Swinger economics and pricing in platform markets

I was interested to read this week this 2010 article by Fabio D’Orlando (Università di Cassino, Italy) on swinger economics (ungated earlier version here), published in the Journal of Socio-Economics. The article is exactly what you would expect from the title - it's on the economics of swinging in Italy. It's mostly a theoretical paper (there's not a lot of available data on swinging behaviour), but this bit in a footnote caught my attention, given the discussion we have in ECONS102 on platform (or two-sided) markets:

Another matter of theoretical interest could be the organization of the market, with particular reference to the supply of services for swingers. These services take the form of structures (in many cases, firms) which allow swingers to meet together, both furnishing (virtual) platforms by means of which couples advertise themselves and their wishes to get in touch with other swingers, and furnishing (physical) places in which couples can have sexual intercourse with other couples or single males in a reasonably secure environment. The way these structures operate implies network externalities and can be examined in the logic of two-sided markets... Generally, an access fee is charged for both single males and couples when joining the club, and this fee is higher for singles, lower for couples. Thereafter, single males pay high usage fees for each entry in the club, whereas couples pay discounted rates or enter the club free. It is therefore in the club owner’s interest to have the greatest possible number of single males entering the club. The problem is, and here is the two-sided aspect, that couples generally dislike situations in which there are too many single males: so, if the number of single males admitted rises over a certain level, fewer couples enter the club; and with the decrease in the number of couples also the interest (and willingness to pay) of single males to access the club decreases. Summarizing, the willingness of single males to pay depends positively on the number of couples present in the club; the willingness of couples to pay (or enter the club) depends negatively on the number of single males present in the club; and the owner’s profit depends positively on the number of single males present. These circumstances lead club owners to particular strategies, the most common being to pay prostitutes and their partners to pretend to be swinger couples, thereby increasing the couples/single males ratio in the club.

A platform (or two-sided market) exists where a firm brings together two sides of the market (e.g. buyer and seller), both of whom benefit by the existence of the platform, and both of whom may (or may not) have to pay to have access to the platform. In this case, it isn't buyers and sellers but couples (and single males), and the platform is the swingers club. The club owners face a trade-off though, because the more profitable sub-market for the club owner (single males) deters the other sub-market (couples), and it is access to the couples that the single males demand. So, without planting 'fake couples' in the club (as noted in the last sentence of the quote above), the profit-maximising swingers club owner would have to set the price for single males high enough to reduce their numbers in order to attract couples, but not so high that it deters too many of the profitable single males from paying for access to the club. Pricing in the real world is hard!

How much money would you accept to give up Facebook for a month?

If I offered you $10, would you give up Facebook for a month? What about $20? $50? $150? On the other hand, if you've already bought into #deleteFacebook, then I wouldn't need to offer you anything. Asking how much I would have to pay you to give up Facebook seems like a fanciful question, but it has an important implication.

In economics, consumer surplus is the difference between the maximum that a consumer is willing to pay for a good or service, and what they actually pay for it (the price). You can think of consumer surplus as the 'profit' (or net benefit) that consumers get from buying. In order to measure the total consumer surplus in a market, we need to measure the area between the demand curve (which shows consumers' willingness-to-pay for the good or service) and the price, for the quantity that is purchased in total. So, in order to measure consumer surplus, you need to know the demand curve for the product. In practice, observing different prices and the quantities that consumers buy at those different prices gives us an idea of the shape of the demand curve (leaving aside the identification problem for now).

But what if you have a good or service that is given away for free? How do you estimate the consumer surplus then? That's where the questions in the title and first paragraph of this post come in. And this is pretty much what some researchers did recently, as described in this new NBER Working Paper (ungated version here) by Erik Brynjolfsson (MIT), Felix Eggers (University of Groningen), and Avinash Gannamaneni (MIT). The authors use a specific type of non-market valuation called discrete choice experiments (which I have used in research before, including in this paper):

Specifically, we ask consumers to make a choice between keeping a digital good or taking a monetary equivalent compensation when foregoing it. This approach measures willingness-to-accept rather than willingness-to-pay money and experimentally varies the offered monetary values.

Which is more-or-less the same as the questions I started this post with (although in their experiment, each person was only asked the question in relation to a single monetary value). The interesting thing about their experiment is that it isn't just hypothetical:

In some of the experiments, we enforce the consumers’ choices, for instance be requiring them to give up Facebook for a given period before they get any payment. This makes their choices incentive-compatible: the rational thing to do is tell the truth when comparing alternatives options or being asked about valuations.

Yes, in order to get the money, some consumers (randomly selected) actually had to give up Facebook. Their sample was in the thousands, and they found a median willingness-to-accept (in exchange for giving up Facebook for a month) of $48.49 in 2016, which decreased to $37.76 in 2017. Looking at this willingness-to-accept, it has plausible relationships with demographic and other variables:

The usage of Facebook per week (self-reported, measured on a 5-point scale from “less than 1 hour” to “more than 14 hours”) is a significant predictor for the value of Facebook (p = 0.006). The more time a consumer spends on Facebook, the more likely they are to keep their access... Similarly, the more friends someone has on Facebook (self-reported, measured on a 6-point scale from “less than 50” to “more than 1000”) the more compensation they require to leave Facebook (p = 0.024). In terms of activities on Facebook (measured on a 6-point scale ranging from “never” to “several times a day,”) consumers perceive significantly more value in Facebook the more they post status updates or share pictures and videos (p = 0.010), the more they like and comment (p = 0.018), and play games (p = 0.025). Watching videos is marginally significant (p = 0.080), while using the messenger and chat is associated with no additional value (p = 0.100). Consistently, we find significant substitution effects due other social media services, i.e., Instagram (p = 0.025), and video platforms, i.e., YouTube (p = 0.003). Thus, consumers who also use Instagram or YouTube are more likely to give up Facebook...

...we see that female respondents are more likely to keep Facebook than male users (p = 0.011). The same holds for older consumers (p < 0.001).

The paper goes on to estimate willingness-to-accept values for other digital goods, which imply an annual consumer surplus that is as high as $17,350 for search engines (compared with just $322 for social networks collectively, including Facebook). The confidence intervals on these estimates are quite large (which is just as well - would it really take over $17,000 to get the median person to give up search engines for a year?).

The paper is written from the perspective that consumer surplus is a better measure of welfare than Gross Domestic Product (GDP). This is because, among other issues, when consumers substitute physical goods for digital goods, this reduces GDP even though it increases consumer welfare. If you're interested in thinking about better measures of national wellbeing than GDP, this is an important argument (although reading this paper is probably not the best place to start if you are interested in that - try here instead). If we wanted to better measure national wellbeing, then measuring consumer surplus in all markets (including markets where there is no price) would be a good option. But then we have to find a way to measure consumer surplus in markets where there is no price, and the Brynjolfsson et al. paper shows us one way to do this.

[HT: Marginal Revolution]

Noah Smith on capitalist lyrics in rap

Noah Smith wrote back in 2015:

The economics of rap lyrics would be an interesting subject for a pop econ book...

One interesting thing is how overwhelmingly capitalist this theme is. A number of (white) lefty humanities students I meet are quite enamored of rap, viewing it as a form of protest against the structural injustice of the capitalist system. But barely any of that has been popular for many years now. The overwhelming majority of the mainstream popular rap music from the last decade and a half has been about working hard, taking risks, reaping financial rewards, and enjoying a money-driven status-conscious consumerist lifestyle. In other words, a total and utter embrace of the capitalist dream. Of course, the successful business exploits of rappers themselves are now well-known; the capitalist dream goes way beyond music-making.

Modern rap also puts the lie to the idea, popular in right-wing media, that rap encourages a culture of poverty. That was true of gangsta rap - even if he amasses money and power, a gangster is expected to stay in his community and remain true to the lifestyle of the streets (much like the ideal of noble poverty in chivalric fiction). But modern capitalist rap is about hard work and risk-taking in the pursuit of prosperity - exactly the kind of values conservatives ostensibly want people to have. Ludacris, whose music O'Reilly has repeatedly failed to recognize for the satire that it is, even has a song advocating Randian selfishness...

I don't think I'm reading too much into these songs, either; rappers themselves are obviously acutely aware of the importance of good formal economic institutions.

The music industry, including rappers, is characterised by tournament effects. With tournament effects (which I have written about before in the context of CEOs and football players), a small group of highly successful people earn a lot, while many others accept low pay in exchange for the chance to become one of the highly successful few at some point in the future. We probably really on get to see or hear about the success stories, while the less successful fade into obscurity. And no economist would be surprised that the successful rappers are those that act like rational business owners trying to maximise their profits, which is what we expect from capitalists.

Still, I encourage you to read the whole of Noah's post. I'm not a fan of rap (rap rock like Hollywood Undead, on the other hand, is a different story). However, reading that blog post reminded me of the first verse of Forgot about Dre, and the silver Ferrari in the music video:

Capitalism writ large.

[HT: Marginal Revolution just this week, even though it was a 2015 Noah Smith post!]

Facebook as a measure of social connectedness

Economists are often maligned for not recognising the importance of social relations in research. That is somewhat unfair, since the importance of social connections or networks is well recognised in the research on migration and trade, not to mention the growing literature on the importance of social capital. However, the biggest problem with including social connections in economics research is that they are notoriously difficult to measure. So, I was quite excited to read this 2017 NBER Working Paper (ungated version here) by Michael Bailey (Facebook), Ruiqing Cao (Harvard), Theresa Kuchler, Johannes Stroebel (both New York University), and Arlene Wong (Princeton). In the paper, the authors demonstrate a new Social Connectedness Index (SCI), derived from Facebook friends data:

Specifically, the SCI corresponds to the relative frequency of Facebook friendship links between every county-pair in the U.S., and between every U.S. county and every foreign country.

The paper then goes on to demonstrate the usefulness of the SCI:

We use these data to document important geographic patterns of social networks. We also show that the SCI data can be informative about the role of social connectedness for the large number of social and economic outcomes that can be measured at various levels of geographic aggregation, such as trade, migration, and patent citations. To facilitate further research along these dimensions, the SCI data can be made accessible to members of the broader research community...

We find that the intensity of friendship links is strongly declining in geographic distance, with the elasticity of the number of friendship links to geographic distance ranging from about -2.0 over distances less than 200 miles, to about -1.2 for distances larger than 200 miles. Conditional on distance, social connectedness is significantly stronger within states than across state lines. We also show that, conditional on geographic distance, the social connectedness between two counties is increasing in the similarity of these counties along important social and economic characteristics...

After aggregating the SCI to the state level to match available interstate trade data, we document that state-pairs with higher social connectedness see larger trade flows, even after controlling flexibly for geographic distance...

We also find that when counties are more connected, they are likely to have more cross-county patent citations...

Finally, we find that more connected county-pairs see more migration and labor flows, highlighting the potential of social networks to overcome frictions involved in moving across the United States...

Overall, the findings presented in this paper suggest that social connectedness plays a large role in explaining social and economic interactions, both within and across counties.

It seems to me that there is a huge amount of potential in using the SCI data. Better still, the dataset is available to researchers, as Bailey et al. note in a footnote:

Researchers are invited to submit a one-page research proposal for working with the SCI data to sci_data@fb.com. The data will be shared for approved research projects under the terms of an NDA between Facebook and approved researchers.

The Bailey et al. analysis suffers from being correlation rather than causal, but the depth and coverage of the SCI data means that there are a lot of research questions that it could be useful for, especially in studies of migration (where social networks matter in terms of migrants' or potential migrants' decisions about where to move), immigrant assimilation (where local social networks facilitate immigrants' adaptation to their new location), entrepreneurship (where social networks may impact on business success), idea or norms diffusion (where social networks are important mechanisms for promotion), and for any application where the measurement of social capital is important.

The biggest problem may be: is this dataset still available, given the current climate surrounding Facebook and data? There is no individual data in the SCI dataset (it is made up of county-level and country-level data only), so one would hope so.

[HT: Marginal Revolution, in July last year]