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]

Evergreening viagra

Following on from yesterday's post about market power, another way that sellers can reduce competition and increase their market power is to sell a patented product. Patents grant a time-limited right to produce and sell a given product, and prevent competition for that particular product (although close substitutes can arise). Patents are particularly effective in pharmaceutical markets (as I've written about before, here and here). However, because they are time-limited (for example, twenty years in New Zealand), a firm's market power reduces substantially when the patent ends. Market power isn't entirely extinguished though, as even if generic versions of the product enter the market, the original supplier will continue to benefit from brand recognition (the generic products are not quite perfect substitutes for the original product).

Rather than allowing the patent to expire, what if it was possible to extend the patent for a further period of 20 years? In most cases, this isn't possible, but in the case of pharmaceutical products, it is. This is because, if a new use for the pharmaceutical product can be established, it can be patented for the new use. This is called evergreening. Which brings me to this story from the New Zealand Herald last month:

A major New Zealand Australia clinical trial has found some evidence that mothers taking Viagra during pregnancy could help babies suffering from stunted growth in the womb.

Viagra is used to treat male erectile dysfunction by dilating blood vessels in the pelvis. The researchers wondered whether it might work the same way in women by increasing blood supply to the placenta...

The study is part of a wider network of four trials across five countries.

Of course, if it turns out that Viagra (or sildenafil) is an effective treatment for babies suffering from stunted growth, then that is a great thing. And not just for the babies. Pfizer (the patent-holder for Viagra) would have protection from generic versions of sildenafil for another twenty years, meaning another twenty years of market power - not just for Viagra used for treating babies, but Viagra used for all treatments (including the highly profitable market for treating erectile dysfunction). A really cynical person would probably recognise that the sudden interest in new uses of Viagra now (the four trials mentioned in the article are not the only trials trying to find new uses for Viagra - see here for another example) is because Viagra comes off patent in April 2020. The clock is ticking for Pfizer, if they want to keep milking their Viagra cash cow.

Why are social workers like sex workers?

I guess there is more than one answer to the question in the title of this post, but the one I have in mind is that both social workers and sex workers have been in the news in the last few days because of fairly transparent attempts to increase (or rather, maintain) their market power. Market power exists when a seller (or sometimes a buyer) has the ability to effect the market price (in the case of workers, this is their wages). For a seller, this allows them to charge a price that is above their costs, and make a profit.

There are many ways that sellers can gain market power. However, two of the most effective ways are: (1) by limiting the ability of their competitors to compete effectively; or (2) by restricting the ability of potential competitors to enter the market and compete with them. In both cases, because buyers/customers/clients have less choice, the seller can raise their price above their costs (which they would find more difficult if there was more competition in their market). In the case of social workers and sex workers, both have been advocating for restricting the entry of potential competitors into their markets in the last few days.

First, on social workers, Emanuel Stoakes (advocacy and communications co-ordinator for the Aotearoa New Zealand Association of Social Workers) wrote in the New Zealand Herald today:

The social work profession in Aotearoa New Zealand is at a turning point. A crucial decision is about to be made that could have long-term implications for social workers across the country.

The threat is a section of the Social Work Registration Legislation Bill which is before Parliament's social services select committee. If the bill remains as it is, it could mean up to 50 per cent of currently registered social workers and practitioners with a social work qualification in roles not described using the words "social worker" will not be required to be registered, meaning they can operate without any accountability.

Occupational licensing is one way that workers can obtain market power. Sometimes, occupational licences make sense, such as when customer safety is at stake. In other cases, occupational licences make less sense. Either way though, the result is a decrease in competition for licensed practitioners from the unlicensed hordes that might compete with them, and a consequent increase in their market power. You might agree with Stoakes that social workers (or anyone doing social work even though their job title is not 'social worker') should be licensed. That's fair enough. But it doesn't mean that the licensing regime wouldn't exclude at least some potential workers who could do a quality job (such as those with social work qualifications from countries, where the degree is not 'recognised' in New Zealand). And excluding those unlicensed 'competitors' raises the market power of social workers.

