Are men's and women's soccer complements or substitutes?

Both my ECONS101 and ECONS102 classes touched on the subject of complementary and substitute goods this week (in different model contexts). Two goods are complements if consumers tend to consume them together. In that case, a decrease in the price of one good would increase the quantity that the consumer buys of both goods. Two goods are substitutes if consumers tend to consume one or the other. In that case, a decrease in the price of one good would increase the quantity that the consumer buys of the now-cheaper good, but decrease the quantity that the consumer buys of the other good (which is now relatively more expensive).

Often, it is easy to tell if goods are complements or substitutes. However, sometimes it is not straightforward. Consider the example of men's and women's soccer matches. Are they complements, or substitutes? If, when faced with the choice of whether to attend a men's or a women's soccer match, or both, fans tend to choose one or the other (and not both), then the matches are substitutes. On the other hand, if fans tend to go to both, then the matches are complements. Another way of thinking about this is that, when the price of one of the matches goes up, what happens to attendance at the other. So, if the ticket price for a men's soccer match increases and attendance at women's matches goes up, then they are substitutes, whereas if attendance at women's matches goes down, then they are complements.

Ultimately, whether men's and women's soccer are substitutes or complements is an empirical question. Fortunately, this 2025 article by Galila Nasser and Christian Deutscher (both Bielefeld University), published in the Journal of Sports Economics (open access), provides us with an answer. Or rather, they provide us with an answer in one particular context, which is German soccer.

Specifically, Nasser and Deutscher use data from the 2009/10 to 2018/19 seasons of the Frauen-Bundesliga, and look at the impact on match attendance when a Frauen-Bundesliga match is played on the same day as a men's Bundesliga match. They also consider whether the effect is larger when the overlapping men’s and women’s matches involve teams belonging to the same club. Their dataset contains 1,256 Frauen-Bundesliga matches, including 851 played on the same day as a men's Bundesliga match and 118 played on the same day as a match involving the men's team of the same club.

Controlling for the day of the week, week of the season, the weather, whether a UEFA Champions League match was also being played that day, and a variety of variables capturing the popularity of the match, Nasser and Deutscher find that there is:

...an approximately 15 percentage points decrease in attendance when women’s games coincide with men’s games on the same day.

A minor quibble with the paper is that when they say a 15 percentage points decrease, they really mean a 15 percent decrease. And the effect for matches played by the same club on the same day is somewhat larger, with attendance lower by about 16 percent. So, these results are consistent with men's and women's top-league soccer matches in Germany being substitutes (fans tend to go to men's or women's games, and not both). However, we can't conclude this for certain as the results are based on observational data so they are correlations, not causal. Nevertheless, Nasser and Deutscher conclude that:

For matches on the weekend, it is essential for clubs that have both men’s and women’s soccer teams in the first Bundesliga to avoid scheduling their matches on the same day.

Given that the seasons overlap substantially, and clubs in both leagues understandably want weekend matches, another option might be to make joint attendance at both men's and women's matches more attractive. Clubs with both men’s and women’s teams could offer a combined ticket covering matches played on different days, or even arrange occasional double-headers. As I note in my ECONS101 class, this sort of bundling can be an effective pricing strategy when there is heterogeneous demand across multiple products. Provided the variation in fans' willingness to pay for the ticket to the combined event is lower than the variation in fans' willingness to pay for the tickets separately, then bundling has the potential to increase total revenue overall. And that higher total revenue can then be shared between the men's and women's teams. Whether that would work here is another empirical question. Perhaps Bundesliga clubs could indulge us by running the experiment?

The gradual rise of high-level gaming may have shifted alcohol and gaming from complements to substitutes

When I was growing up, my friends and I spent an awful lot of time gaming. In those days, that initially meant roleplaying games like Dungeons and Dragons or MERP, or tabletop war games like Renegade Legion: Centurion or BattleTech. By the time we got to university, we still gamed, but increasingly on computers, playing hot seat games like Warlords II or Robosport. Regardless of the game though, alcohol was a key accompaniment. If gaming had been less costly (in terms of opportunity costs), we would have done more gaming, and more drinking. Gaming and drinking were clearly complements.

Not any more it seems. According to this article in the Financial Times last month (paywalled):

Gaming, video streaming and social media have had a far bigger impact on alcohol consumption than Gen Z concerns over its effect on health, according to the head of one of the world’s largest brewers.

Atsushi Katsuki, chief executive of Japan’s Asahi, said “there’s no doubt” the rise of digital entertainment platforms had hit demand for his sector’s products far more than abstinence driven by concerns over the harmful impact of drinking.

“Alcohol used to occupy a much bigger share of people’s entertainment and joy,” he told the Financial Times. “In the past 10 years, the number of entertaining things has grown including gaming, so I believe alcohol’s share of fun, enjoyment and happiness has decreased.”

If drinking is something that consumers do instead of other entertainment options, rather than alongside other entertainment options, then alcohol has become a substitute, rather than a complement, for entertainment like gaming. That's what Katsuki appears to believe.

This change might be linked to changes in the way that people game, as much as changes in the way that people drink. This 2019 article (open access) found that low-level gaming is positively associated with problem drinking. So, for people engaging in low-level gaming, alcohol and gaming may be complements (and that was probably the case for my friends and I - gaming was primarily a social activity). That research also found that high-level gaming is negatively associated with problem drinking. So, for people engaging in high-level gaming, alcohol and gaming may be substitutes (high-level gamers don't drink and game).

So perhaps over time, as gamers have gradually become more serious about their gaming, more gamers fit into the high-level category than the low-level category. And observationally, more people are gaming than before. Taking those together, the overall population-level association between alcohol and gaming may have gradually switched from complement (people drinking and gaming together) to substitute (people drinking, or gaming, but not both).

And now that young people are viewing gaming and alcohol as substitutes, it appears that alcohol is losing out. It's no wonder that Asahi and other alcohol producers are worried.

Is good research a substitute or complement for good teaching?

University lecturers engage in two main activities: teaching, and research. Some people believe that the two activities are complements. For example, higher-quality research is associated with a better or deeper understanding of the discipline, which can then be passed onto students with higher-quality teaching. On the other hand, teaching and research may be substitutes. Academics have limited time to devote to each activity, and naturally spending more time on one means less time devoted to the other. That would suggest that higher-quality research would be associated with lower-quality teaching.

So, which is it - complements or substitutes? Past studies I've written about (see here and here) haven't provided good evidence either way. So, I was interested to read this 2018 article by Ali Palali (CPB Netherlands Bureau for Economic Policy Analysis) and co-authors, published in the journal Economics of Education Review (ungated earlier version here). They first provided a much more thorough explanation than mine above of the mechanisms that might relate teaching and research:

The first type of mechanisms suggests a positive relationship between research quality and teaching quality via complementarity between skills... Conducting research can both enhance proficiency of the teacher in the subject and keep him up-to-date with the latest developments in the discipline. As a result, research activities have a positive impact on teaching quality...

The second set of mechanisms suggests a negative relationship between research quality and teaching quality. Both research and teaching activities require investment of time and effort. Time and effort spend on research reduces the amount of time and effort that can be spent on teaching, unless some activity benefits both research and teaching (e.g. reading a scientific paper can simultaneously contribute to research ideas and to teaching preparation)... A negative relation between research and teaching can also result if (contrary to the first set of mechanisms) teaching and research require a different set of skills. If research requires more specific skills (e.g. synthesis, deduction) than teaching (e.g. communication, mentoring), this can lead to disparities between skill transfers.

Palali et al. used data on student performance from over 9000 students in the BA and MA programmes at Maastrict University in the Netherlands over the period from 2008 to 2013, essentially identifying the relationship between student performance (measured by grades) and the research quality of their teachers. This approach is valid because, after students have chosen their courses:

The Scheduling Department at SBE allocates students into tutorial groups using a computer program. Once the online registration is closed, all students taking the same course are randomly assigned to tutorial groups by a computer program. Subsequently, tutorial teachers are randomly assigned to tutorial groups within a course...

The randomisation ensures that good students are not systematically paired with good teachers (or good researchers, for that matter), and means that the results of the analysis are plausibly causal, rather than simply correlations. They measure research quality using research publication, which in the first instance is a dummy variable that captures whether each academic has any research publications in the previous four years, or alternatively a measure of the total number of research publications in the previous four years. They also use measures of quality based on a dummy variable for whether each academic has any publications in journals rated 'A', 'B', or 'C' (in a classification used at Maastricht University). In their analysis, Palali et al. find that:

Only for master students a positive effect of this research quality measure is found on student grades. Students of teachers with at least one publication the past 4 years have on average 0.35 (in a scale of 0–10) higher grades than those of teachers with no publications in the past 4 years...

...the coefficient estimate for the total number of publications in the last 4 years shows that the total number of publications has no effect on student performance.

Those two measures mostly ignore research quality. However, moving onto their other measures, Palali et al. find that:

The coefficient estimate for master students shows that there is a significant positive effect on student grades for master students. Having a teacher with at least one A level publication in the last four years in associated with a 0.43 higher student grade. This suggests that in master programs students taught by teachers with high quality publications perform better, but students of teachers with many publications do not. Thus, quality seems to be more important than quantity.

So, overall, the results suggest that research and teaching are complements, but only for postgraduate (Masters-level) study. Why might that be? Palali et al. suggest that:

Most of the courses in bachelor programs are mandatory courses at the introductory level. Master courses, on the other hand, are more often elective courses, and are more specialized courses on a specific topic, and followed by students that are more interested and motivated. It is also generally the case that teachers give special topic courses which primarily focus on their field of interest. This can increase the effects of skill transfers and the effects of interactions between teachers and students.

On the other hand, Palali et al. also find little evidence for any relationship between research quality and student evaluations of teaching (also such evaluations have their own problems - see here and the links at the bottom of that post).

So, should we conclude that research and teaching are complements, or that there is no relationship between them? Before we conclude, we need to note that there is a problem with this analysis. Higher-quality teaching should manifest in students doing better in their subsequent studies, not just in the particular course they are studying in at the time. Higher student grades in courses taught by better researchers could simply mean that better researchers grade their students more generously (perhaps so they don't have to spend time on student complaints, and can therefore devote more time to high-quality research). The effect on future grades is relatively easy to check for (such as in studies on teacher value-added, see here). When Palali et al. look at future grades, they find that:

...there are no dynamic effects. Although coefficient estimates are positive, they are small in magnitude and insignificant.

So overall, it remains difficult to say whether good research and good teaching are complements or substitutes.

Read more:

• Are teaching and research substitutes or complements?
• Adjuncts are better teachers than tenured professors in introductory courses

Is Uber a substitute or complement for public transport?

Is Uber a substitute or complement for public transport? You could make arguments either way. On one hand, passengers could use Uber instead of public transport. So, if Uber becomes more available or relatively less expensive, some passengers might switch to Uber for their commuting or other journey - in that case, Uber and public transport would be substitutes. On the other hand, passengers could use Uber to solve the 'last mile' problem. The could take public transport for most of their journey, and then use Uber to 'fill in' the first or last part of their journey, which public transport cannot provide - in that case, Uber and public transport would be complements.

So, which is it? Substitutes or complements? That is the question addressed in this 2018 article by Jonathan Hall (University of Toronto), Craig Palsson (Utah State University), and Joseph Price (Brigham Young University), published in the Journal of Urban Economics (ungated version here). They use data from US Metropolitan Statistical Areas (MSAs) over the period from 2004 to 2015, and apply a difference-in-differences approach. That essentially involves comparing MSAs with and without Uber, before and after Uber was introduced to each MSA. In addition to using a straightforward binary variable to capture Uber's presence (or not), they also use a measure of the intensity of Uber's penetration into each MSA market, based on the proportion of Google searches for "Uber".

While also controlling in their analysis for total employment and unemployment rates, population, and gas prices, Hall et al. find that:

...when Uber arrives in an MSA, transit ridership does not change much, with a coefficient that indicates there is a 0.26% increase in public transit use which is not statistically significant. However... as Uber becomes more commonly used in the MSA, there is an increase in public transit use, with a standard deviation increase in Uber penetration increasing public transit ridership by 1.4%.

In other words, Uber and public transport are complements. Hall et al. suggest that:

One reason Uber is a complement rather than a substitute for the average transit agency may be that transit is still much cheaper to use. The median minimum Uber fare is $5, while transit fares average just $1. Undiscounted fares for bus or light rail are never above $3, and for those with a monthly pass the marginal fare is zero. Transit is cheaper by enough that Uber’s role in adding flexibility to the transit system is more important than its ability to substitute for riding transit.

So, Uber is simply too expensive to be a substitute for public transport for most passengers. Hall et al. then extend their analysis, and find that:

Uber most strongly complements small transit agencies in large cities. This is likely because a small transit agency in a large city provides the least flexible service in terms of when and where they travel, and so Uber’s ability to add flexibility for such agencies is valuable to riders... In addition, transit riders in larger cities tend to be wealthier, and so there is greater overlap between those who ride transit and can afford to take Uber...

Finally, Hall et al. look at the effect of Uber on commuting times, using data from the American Community Survey. If passengers are using Uber for the 'last mile' portion of their journey, that may reduce their commuting time, but increase traffic and the commuting times for others. Hall et al. find that, as expected:

For public transportation users, the coefficients are large and negative, but the results are not statistically significant, and commute times for private vehicle commuters in large MSAs or those with a small transit agency increased by 1.5–2.5%. Together these results suggest that Uber reduced commute times for public transit users while increasing congestion.

So, in most cases, and especially in large cities with small transit agencies, Uber is a complement for public transport. However, adding Uber to a city is not without cost. Commuters who are not using public transport likely face more traffic congestion as a result of Uber (as I've noted before).

Read more:

• Uber as a substitute for ambulances
• Uber and Lyft increase traffic congestion in cities
• The availability of UberX, and alcohol consumption
• Uber and alcohol-related traffic fatalities

Are international trade and migration complements or substitutes?

As migrants move from their origin country to a destination country, does that result in increased trade as well as migration? Intuitively, it seems like it would. In the simplest sense, those migrants might send goods back to family and friends at home in the origin country, and they might import goods from the home country to their destination. Causality need not run from migration to trade though. People are more likely to migrate to places that they are more familiar with, and having experienced goods from a country might increase familiarity with it - a mechanism leading from trade to migration. Either way, those explanations would suggest that international trade and migration are complements - an increase in one is associated with an increase in the other. However, the international literature has been inconsistent in its findings. Some studies find that trade and migration are complements, while other studies find that they are substitutes - an increase in trade is associated with a decrease in migration, and vice versa.

In a new working paper, my PhD student Rosmaiza Abdul Ghani and I, along with Bill Cochrane (University of Waikato) and Matthew Roskruge (Massey University) use a newly available migration dataset, along with longstanding trade flows data, to investigate these relationships. Most studies of migration and trade limit themselves to a few countries, or use migrant stocks (the number of migrants living in a particular country) as a proxy for migration. However, this dataset by Nikola Sander and Guy Abel covers migration flows between over 240 countries. And it comes with cool graphics (try them at this link).

Anyway, that data allows us to investigate the relationships between trade and migration more thoroughly than previous studies. We make use of seemingly unrelated regression, which is a technique that allows us to simultaneously model the relationships that run in both directions. We found that:

...trade and migration have positive coefficients in all of the specifications except for the fixed effects model (where, as noted above, the interpretation of the coefficients is challenging). That is, trade and migration are complements. In our preferred PPML-SUR specification, an additional migrant from country i to country j is associated with 1.7 percent higher trade flows from country i to country j, while an additional USD1000 in trade flows from country i to country j is associated with 25.4 percent higher migration flows from country i to country j.

The second of those coefficients seems a little large, but it starts from a very low base - perhaps we should have re-centered the data. In any case, the results support the story I noted at the beginning of this post - international trade and migration are positively related, so they are complements. This analysis is correlational though - we haven't established any causality here. That is the subject of the second paper contributing to Rosmaiza's PhD, which I'll blog about in a future post.

What happens when you disconnect from Facebook?

I've written a few posts on whether Facebook or internet use makes you unhappy (see here and here and here). The problem with most (if not all) earlier studies is that they show a negative correlation between Facebook use and happiness (or life satisfaction), but fail to show a causal relationship. It might be that unhappier people are more likely to use Facebook, or to more intensively use Facebook, than happier people. Or maybe there is some third factor (e.g. work satisfaction) that affects both Facebook use (more satisfied workers use Facebook less) and happiness (more satisfied workers are happier).

A new working paper by Hunt Allcott (New York University) and co-authors (recently covered by the New York Times) addresses this by using a randomised controlled trial - they randomly selected some of their 2844 research participants to switch off Facebook for four weeks, while others only switched off Facebook for one day. They then looked at the effects of that period on a battery of different measures of online and offline activity, news knowledge, political knowledge and views, and life satisfaction, based on a comparison of the treatment group (those that switched off Facebook for four weeks) and the control group (those that switched off Facebook for a single day). As is increasingly common, they had a pre-registered analysis plan, which limits the degrees of freedom to manipulate the analysis to achieve a preferred statistical result. So the results are fairly believable.

Allcott et al. found that:

Deactivating Facebook freed up 60 minutes per day for the average person in our Treatment group. The Treatment group actually spent less time on both non-Facebook social media and other online activities, while devoting more time to a range of offline activities such as watching television alone and spending time with friends and family. The Treatment group did not change its consumption of any other online or offline news sources and reported spending 15 percent less time consuming news...

The fact that Facebook use declined is not surprising, but other online activities also declined, showing that Facebook and other online activities (including online news consumption) are complements, rather than substitutes. Moving on, they also found that:

Consistent with the reported reduction in news consumption, we find that Facebook deactivation significantly reduced news knowledge and attention to politics. The Treatment group was less likely to say they follow news about politics or the President, and less able to correctly answer factual questions about recent news events. Our overall index of news knowledge fell by 0.19 standard deviations. There is no detectable effect on political engagement, as measured by voter turnout in the midterm election and the likelihood of clicking on email links to support political causes. Deactivation significantly reduced polarization of views on policy issues and a measure of exposure to polarizing news. Deactivation did not statistically significantly reduce affective polarization (i.e. negative feelings about the other political party) or polarization in factual beliefs about current events, although the coefficient estimates also point in that direction. Our overall index of political polarization fell by 0.16 standard deviations...

We might decry Facebook as a source of fake news, but it appears to also be a significant source of real news knowledge as well, as shown by the decrease in political knowledge from deactivating Facebook. To be clear, this result arises mainly because it makes people less sure about the news statements they were presented with in the survey (and asked if the statements were true, or false, or if they were unsure). As many would expect though, it appears that Facebook contributes to political polarization. Finally, in terms of happiness or life satisfaction:

Deactivation caused small but significant improvements in well-being, and in particular on self-reported happiness, life satisfaction, depression, and anxiety. Effects on subjective well-being as measured by responses to brief daily text messages are positive but not significant. Our overall index of subjective well-being improved by 0.09 standard deviations... These results are consistent with prior studies suggesting that Facebook may have adverse effects on mental health.

Interestingly, these outcomes were about two-thirds smaller than the effects measured in past correlational studies (which they demonstrate in the paper). So perhaps Facebook isn't as negative for our overall wellbeing as it has been portrayed. However, it is worth noting that the participants that deactivated Facebook were also more likely to reduce their Facebook use after the experiment concluded. Allcott et al.'s results are also:

...consistent with reverse causality, for example if people who are lonely or depressed spending more time on Facebook, or with omitted variables, for example if lower socio-economic status is associated with both heavy use and lower well-being.

Finally, their data allows them to estimate the consumer surplus of Facebook, which is essentially a measure of the total benefits generated by Facebook for consumers. [*] This is because they asked people how much they were willing to accept to deactivate Facebook for a month - a form of non-market valuation (they are not the first to do this, as I noted in this post last year). They estimate this consumer surplus for US consumers at US$230 billion to $365 billion per year. So despite the impacts on wellbeing, Facebook does generate a lot of value.

[HT: Marginal Revolution]

Read more:

• How much money would you accept to give up Facebook for a month?
• Does the Internet make people happier?
• The more you use Facebook, the worse you feel
• Quitting Facebook might make you happier

*****

[*] Strictly speaking, the consumer surplus is the amount that consumers would be willing to pay for the service, minus the amount that they actually pay. In this case, consumers don't pay anything for Facebook use (at least monetarily - we voluntarily give Facebook lots of our data, which may or may not be valuable to us!).

Would a soda tax increase alcohol sales?

Soda taxes (or taxes on sugar-sweetened beverages (SSB), if you prefer) have been in the news quite a bit recently. You can read some of the debate over whether soda taxes would be effective in fighting obesity here (Laurie Kubiak) and here (Boyd Swinburn). Eric Crampton also has a number of related blog posts (see here and here and here and here). The short version is that NZIER's report for the Ministry of Health suggests that soda taxes would be pretty ineffective.

In this post though, I want to focus on something else. Let's say a soda tax is effective, and people consume less soda. What will they consume instead? Will they switch to bottled water? Or to sugar-free beverages? Or maybe they will switch to alcohol? In other words, what will consumers substitute towards if soda is made more expensive with a tax?

A new paper in the Journal of Epidemiology and Community Health (ungated), by Diana Quirmbach (London School of Hygiene and Tropical Medicine) and others looks at exactly this question. Or rather, they look at whether consumers would purchase more alcohol if the price of soda increased. They used data on 6 million beverage purchases by nearly 32,000 UK households in 2012 and 2013, and estimate own-price elasticities for soda (separated into high-sugar, medium-sugar, and low-sugar varieties), and cross-price elasticities between soda (by type) and alcohol (beer, lager, cider, and spirits). They found that:

...own-price elasticities for non-alcoholic drinks are lower than for alcoholic beverages (that is, alcoholic drinks are more sensitive to price change), and that elasticities for all three SSB groups are inelastic (ie, smaller than 1), which means that there is a less than proportionate decrease in purchase following a price rise. This also compares with relatively inelastic (ie, insensitive) reactions to changes in the price of alcoholic drinks (except for lager for low- and medium income groups, and cider and wine for the high-income group)...

Increases in the price of high-sugar SSBs are associated with increased purchases of diet drinks, juice and lager (ie, they act as substitutes), whereas they decrease purchases of medium-sugar SSBs and spirits (ie, they act as complements). Increases in the price of medium-sugar SSBs impacts across a wider range (high-sugar SSBs, juice, water, beer, lager, wines and spirits), although all categories affected witness reduced purchasing (ie, a consistent complementary relationship of ~0.1% for a 1% price increase). Increases in the price of diet/low sugar SSBs increases the purchases for all other categories (with the exception of the two other SSB categories), ranging from 0.1% for juice to 0.7% for milk-based drinks and spirits per 1% price increase. 

In other words, a tax on soda (especially on high-sugar and diet/low-sugar sodas) would induce consumers to consume more alcohol. So, the overall effect of a soda tax on calories consumed (and hence, obesity and other health problems) is somewhat ambiguous, especially when you consider that alcohol is more energy-dense than sugary sodas. If people consume more alcohol as a result of a soda tax, the net impact on society may well be negative. Of course, this assumes that a soda tax is effective at all, which the NZIER report on the evidence thus far indicates is far from clear.

The Quirmbach et al. study does have some issues, which are common to most studies that try to estimate elasticities when prices are not directly observed. The main problems are well summarised in this article in The Conversation by Robin Room and Heng Jiang, and their main criticism is:

In principle, elasticity is about what happens over time when there is a change – such as a new tax – which results in a higher price.

But the study was not actually measuring the effects of change in price over time. Rather, it correlated how much one family bought of each beverage type when faced with a particular set of prices against how much another family bought of each beverage type with a different set of prices.

But because the study isn’t actually measuring and correlating the change that elasticities would measure – a new tax and the change in consumption over time – it offers no direct evidence of what would happen in case of a change like a new tax, and should not be interpreted as having done so.

In spite of the problems with the study, it does raise a valid question that requires further investigation. If we tax soda, should we be concerned about the negative impacts of what consumers would purchase instead?

Why the alcohol industry is a big supporter of self-driving cars

The Washington Post reports:

Automakers and tech firms have long been the ones hustling to get self-driving cars on the street. But they’ve lately been joined by a surprise ally: America’s alcohol industry.

In recent weeks, two industry groups -- one representing wine and liquor wholesalers, and another representing large producers -- have thrown their weight behind coalitions lobbying to get autonomous vehicles on the road faster.

Inherent in their support, analysts say, is an understanding that self-driving cars could revolutionize the way Americans drink. Brewers and distillers say autonomous vehicles could reduce drunk driving.

Without the need to drive home after a night at the bar, drinkers could also consume far more. And that will boost alcohol sales, one analysis predicts, by as much as $250 billion.

This week in ECONS101, we are talking about elasticities. On Wednesday, we will discuss cross-price elasticities, so this WaPo story is certainly relevant, because it suggests that alcohol and self-driving cars are complements. Complements are pairs of goods where the demand for one good is negatively related to the price of the other good. In other words, if Good A decreases in price, consumers will demand more of Good A (because of the Law of Demand), as well as more of Good B (the complementary good to Good A).

How does this relate to alcohol and self-driving cars? If self-driving cars are only lightly regulated (or left unregulated), then the cost of using them decreases (compared with if they were more heavily regulated). Consumers will be more likely to buy a self-driving car if it costs less, so light regulation of self-driving cars will increase the number of consumers who purchase them. Consumers with self-driving cars will also be able to drink more and still use their own vehicle to get home (rather than public transport or a taxi or Uber). This suggests that alcohol and self-driving cars are complements.

Not all consumers will drink more of course, but at least some who would previously have had little to drink (knowing they had to drive home) will instead drink more. More drinking means more alcohol sales, and greater profits for the alcohol industry. And that is why it makes sense for the alcohol industry to be a big supporter of self-driving cars. Forget "autonomous vehicles could reduce drunk driving": this is about the alcohol industry's potential for greater sales and profits.

So, the next obvious question is: how long will it be before the anti-alcohol public health lobby becomes anti-self-driving vehicles as well?

How airlines use extra charges to boost their profits

Grant Bradley wrote in the New Zealand Herald back in July:

Airline revenue from frequent flier schemes, charging for bags and food has grown more than 10 times in the past decade to nearly $40 billion.

A study of 10 airlines which are among the biggest ancillary earners show that in 2007 it generated US$2.1 billion ($2.87b).

Last year the top 10 tally has leapt to more than US$28 billion.

While base air fares are near historic lows, if passengers want extras they are increasingly being forced to pay for them, especially on budget carriers...

"Low cost carriers rely upon a la carte activity by aggressively seeking revenue from checked bags, assigned seats, and extra leg room seating. Some of the best in this category have extensive holiday package business with route structures built upon leisure destinations," the report says.

None of this should be terribly surprising. The airlines are making use of a simple business strategy that we discuss in ECON100: taking advantage of customer lock-in.

In the usual discussion of customer lock-in, customers become locked into buying from a particular seller if they find it difficult (costly) to change to an alternative seller once they have started purchasing a particular good or service. Switching costs (like contract termination fees) typically generate customer lock-in, because a high cost of switching can prevent customers from changing to substitute products.

In this case, once the airline customer has purchased a ticket from an airline, they are locked into travelling with that airline (and often, they are locked into a particular flight, if they have selected a ticket type that is non-transferable). The airline knows that the customer won't switch to another airline (or flight) if they charged additional fees for complementary services [*], such as for checked bags, in-flight meals, selecting their own seat, and so on.

This is a highly profitable proposition for the airlines (see Bradley's figures above), and this is because customer demand for those extra services is relatively inelastic. Once you have purchased a plane ticket for a given flight, there are few (if any) substitutes that allow you to get your checked baggage to the same destination as you are going. So your demand for checking a bag onto your own flight (if you have a bag that needs checking in) is probably very inelastic. Similarly, if you are not prepared for your flight and buy some snacks to take onto the plane with you (and/or you don't have a meal before boarding and are unwilling to wait until you land to eat), there are no substitutes to buying a meal while in the air. When there are few substitutes for a good or service, demand will be relatively more inelastic, and the optimal mark-up over marginal cost is high. As many of you will have observed, the mark-up on in-flight snacks and meals is very high. It is these high mark-ups that leads these extra charges to be highly profitable for the airlines.

While the extra charges have been increasing, ticket prices have been declining. Airlines can afford to lower ticket prices if they know they will more than make up for the lost profits on tickets with the additional profits from these extra charges. In fact, they could (and may yet) go as far as using economy-class tickets as a loss leading product! Economy-class tickets will be effective as a loss leader if demand for tickets is relatively elastic (so that lowering the price leads to a large increase in the number of ticket buyers), and where there are many close complements (so that the airline will sell a lot of the extra services, which are highly profitable). Both conditions appear to be being met, so airline economy-class ticket prices may have further to fall, but don't expect those extra charges to disappear any time soon.

*****

[*] Note that this is complementary, meaning services that are consumed along with the airline ticket, and not complimentary, meaning free!

Masturbation and partnered sex: Substitutes or complements?

That is the title of a new paper by Mark Regnerus (University of Texas at Austin), Joseph Price and David Gordon (both Brigham Young University), and published in the journal Archives of Sexual Behavior (I don't see an ungated version online). The title pretty much explains what the authors are trying to establish, using data on 15,738 adults (aged 18-60 years) from the Relationships in America study in 2014.

Essentially they are testing two competing models. The first is the compensatory model, which:

...holds that masturbation and paired sexual activity are inversely associated; that is, masturbation is an outlet for sexual energy when paired sexual activity is not possible, either due to lack of a partner or the unwillingness or inability of a partner to engage in sex as often as desired.

The compensatory model suggests that masturbation and partnered sex are substitutes. In contrast, the complementary model suggests that they are complements, i.e.

...that paired sex stimulated demand for additional sex and sexual activities, including masturbation.

Past studies have shown that men's behaviour is consistent with the compensatory model, while women's behaviour is consistent with the complementary model. However, Regnerus show that it isn't quite that simple, and that sexual contentment matters. Their results showed that:

Among men who were content with their sexual frequency, we saw few discernable trends in the likelihood of masturbation based on recent sexual frequency... However, the pattern was different for men who were sexually discontented. Among them, the odds of recent masturbation among those who have had sex 2-3 times, or 4 or more times, in the past 2 weeks were significantly lower than those who have not had sex at all in the past 2 weeks.

For women, the pattern appeared to be reversed. The odds of recent masturbation among women who reported being content with their sexual frequency were more than twice as high if they had had sex four or more times when compared to those who not had [sic] any sex in the past 2 weeks... In this way, sex and masturbation again appeared complementary among them. Meanwhile, there was no discernable association, net of controls, between frequency of recent sex and masturbation for women who reported sexual discontentment.

The concluded that:

...the compensatory model modestly fits sexually unsatisfied men, and a complementary model fits sexually satisfied women.

The main downside of this study of course is that it was based on a cross-sectional sample, so the results are correlations, not causal. They had a number of control variables, including most of the obvious ones like whether people were partnered. However, they only ever look at the differences between people, and it's possible that there is something systematically different between those who report masturbating and those who don't which isn't captured by the variables in the model. Having longitudinal (panel) data would go some way (but not all the way!) towards solving this issue, since it would allow you to observe at least some of the people in the sample at times when they are content, and at other times when they are not, and see if that affects the likelihood of reporting masturbation. Still, for the moment this is the best study on the topic and provides a more nuanced picture than earlier studies.

[HT: Marginal Revolution]