Positive network externalities and the value of social media

How much is social media worth? In an interesting article in The Conversation earlier this week, Peter Martin (Australian National University) discussed the value of social media networks:

Social media is a problem for economists. They don’t know how to value it...

As the Australian Senate prepares to hold an inquiry into the impact of social media, economists meeting in Adelaide at the annual conference of the Economic Society of Australia have been presented with new findings about the value of social media that point in a shocking direction. They suggest it is negative.

That’s right: the findings suggest social media is worth less to us than the zero we pay for it. That suggests we would be better off without it.

Wait, what? There's a good that we willingly use that has negative value? People may not be purely rational decision-makers, but that will take some explaining. Here's what Martin wrote about that study:

Leonardo Bursztyn of the University of Chicago presented the findings in the keynote address to the conference...

They surveyed more than 1,000 US university students, asking a series of questions about TikTok, Instagram and Google Maps (more about maps later).

The first set of questions was designed to ascertain how much they would need to be paid (or would be prepared to pay) to be off TikTok and Instagram for a month...

The answers suggest users value these platforms a lot, on average by US$59 per month for TikTok and $47 for Instagram. An overwhelming 93% of TikTok users and 86% of Instagram users would be prepared to pay something to stay on them...

Then Bursztyn and colleagues asked a second set of questions:

If two-thirds of the students on your campus sign up to deactivate, how much would you need to be paid (or be prepared to pay) to sign up too?...

Most of the TikTok users (64%) and almost half of the Instagram users (48%) were prepared to pay to be off them, so long as others were off them, resulting in average valuations across all users of minus US$28 for TikTok and minus $10 for Instagram.

Martin notes that:

The finding is a measure of the extent to which many, many users hate TikTok and Instagram, even though they feel compelled to use them.

I'm not so sure. Maybe users dislike TikTok and Instagram that much, but there is an alternative explanation, which relates to something I cover in my ECONS101 and ECONS102 classes: positive network externalities.

An externality is the uncompensated impact of the actions of one party on someone else (a bystander). A positive externality is an externality that makes the bystander better off. For example, if I plant a nice flower garden in the front of my house, it makes me feel happy, but it also makes people walking by happier as well. The flower garden creates a positive externality for the people walking by (the bystanders). The flower garden creates value for those walkers.

A network externality means that the value of belonging to a network depends (in part) on the number of other people using the network. A positive network externality is one where the larger the size of the network, the more value each network user receives from belonging to the network. Consider Facebook as an example. If you were the only user of Facebook worldwide, you've got a place to store photos, or you can post notes to yourself. So, it provides you some value, I guess. But the value of Facebook really comes about because you can interact with your friends there. The more of your friends on Facebook, the more value it creates for you. We could tell a similar story about Instagram, or TikTok.

Now, let's consider Bursztyn's results in the context of positive network externalities. When users of TikTok or Instagram were surveyed and asked how much they would have to be paid to stop using those services for a month, they had to be paid a lot. Clearly, those services do provide value to the consumers.

Next, when the users were asked how much they would have to be paid to give up TikTok or Instagram if two-thirds of the students on their campus sign up to deactivate, the value evaporated, and became negative for many users (let's call that the 'core value' that the social network provides). Why? Because if fewer of their friends are using Instagram or TikTok, then the value from the positive network externality is much lower. They are not willing to pay much if the service doesn't provide any core value (or even negative core value), because few or none of their friends are using it (and so any positive network externality isn't enough to make it worthwhile for them to use the social network).

In The Conversation article, Martin talks about "fear of missing out" as driving the results (and so do Bursztyn et al. in the research paper that Bursztyn's keynote was based on), and that may be true to some extent, but I think that frames the total value that social networks provide in a unnecessarily negative way. We have to remember that the whole purpose of social networks is networking - interacting with others. Without the interactive and community elements, a social network might as well just be a static website. Moreover, some users do receive core value from the social network, even without the positive network externalities. 

However, it is interesting that the service (excluding any positive network externalities) of Instagram and TikTok has negative core value for many (but not all) consumers. Those consumers demonstrating a negative core value wouldn't be using the social network if their friends weren't using it. This demonstrates that while particular social networks have a stranglehold on users' attention right now, that dominance is somewhat fragile. If a new service comes along that provides a higher core value, and attracts away a sufficiently large number of users, then that can cascade into a new dominant service. That is exactly what happened when Facebook took over the social network space from MySpace, Friendster, and Bebo. Or what TikTok may be doing to YouTube right now. And this creative destruction of the dominant firms is likely to be further promoted by the 'enshittification' of these products.

We could use results like Bursztyn's to argue that social networks are a bad thing, because they provide negative core value for many consumers. Or, we could recognise that overall they do provide value, because if they didn't, then consumers wouldn't use them. Just because that value comes from the fact that many other users are also using the same network, that doesn't mean that consumers don't want these products or value them. It's just that the value mostly comes from the network, not from the product. And if someone can make a better product and create a new valuable network, then consumers will move onto this next new shiny network instead.

Read more:

• How much money would you accept to give up Facebook for a month?
• What is Facebook worth to you?

Frank DiTraglia on how to read econometrics papers

Reading economics research papers is hard work when you are doing it for the first time as a graduate student. That's why I try to get as many undergraduate students as possible engaged in some 'inspectional reading' (a term I learned from Marc Bellamare's book Doing Economics, which I reviewed here), through the Waikato Economics Discussion Group. The hardest papers to read are papers in econometrics. Hard, but unfortunately necessary for students and researchers who want to apply the latest methods to their analyses, or who want to understand fully the canonical methods in econometrics.

So, it was interesting to read Frank DiTraglia's advice recently on how to read econometrics papers. Econometrics papers don't really lend themselves to 'inspectional reading', because the purpose of reading them is to understand the methods, and the actual results and simulations used to illustrate those methods are often incidental to this purpose.

DiTraglia offers a number of tips for readers (targeted at graduate students, but of use to other readers as well), including:

1. Reading more recent articles that apply the method, or reading review articles, rather than reading the original paper that introduces a particular method;
2. Don't assume that you have to understand the whole thing when you read a paper, but focus on understanding the key ideas;
3. Don't assume that you're stupid if you don't understand the paper, because key details that the authors assume you know about may be left out of the paper (which means reading other articles is doubly important);
4. Try explaining the key ideas to someone else, because as anyone who has done any teaching can tell you, you only really recognise how little you really understand, when you go to try and teach it to someone else; and
5. Head straight to the simulation or empirical example, rather than getting bogged down in the equations.

DiTraglia offers other points of advice as well, but I think those are the key points for most people who aren't going to get deep into the weeds of how a particular method works. Personally, I can vouch for #1 and #5 as really helping me to understand some econometrics papers, but especially #1. In my experience, the first person to develop a particular method is often rubbish at explaining it. It is only the subsequent authors, applying the method themselves and writing papers (who are really doing #4 from DiTraglia's list when they write up their research), who are really helpful in understanding the method.

[HT: Both David McKenzie on the Development Impact blog, and Marginal Revolution]

Paul Blacklow on types of competition

In my ECONS101 lecture this morning, we covered market structures. In a weird coincidence, this new article on The Conversation by Paul Blacklow (University of Tasmania) was published today, also on market structures. As Blacklow notes, there are four main market structures:

In the most ideal, a perfectly competitive market, firms must use resources efficiently to produce what we consumers want at the lowest possible cost...

At the opposite extreme, in monopoly markets, there is only one seller of a good or service. Typically, there is some barrier preventing new firms from entering the market and driving prices down...

More common than monopoly is what’s called monopolistic competition, which is the market structure for many of our tech, entertainment and dining goods and services...

In Australia, many key goods and services are traded in oligopoly markets.

Oligopolies arise when a few large firms dominate a particular industry, such as supermarkets, domestic airlines, banking, mobile telecommunications, and petrol retailing.

I like Blacklow's description of the market structures, which is not dissimilar to how I describe them in class. If you are interested in learning more, I encourage you to read the article. However, in my view there are a couple of additional points to note, in relation to monopolistic competition.

