Shareholders of dating apps should be freaking out right now

My ECONS102 class has been covered the economics of information this week, including asymmetric information and signalling. So, it is timely to revisit the topic of online dating (which I have discussed earlier this year, here and here), particularly given the rise of artificial intelligence. As the Financial Times reported last month (paywalled):

Terrible news from the world of online dating. As if a parade of dubious romantic prospects and dead-end chats wasn’t bad enough, artificial intelligence has dipped its toe into the dating pool.

Eleven years ago, Tinder helped to turn dating into a series of quick-fire interactions on the internet. But for some jaded users, even writing “Hi” to a romantic prospect is now too much effort. Tech start-ups such as Rizz and YourMove AI are gaining a foothold in the sector by offering AI assistance in creating witty opening lines and appealing profiles.

Meeting strangers on the internet is by nature a random affair. Artificial chat is at least a less sinister way to help that process along than asking users to swab the insides of their mouth, as DNA-dating app Pheramor once did. But a proliferation of AI-assisted conversations suggests that eventually dating apps will simply be full of computers trying to woo other computers.

One start-up even offers the chance to watch this exact premise unfold. Teaser AI asks users questions about themselves and their personalities and then crafts AI-generated chat that is designed to mimic them. When individuals match, they can sit back and watch as their chatbots try to chat each other up.

I'm sure I wasn't the first to point out that we would eventually find ourselves in a world where one instance of ChatGPT was chatting up another instance of ChatGPT, with no humans involved. On top of being a somewhat amusing situation, there is a downside in this development. It will simply make it more difficult for someone genuinely looking for love to find a match online.

To see why, we need to discuss adverse selection. Adverse selection arises when one of the parties to an agreement (the informed party) has private information that is relevant to the agreement, and they use that private information to their own advantage at the expense of the uninformed party. In the case of online dating, the private information is the quality of each potential date. They know if they are high quality or not, but no one else knows. That could lead to a pooling equilibrium, where every online dating subscriber assumes that everyone they are matched with is low quality (because they can't tell the high quality and low quality dates apart, and assuming that every match is high quality is a recipe for disaster). High quality dates don't want to be treated as if they are low quality, so they drop out of the online dating market. Eventually, the online dating market only has low quality dates. The 'market' for high quality dates fails.

Of course, the market typically hasn't failed. People find love in online dating, so clearly the online dating apps are doing something to reduce the adverse selection problem. One thing that they do is offer the ability for subscribers to chat with the people they are matched with. Chatting allows the subscriber to work out (albeit imperfectly) who is high quality and who is low quality. When applied by the uninformed party, this is referred to as screening.

It also allows the high-quality dates to signal that they are high quality. To be effective, a signal must meet two criteria. First, the signal must be costly (otherwise everyone, even those who are lower quality dates, would provide the signal). And second, it must be costly in a way that makes it unattractive for the lower quality dates to attempt (such as being more costly for them to engage in). Engaging in witty and flirty conversation (or whatever type of conversation a subscriber is looking for, if not witty and flirty) on a dating app is costly - it takes time and effort. It will also be less costly for high-quality dates, for whom the desired type of conversation may come more naturally. It is much easier to be yourself in conversation than it is to pretend to be someone you are not. So, conversation on dating apps is an effective signal, albeit an imperfect one.

The problem with AI is that it eliminates the signalling value of conversation on the app. An uninformed subscriber should no longer find the conversation on the app to be a credible signal of the quality of the match they are engaging with. They can't use the conversation for screening either. After matching, the best option is likely to be, as I suggested earlier, in-person meet-ups.

The shareholders of online dating services should be freaking out right now. Their business model, which is built on providing high-quality matches, is under threat by AI. Once the novelty of watching their AI wingman chatting up their match's AI wingman wears off, subscribers will realise that paying for the dating app has become a waste of time. In fact, here's the share price performance over the last six months of the three biggest dating app companies, Match Group (MTCH) in blue, Bumble (BMBL) in black, and Grindr (GRND) in green (original data taken from here):

While Match is up 10.4 percent over that time, Grinder is down 19.5 percent, and Bumble is down 25.3 percent. It's not looking good.

Read more:

• Who loses status, and who gains status, with ChatGPT
• AI may be the killer app, as well as the killer of (dating) apps

Drip pricing and quasi-rational behaviour

In an interesting article in The Conversation last month, Ralf Steinhauser (Australian National University) explains the idea of drip pricing:

You see a fantastic offer, like a hotel room. You decide to book. Then it turns out there is a service fee. Then a cleaning fee. Then a few other extra costs. By the time you pay the final price, it is no longer the fantastic offer you thought.

Welcome to the world of drip pricing – the practice of advertising something at an attractive headline price and then, once you’ve committed to the purchase process, hitting you with unavoidable extra fees that are incrementally disclosed, or “dripped”.

Drip pricing – a type of “junk fee” – is notorious in event and travel ticketing, and is creeping into other areas, such as movie tickets. My daughter, for example, was surprised to find her ticket to the Barbie movie had a “booking fee”, increasing the cost of her ticket by 13%.

Steinhauser then goes on to explain why consumers are susceptible to drip pricing, blaming present bias and loss aversion:

In the case of booking that hotel room, you could abandon the transaction and look for something cheaper once the extra charges become apparent. But there’s a good chance you won’t, due to the effort and time involved.

This is where the trap lies.

Resistance to the idea of starting the search all over again is not simply a matter of laziness or indecision. There’s a profound psychological mechanism at play here, called a present-bias preference – that we value things immediately in front of us more than things more distant in the future...

Beyond the challenge of starting over, there’s another subtle force at work when it comes to our spending decisions. Drip pricing doesn’t just capitalise on our desire for immediate rewards; it also plays on our innate fear of losing out.

This second psychological phenomenon that drip pricing exploits is known as loss aversion – that we feel more pain from losing something than pleasure from gaining the same thing...

Imagine you’re booking tickets for a show. Initially attracted by the observed headline price, you are now presented with different seating categories. Seeing the “VIP” are within your budget, you decide to splurge.

But then, during the checkout process, the drip of extra costs begins. You realise you could have opted for lower-category seats and stayed within your budget. But by this stage you’ve already changed your expectation and imagined yourself enjoying the show from those nice seats.

Going back and booking cheaper seats will feel like a loss.

In my view, Steinhauser is absolutely correct that drip pricing exploits consumers' quasi-rationality (that is, that consumers are subject to biases in their decision-making). However, he is not fully correct about the sources of the quasi-rational behaviour.

First, present bias would tend to work against drip pricing, because (using Steinhauser's example) consumers are weighing up the cost of the tickets (which they face now) against the benefit of the concert they will attend (which is in the future). If consumers weigh the present more heavily than the future, then the costs weigh more heavily than the benefits, which would work against the consumers paying the junk fees.

Second, Steinhauser is correct about loss aversion, but for the wrong reason. Nobel Prize winner Richard Thaler noted that people engage in mental accounting related to particular decisions. People like to keep their mental accounts in positive balances, and are reluctant to give up on something if the mental account has a negative balance, because that would result in 'booking a loss'. Since people are loss averse, they will only want to close mental accounts that have a positive balance.

What does that mean for a consumer buying a concert ticket? They have spent some time and effort selecting their seats and completing most of the booking process. That puts their mental account for the concert into a negative balance. So, facing a small additional fee seems like a good deal, when compared to closing the mental account with a loss. The consumer pays the fee. They don't necessarily feel happy about it, but it is better than the alternative. The only way to get their mental account for the concert into a positive balance is to attend the concert.

A related way of thinking about the process of buying concert tickets with junk fees is the concept of switching costs. Switching costs are the costs of switching from one seller to another, or from one good or service to another. In this case, for a quasi-rational consumer who is running a mental account for the concert, giving up on buying the ticket when they are faced with the junk fees creates a switching cost - the loss in their mental account. When consumers face high switching costs, they can become locked in to buying a product. The seller can then take advantage of their locked in consumers by increasing the price (which is what the junk fees effectively do).

If you are a strong believer in the tenets of neoclassical economics, then the consumer response to drip pricing seems somewhat at odds with rational behaviour. For a purely rational consumer, the time and effort spent on the booking process up to the time that they face the additional of the junk fees is a sunk cost. It shouldn't affect the decision about whether to proceed with buying the ticket or not, because that decision should depend only on the costs and benefits of attending the concert. If the junk fees increase the costs of attending the concert to such an extent that they are higher than the benefits of attending the concert, a purely rational consumer would stop the ticket-buying process at that point. However, a quasi-rational consumer, who is running a mental account for the concert, would be more likely to proceed with the purchase even when presented with the junk fees.

So, overall, drip pricing leads to more sales if consumers are quasi-rational than if consumers are purely rational. It's lucky (and very profitable) for the ticket sellers that so many of us are not purely rational consumers.