What about sex workers? They are much more direct about the effects of competition on their earnings, as noted in this article in yesterday's New Zealand Herald:

New Zealand sex workers are furious that foreign prostitutes who come on temporary visas can advertise their services here despite it being illegal for them to work.

High profile escort Lisa Lewis is one of several who have taken their complaints to Immigration New Zealand (INZ) and the Minister of Immigration Iain Lees-Galloway - calling for a harsher stance against migrant sex workers...

She wants INZ to shift its focus from just deporting migrant sex workers to punish those that profit from helping the promotion of these illegal sex workers.

Lewis said the increase in number of foreign prostitutes coming over has hit local sex workers in the pocket.

"Many of the girls no longer meet the same quota as they did a few years ago," she said...

Another sex worker, who spoke to the Herald on the condition of anonymity, said her income had halved from about $12,000 weekly to about $6000 in the last two years...

"We can't compete with the type of services they offer, and besides it is illegal for us to do so," she said.

"But the fact is, every dollar that these migrant prostitutes make is a dollar taken from the back pockets of New Zealand working girls."

The laws restricting foreign sex workers from operating in New Zealand are there for good reason - to prevent cross-border human trafficking into New Zealand. However, if effective (which it seems they are not completely) they have the effect of reducing competition and giving domestic sex workers additional market power.

Both social workers and sex workers have been advocating for greater market power. However, isn't it interesting that only the sex workers are open about it?

If you're not already studying towards a double major, you should be

For a long time, I've been of the view that for most students, a double major is a better option than a single major. This is for two main reasons. First, it opens more options in terms of employment, especially if the two majors are not strongly overlapping (so accounting and economics, to me, is a better combination than finance and economics). Second, it allows a student to go deep into both disciplines, whereas a single major plus a bunch of disparate electives or a single major alone does not. In the latter case (a single major alone, with minimal electives) may allow extra depth in that discipline, but in many cases there may not be enough course options to only choose a single major (as is the case at Waikato now, where we have substantially curtailed the number of paper options in each major).

Anyway, aside from my own views, is there evidence to support the contention that a double major is better? Yes, there is. A 2008 paper by Alison Del Rossi (St. Lawrence University) and Joni Hersch (Vanderbilt University), published in the journal Economics of Education Review (sorry I don't see an ungated version online), uses data from 66,825 U.S. students in 2003 to answer the question.  They first grouped majors into five groups:

...arts/social science, which includes arts, humanities, social science and other majors; business, which includes economics; education; engineering; and science/math, which includes math, computer science, and science majors.

Then they looked at earnings for single majors, double majors where both majors were in the same group, and double majors where each major was in a different group. Here's what they found:

In the full sample, the results indicate that having a double major significantly increases earnings, with earnings 1.4% higher than for those without a double major. However... the premium for a double major is limited to those whose highest degree is a bachelor’s degree, with a premium of 2.3%. Even though the rate of double majoring is higher among those who achieve graduate degrees, having a double undergraduate major does not increase earnings controlling for level and/or field of the post-bachelor’s degree. The most likely reason is that the highest degree has the primary influence on earnings.

So, a double major is worthwhile (in terms of higher earnings), unless you go on to get a graduate degree (e.g. a Master's degree). Interestingly:

...having an additional bachelor’s degree has no significant effect on earnings, but the returns to graduate degrees are substantial with MBAs and professional degrees having the greatest impact on earnings.

So, in our context, a conjoint degree might not be so worthwhile (as well as those students having a lower odds of completing their double degree). Coming back to majors though, the choice of single major matters:

...majoring in engineering produces the highest return for those with a single major, with a return of about 33%. For those with a bachelor’s degree only, having only one major in business has the next highest return for a single major, 17% higher than a single arts/social science major.

Remember that economics is a business major in this research. And for double majors:

...having two business majors provides returns that are 10 percentage points higher than returns to a single major in business, while those with two education majors have returns that are 5 percentage points higher than those who have a single education major. Aside from those two cases, graduating with one or two majors within the same general area yields about the same relative returns. Notably, having two engineering majors or two science/math majors has no increased return relative to having a single engineering or single science/math major...

The combination of business and science/math has a higher return than either major individually, 10–16 percentage points higher than having a single business major and 11–12 percentage points higher than having a single science/math major for the two subsamples, respectively.

That seems to bode well for students doing economics as part of a double major in a business degree, or combining economics with science or maths. Interestingly, they find similar results for both genders, although:

...females have higher returns than males to engineering and science/math majors, for single majors and most double major combinations including those fields.

Although the U.S. setting is different from New Zealand, Del Rossi and Hersch's paper does provide some suggestive evidence that doing a double major is worthwhile. I may be biased, but I would add that having economics as one of those majors would be an advantage.

Why we should care about the gender gap in economics

In a post I wrote last year, I was challenged a little in the comments as to why I thought the gender gap in economics needed to be narrowed. My (weak) response was that we lose something by being out of balance. What we lose of course is diversity of opinion, to the extent that that women and men (or more specifically, male and female economics) have different views about economic theory and/or policy, and/or different interpretations of the research evidence.

I just finished reading a 2014 article by Ann Mari May, Mary McGarvey (both University of Nebraska - Lincoln), and Robert Whaples (Wake Forest University), published in the journal Contemporary Economic Policy (ungated version here). In the article, the authors report on a survey of 143 randomly selected members of the American Economic Association, the largest such association in the world. They essentially asked each survey participant about the extent to which they agreed with a number of statements, which were grouped into five categories:

The first group of questions relate to core principles in economics and economic methodology. The second through fourth groups examine views on market solutions and government intervention, government spending, taxing, and redistribution, and the environment. The fifth group of questions asks specifically about equal opportunity in society and gender equality in the economics profession.

Their findings demonstrate just how much diversity of opinion there is between male and female economists:

Male and female members of the AEA with doctoral degrees from U.S. institutions appear to agree on core precepts and economic methodology, whereas female economists tend to favor government-backed redistribution policies more than males, view gender inequality as a problem in the U.S. labor market and economics profession more than males, and favor government intervention over market solutions more than their male counterparts... The mean views of women economists on government spending, taxing, and redistribution and on gender inequality are both approximately one standard deviation away from the mean opinion of male economists. Although the divergence in magnitudes of the GLS and OLS estimated gender difference in opinion on U.S. environmental policies is not large, the GLS estimate is statistically significant. The mean response of female economists is about .45 standard deviations greater than the mean male response, indicating that women tend to favor an increase in U.S. environmental protection more than men...

The results of our survey of male and female economists show that the area of largest disagreement between men and women lies in views on equal opportunity. These differences reveal themselves not only in views of gender equality in the economics profession, but in society in general. Large disparities in average responses between male and female economists emerge in response to the statement, “Job opportunities for men and women in the United States are currently approximately equal.” The estimation results show the mean response of female economists is one point (a full standard deviation) lower than that of male economists after controlling for degree vintage and employment type. 

May et al. even tell you why their results are important:

First, these results suggest that it is crucial to include both women and men economists at the table when forming policy to ensure that a variety of professional perspectives are included in the discussion. If demographic differences, such as sex, shape our views of policy-related questions, it may be important that women be included on boards and in policy-making circles at all levels of decision making...

Second, the gender gap in economists’ views may provide a possible explanation why women are underrepresented in economics as faculty in the leading research institutions. If women hold views that shape their perspectives on research issues and inform their thinking on policy conclusions that are at odds with the perspectives of their male counterparts in areas that are at the heart of a discipline, this may affect hiring and promotion decisions in ways that disadvantage women...

Finally, differences in views on economic policy between similarly trained men and women may also influence classroom materials and discussion and ultimately the worldview of students in these classes.

There's a lot more detail in the paper, including some fascinating differences in response to the individual questions. I encourage you all to read it.

Compensating differentials, preferences, and the gender gap in wages

Consider two jobs. Job A involves working long hours at unsociable hours of the day, and in areas that are unpleasant or unsafe to visit. Job B involves shorter and more flexible working hours, and working in areas that are safer and more pleasant. Which job would have the higher pay, if all other characteristics and job requirements (other than those I mentioned above) were the same? If you answered Job A, then you're probably right. Job A would pay a higher wage, and the difference in wages between Job A and Job B is what economists refer to as a compensating differential. Essentially, the workers are compensated for the negative non-monetary characteristics of the job through a higher wage.

Now consider two groups of workers. For a given compensating differential (a given difference in the pay between Job A and Job B) Type X workers are more likely to choose Job B. In contrast, Type Y workers are more likely to choose Job A. Type Y workers would earn more than Type X workers on average, but more Type Y than Type X workers would also have to put up with the negative characteristics of Job A. Would you argue that the wages need to be modified in order to ensure that both groups of workers earned the same wage? Maybe you would, but remember that it is the compensating differential that makes Job A worthwhile, and reducing (or eliminating) the compensating differential will increase competition for Job B. So, maybe that's not such a good idea after all.

Now what if I said that Type Y workers were men, and Type X workers were women. Would that change your answer?

That thought experiment is important. The gender wage gap is real, but it isn't all a story about discrimination. Some of it is, no doubt, but some of the gender wage gap may be due to differences in preferences for job characteristics, and only one of those characteristics is the wage. How much of the gender wage gap is due to differences in preferences between men and women? It turns out that is quite a difficult question to answer, but a recent paper by Cody Cook (Uber), Rebecca Diamond (Stanford), Jonathon Hall (Uber), John List (University of Chicago) and Paul Oyer (Stanford) provides some interesting insights. They use data from Uber, and the great thing about their data is that there is no role for discrimination because, as they put it:

Uber set its driver fares and fees through a simple, publicly available formula, which is invariant between drivers. Further, similar to many parts of the larger gig economy, on Uber there is no negotiation of earnings, earnings are not directly tied to tenure or hours worked per week, and we can demonstrate that customer-side discrimination is not materially important. These job attributes explicitly rule out the possibility of a "job-flexibility penalty".

At the national level, they find a gender pay gap of around 7% when looking at hourly earnings of Uber drivers. However, in decomposing the gender wage gap, they focus on data from Chicago (although they note that their results are not sensitive to the choice of city, and in the appendix they present similar looking results for Boston, Detroit, and Houston). Their data on Chicago drivers includes 120,223 drivers (just over 30% female), and about 33 million driver-hours of observations. They find that:

We can explain the entire gap with three factors. First, through the logic of compensating differentials, hourly earnings on Uber vary predictably by location and time of week, and men tend to drive in more lucrative locations. The second factor is work experience. Even in the relatively simple production of a passenger’s ride, past experience is valuable for drivers. A driver with more than 2,500 lifetime trips completed earns 14% more per hour than a driver who has completed fewer than 100 trips in her time on the platform, in part because she learn where to drive, when to drive, and how to strategically cancel and accept trips. Male drivers accumulate more experience than women by driving more each week and being less likely to stop driving with Uber. Because of these returns to experience and because the typical male Uber driver has more experience than the typical female—putting them higher on the learning curve—men earn more money per hour.

The residual gender earnings gap that persists after controlling for these two factors can be explained by a single variable: average driving speed. Increasing speed increases expected driver earnings in almost all Uber settings. Drivers are paid according to the distance and time they travel on trip and, in the vast majority of cases, the loss of per-minute pay when driving quickly is outweighed by the value of completing a trip quickly to start the next trip sooner and accumulate more per-mile pay (across all trips). We show that men’s higher driving speed is due to preference as drivers appear insensitive to the incentive to drive faster. Men’s higher average speed and the productive value of speed for Uber and the drivers (and, presumably, the passengers) enlarges the pay gap in this labor market.

We interpret these determinants of the gender pay gap—a propensity to gain more experience, choice of different locations, and higher speed—as preference-based characteristics that are correlated with gender and make drivers more productive...

First, driving speed alone can explain nearly half of the gender pay gap. Second, over a third of the gap can be explained by returns to experience, a factor which is often almost impossible to evaluate in other contexts that lack high frequency data on pay, labor supply, and output. The remaining ~20% of the gender pay gap can be explained by choices over where to drive. 

In other words, in a setting where discrimination is unlikely or impossible, the gender wage gap is entirely explained by differences between men and women in experience (about one third) and preferences (about two-thirds). Preferences turn out to be a really important component of the gender wage gap. It does leave open the question of how much of the gender wage gap in other occupations (where discrimination is possible) is due to discrimination, but we can be sure that it isn't anywhere near all of the gap. The results in terms of work experience are not gender neutral though, as men will build their job experience faster if they work more hours (and they do).

The gender wage gap is real, but we need to be careful before we pronounce it as definitive evidence of sexism (such as here).

[HT: Marginal Revolution, and then Offsetting Behaviour]

Menu pricing in restaurants is about to become more complex

Price discrimination occurs when firms charge different prices to different customers for the same product or service. Savvy firms will charge higher prices to customers with more inelastic demand (i.e. those who are less likely to be dissuaded by higher prices), and lower prices to customers with more elastic demand. This allows firms to extract more profits from customers who are willing to pay more.

Menu pricing (also known as second-degree price discrimination) occurs when firms offer customers a menu of different options. Importantly, the firm knows that some of the menu items will appeal to customers who have relatively inelastic demand (and for those items, the firm will charge a higher mark-up over cost) and other menu items will appeal to customers who have relatively elastic demand (where the firm will charge a lower mark-up). Menu pricing is called menu pricing because it is the type of price discrimination typically employed by restaurants. Think of a restaurant wine list - would it surprise you to learn that the mark-up on a cheap bottle of wine is smaller (in percentage terms, not just in dollar terms) than the mark-up on an expensive bottle of champagne?

However, there are other forms of price discrimination as well. Airlines practice price discrimination by charging different prices for flights at different times of the day, or different days of the week. Certain time and day combinations (e.g. early mornings, and late afternoons, on weekdays) appeal more to business travellers, who have more inelastic demand (they have more inelastic demand because they really have to get to that meeting on time, and must go to a particular city on that day and at that time). Airlines charge higher prices for those flights than for flights at other times or on weekends, since those other flights will appeal to leisure travellers (who have more elastic demand, because they have more alternative options open to them).

However, demand for restaurant tables differs by time and day as well. Why don't restaurants price discriminate, by offering different prices by time and day? Of course, many do in a limited way, by offering lunch or brunch menus that differ from their dinner offering (and notice, the prices are cheaper in the lunch menu, even for the same items). Now, it turns out that restaurants might be expanding the practice, as Bloomberg reported back in January:

One of London’s leading restaurants will today start pioneering a new pricing model based on the travel industry, with different charges depending on the day of the week and time of your booking.

Bob Bob Ricard, known for a luxurious dining room where each table has a call-button for Champagne, will offer exactly the same menu, only prices are 25 percent lower for off-peak times such as Monday lunch and 15 percent off mid-peak, including dinner on Tuesdays and Sundays. Book for Saturday night and it’s full price.

“The idea just came from looking at how the rest of the world functions,” said owner and founder Leonid Shutov...

“It’s what we learn in economics 101, it calls for price differentiation. I do realize it’s a bit of a brave decision because any departure from the standard model involves risk. But I am not really worried. We are not changing the menu. We are not trying to entice customers with anything from what they know and love. We are just saying that on certain days it will cost less.”

The idea is good, Leonid, but it's called price discrimination, not price differentiation.

[HT: Marginal Revolution]

Bitcoin mania is passing just like the flu season

I've generally avoided blogging about Bitcoin or other cryptocurrencies (with one exception). To be honest, I've been waiting for the whole Ponzi house of cards to collapse. However, notwithstanding my bearish views on Bitcoin, I have been following the development of cryptocurrencies as they make their way through the hype cycle, so I couldn't help but notice this article by Frank Chung on news.com.au last week:

Bitcoin's wild price rise and subsequent crash has been likened to the spread of an infectious disease which peters out as more people become “immune”, just like flu season.

Analysts at investment bank Barclays developed a pricing model for the cryptocurrency based on epidemiology — the study of the spread of disease through populations — which divides the pool of potential investors into three groups, “susceptible”, “infected” and “immune”.

“Like infection, transmission — especially to those with ‘fear of missing out’ — is by word-of-mouth, via blogs, news reports and personal anecdotes,” Barclays analyst Joseph Abate said in a client note on Tuesday, