in higher profits (or, let's face it, lower losses) overall. At the least, it might help them survive into the future.

Firms' pricing strategy in the real world often isn't as simple as the MR=MC condition makes it seem. A broader perspective is often necessary for us to understand the complexity of pricing strategy, especially when firms like these airlines appear to be deviating significantly from short-run profit-maximising behaviour.

[HT: Marginal Revolution]

Subtitles help in learning a second language

If you've ever watched a movie or television show in a foreign language you're not confident in, you'll appreciate the value of subtitles. And if you've ever watched a dubbed movie or television show (with a voiceover in your language rather than the original language), then chances are you prefer subtitles (at least, I do!). But, have you ever thought about whether reading subtitles while listening to the foreign language helps your language skills?

That's the topic of this 2019 article by Augusto Rupérez Micola (Luxembourg School of Finance), Ainoa Aparicio Fenoll (Collegio Carlo Alberto, Italy), Albert Banal-Estañol (Universitat Pompeu Fabra, Spain), and Arturo Bris (IMD, Switzerland), published in the Journal of Economic Behavior and Organization (ungated earlier version here). Noting that, after World War II, most countries decided whether to dub or subtitle English-language films and television shows and have not changed their practice since, they compare the average English language proficiency of people from 'dubbing' countries with the average English language proficiency of people from 'subtitling' countries. English language proficiency is measured by the average score of people from each country who attempted the online TOEFL (Test of English as a Foreign Language) exams. Controlling for education spending, 'proximity' of the language to English (linguistically), and a number of other variables, they find that:

...a change from dubbing to subtitling translation mode in a country improves test scores by 16.9%.

The TOEFL test breaks down English language ability into reading, writing, speaking, and listening. Looking at those four domains, they find that:

All coefficients are positive and significant. The highest effect is found for listening (25.2%), followed by reading (18.3%), writing (12.6%), and speaking (11.9%). The coefficient for listening is significantly higher than the one of the average effect (16.9%).

Their instrumental variables estimates make these results plausibly causal, rather than simply correlations. So, subtitles appear to help with language learning, especially in terms of listening skills, which is what you would expect theoretically. So, I guess that when I used to find my daughter watching anime instead of studying, and she argued that it was helping her practice her Japanese, I was right to let it go.

[HT: Marginal Revolution]

The U.S.-Mexico border fence and homicides in Mexico

On Tuesday, I posted about the effect of coronavirus on the price of illegal goods, particularly in Mexico:

When goods (or people) become more difficult (more costly) to transport, the equilibrium price of those goods and services will rise. That is the case even when those goods and services are illegal.

Stricter policing of border controls make goods more difficult to smuggle. Even something as simple as building a fence will increase the costs of smuggling, even if only fractionally. Building a fence in some parts of a border, but not others, changes the incentives for smugglers, in terms of where the best places to cross the border are located. And if smugglers want to change their location, they may come into conflict with their rivals. That is the context for this recent working paper by Benjamin Laughlin (University of Pennsylvania).

Considering the construction of 649 miles of border fencing over the period from 2007 to 2011 resulting from the Secure Fence Act, Laughlin looks at how the number of homicides changed in Mexican localities within 10km of the border, before and after the construction of the fence. He finds that:

With both dependent variables [logged homicides, and homicides per capita], the localities with access to alternate smuggling routes suffered a significant increase in lethal violence that persisted for over two years. At the same time, localities near the new border fence saw a decline is violence.

Laughlin doesn't make clear in the working paper the size of the effect. Eyeballing his figures, it looks like around 2 additional homicides per 10,000 people per half year. My back-of-the-envelope calculation suggests that the additional border fence increased homicides by nearly 2000, [*] which is an appreciable amount. Laughlin argues that this arises because:

 ...the border fence restricts drug smuggling routes, which increases the value of alternate routes that circumvent the border fence. As a result of this change in the value of territory, competing drug cartels fight for control over territory that provides access to alternate smuggling routes, which leads to a spike in fatal violence. Over time, a new equilibrium is reached as cartels settle on an arrangement over territory sharing, and fatal homicides will subside.

That last sentence is important, because it explains why the increase in violence in areas without a border fence lasted for just two years before returning to the baseline level. His results are robust to the use of different control groups (of localities), and robust to controlling for the intensity of law enforcement in Mexican localities, and the capture of cartel leaders.

When Donald Trump declared in 2016 that the U.S. would build a wall and make the Mexicans pay for it, many people scoffed. However, based on these results it appears that even if the Mexicans don't have to spend a dime on wall construction, they will probably end up paying a high price.

*****

[*] In Laughlin's dataset, the average locality with no new border fence has a population of 2142, and there are 1144 such localities, which means a population-at-risk of 2,450,488. At my estimated two additional homicides per 10,000 population, that is 490 additional homicides. The model is based on half-years, so for two years that is 1960 additional homicides.

$13 cauliflower is just the beginning

Cauliflower was in the news today, for being sold at the incredibly high price of $13. That's pretty extreme of course, and may be an example of the supermarkets taking advantage of their market power. On the other hand, higher prices are an inevitable consequence of the situation we find ourselves in (and weirdly, high cauliflower prices in March seems to be a thing, as I've posted on this same topic twice before, here and here). On Tuesday I posted about the costs of illegal goods rising because of coronavirus. But legal goods are going to be hit by higher prices too. This article in The Conversation, by Michael Rose (Australian National University) outlines a number of reasons why, but this one is most relevant:

The major variable in whether the coronavirus crisis will hurt fruit, vegetable and nut supplies (and prices) depends on how they are picked while the nation’s border remains closed to the foreign seasonal workers on which Australian farmers depend...

Rural Australia’s dependence on the muscles of tens of thousands of backpackers and workers on temporary working visas is sometime minimised by official statistics...

The indefinite closure of Australia’s borders to non-resident foreign nationals jeopardises this supply of farm workers.

Pretty much the exact same dynamics will play out in New Zealand. Much of our horticulture industry relies on migrant labour, and the border closures mean that the labour is either not available, or is going to be more expensive if it is. Even if you believe that local workers laid off as a result of coronavirus could pick up the slack, local workers have proven unwilling to take up these jobs in the past (which is why we have migrant labourers doing this work in the first place). Rose quotes migration researcher Henry Sherrell in reference to Australia:

 “In theory, Australians laid off in the many sectors now facing recession could head for the countryside and start picking fruit,” he argues in an article co-authored with Stephen Howes, an economics professor at the ANU Crawford School of Public Policy.

"In practice, it is just not going to happen. The work is difficult, and farms often geographically isolated. It would take years not months to change the reality that farm work is just not in the choice set of most Australians – who, after all, live in one of the most urbanised and richest countries in the world."

A lack of horticulture workers, or more expensive horticulture workers, raises the costs of production of fruit and vegetables. This looks the same as in the demand and supply model I posted on Tuesday,

A decrease in supply of fruit and vegetables (from S0 to S1), leading to an increase in price (from P0 to P1). You may be worried about $13 cauliflower, but it is just the beginning.