First, monopolistic competition is actually more common than Blacklow suggests. He uses the examples of tech, entertainment, and dining, but the range of markets in which there is monopolistic competition is much broader than that. Monopolistic competition involves firms selling products that are differentiated from the similar products being offered by other sellers. When it comes to most of the goods that we buy, sellers are trying to differentiate themselves from their competitors who are selling goods that are otherwise very similar. As I see it, most markets are either an oligopoly (like supermarkets) or monopolistic competition (like service stations). [*]

Second, Blacklow focuses on firms differentiating their product by advertising, or research and development. Most differentiation is actually enacted through branding (which is not quite the same as advertising). [**] By branding their products, a firm can make their offering seem different to those of their competitors. For example, service stations are selling the same product (fuel), but differentiate themselves through their brand. Firms can also differentiate themselves spatially, by the location of their stores. Service stations do this as well. The make their offering different from their competitors because the location of their service stations are different. And, firms can also differentiate themselves through the range of products that they sell. Again, service stations provide a good example. Some have a minimal, convenience store range of products in-store. Others have a more upmarket cafe offering. So, there are many ways that firms can differentiate themselves from their competition, and once you realise this, you start to notice just how common monopolistic competition is.

*****

[*] There isn't really a stark distinction between an oligopolistic market and a monopolistically competitive market. Some more realistically, most markets are actually in some uncomfortable space in-between these two market structures. They may even change over time, sometimes being more oligopolistic, and sometimes more monopolistically competitive.

[**] Yes, a firm would advertise its brand as a way of differentiating its product. However, that is not the only purpose of advertising - it also changes consumer preferences, as I noted in this post from several years ago.

Unemployment and trans-Tasman migration

The New Zealand Herald reported earlier this month:

Record numbers of people leaving New Zealand to work in Australia could have a negative affect on the workforce over the medium-term.

A report by economic think tank Infometrics shows Australia’s rate of unemployment was lower than New Zealand’s in the first quarter of this year, which was a break from the average rate between 2014 and 2018 when Australia’s rate was 0.7 percentage points higher than New Zealand’s.

“There is a definite correlation between transtasman migration and the relative labour market performances in New Zealand and Australia,” Infometrics director Gareth Kiernan said in the report.

Correlation doesn't necessarily mean causation. The New Zealand Herald article's title is therefore misleading: "‘Drain’ leaves NZ’s unemployment higher than Australia". Now, there are two problems with the New Zealand Herald article here, especially in terms of the title. First, there could be reverse causation - higher unemployment in New Zealand, and lower unemployment in Australia, causing more migration, not migration causing changes in unemployment. To see why, consider the incentives for workers in New Zealand. If unemployment in Australia is lower than New Zealand, then if wages were similar, Australia would more a more attractive option. Workers would start moving to Australia. Wages are not similar though - they are higher in Australia. That increases the incentives to move from New Zealand to Australia even further. The takeaway is, though, that unemployment differences may be causing migration, not the other way around.

The second issue is that, based on a simple supply and demand model of the labour market, migration could affect unemployment in both countries, but the effect would be in the opposite direction to what the New Zealand Herald suggests. To see why, consider the diagrams below, which show the labour markets of Australia on the left, and New Zealand on the right. In both labour markets, the market wage (W1 in Australia, and WB in New Zealand) is above the equilibrium wage (W0 in Australia, and WA in New Zealand). This means that there is excess supply of labour in both countries. There are more people wanting to work than there are jobs available. That is, there is unemployment in both countries. This excess supply of labour is the difference between QS1 and QD1 in Australia, and the difference between QSB and QDB in New Zealand.

Now consider what happens as workers more from the New Zealand labour market to the Australian labour market, as shown in the diagrams below. Supply of labour decreases in New Zealand from SLA to SLC, and at the market wage, the quantity of labour supplied decreases to QSC. This decreases the excess supply of labour in New Zealand (to the difference between QSC and QDB), so unemployment decreases. In the Australian labour market, the supply of labour increases from SL0 to SL2, and at the market wage, the quantity of labour supplied increases to QS2. This increases the excess supply of labour in Australia (to the difference between QS2 and QD1), so unemployment in Australia increases. So, the migration of workers from New Zealand to Australia should have the effect of decreasing unemployment in New Zealand, and increasing unemployment in Australia, not the reverse.

Now, there are many alternative models of the labour market, aside from the model based on supply and demand for labour. However, I don't think those alternatives would suggest decreases in labour supply would increase unemployment. For example, in a search model of the labour market, fewer available workers in New Zealand might mean that job vacancies remain unfilled for longer, since it would take employers longer to find a suitable worker, but unemployment would be unaffected (on the other hand, wages would increase, because with fewer workers available, each worker has slightly higher relative bargaining power).

So, there may be a correlation between unemployment differences between Australia and New Zealand, and trans-Tasman migration. But that doesn't mean that the migration will make unemployment differences worse.