Agricultural labour and the market for agricultural land

Back in 2021, I wrote a post about a shortage of agricultural labourers on Australian farms. Australian farmers were offering incentives to attract New Zealand farm labourers to move to Australia. I want to revisit that post, but this time from the perspective of the New Zealand markets for agricultural labour and agricultural land.

First, consider the market for labour, as shown in the diagram below. The market starts in equilibrium, where the demand curve D0 meets the supply curve S0. Equilibrium agricultural wages are W0, and Q0 agricultural labourers are employed. As Australian farmers attract New Zealand farm labourers to cross the Tasman, this decreases the supply to S1. That pushes the equilibrium agricultural wage up to W1, and decreases the quantity of agricultural labourers employed to Q1.

How does that affect the market for agricultural land? The demand for agricultural land depends on the value of the marginal product of land. With fewer agricultural labourers available to work the land, the marginal product of land (the amount of production from the next hectare of land) will decrease. That means that the value of the marginal product of land will also decrease - land is not providing as much value to farmers. Now consider the market for agricultural land shown in the diagram below. The market starts in equilibrium, where the demand curve DA meets the supply curve SA. Equilibrium land rents are RA, and QA agricultural land is being utilised. As the value of the marginal product of land decreases, the demand for land decreases to DB. That decreases the equilibrium land rent to RB, and decreases the quantity of agricultural land being utilised slightly, to QB.

It is little wonder that New Zealand farmers were worried about Australian farmers attracting New Zealand farm labourers to leave. Even without considering farm profits directly, not only would it increase farm wage costs, but it would decrease the value of land (which is, as you may expect, related to the rental value of land).

Read more:

• This is how the market responds to shortages of agricultural labour

National's tax policy and the goals of government

In my ECONS102 class, we talk in the first week of class about decision-makers' goals. The goal of people is to maximise utility (satisfaction, or happiness). The goal of firms is to maximise profits. So far, so good. 

The goal of government is not so straightforward. The starting point is that the goal of government is to maximise the wellbeing of the population. When we're talking about markets, that translates into maximising economic welfare (what economists refer to as allocative efficiency). However, we must always remember that government is made up of legislators who are people, who have their own individual goals (they are trying to maximise utility). One way that legislators may maximise their own utility is by maximising their chances of getting re-elected. Maximising re-election chances may not be consistent with maximising the wellbeing of the population. That tension is one of the key insights of the theory of public choice.

One example where political goals trump allocative efficiency is when some of the economic welfare generated by a market goes to non-voters. Since, by definition, non-voters don't vote, legislators may feel much less inclined to protect those market participants from harm. Taking that point even further, if government can find ways of capturing welfare from non-voters and transferring that welfare to voters, that might be a good option for the legislators themselves, by increasing their chances of re-election.

Now, consider National's new tax policy proposals in light of this. As this article in The Conversation from earlier this week, by Jonathan Barrett and Lisa Marriott (both Victoria University of Wellington), notes:

The National Party’s newly released tax package makes a clear and politically prudent play for the middle-income vote. Proposing to alleviate the financial pain of this “squeezed middle”, it may be key to determining who forms the next government...

To ensure the package is revenue neutral, four new taxes will be introduced. If the policy is aimed at those who vote, then three of the new taxes are aimed at shifting the tax burden to those who cannot vote.

The Foreign Buyer Tax (FBT) will be levied at a flat rate of 15% on residential properties worth more than NZ$2 million bought by non-residents.

A second stream of revenue will come from a tax on offshore gambling.

And a third will be from cost recovery from immigrants to cover public spending on the immigration system. To be competitive, charges will not exceed 90% of corresponding Australian immigration charges.

These proposals would cost voters very little, but increase the tax revenue generated from non-voters. Additional financial benefits can then be transferred to voters:

National has announced four key initiatives as part of its tax plan, with implications for those on middle incomes, as well as those at the top and bottom of the income spread:

• shifting income tax brackets to compensate for inflation

• expanding tax credits to reach more modest income earners

• introducing the “FamilyBoost” childcare tax credit (while ending Labour’s extension of 20 hours’ early childhood education for two-year-olds that was scheduled to start in July 2024)

• increasing Working for Families tax credits for working families (from July 2024).

It will be interesting to see how well these proposals are received by the electorate. An overall package that costs voters little, but benefits them financially, could be a winning strategy. Of course, there are limits to how much tax non-voters are willing to bear, but National may not care so much about that. On the other hand, there are other issues with the proposal, and the foreign buyers tax has come in for specific criticism already. Ultimately, we'll find out how successful this strategy is on Election Night in October!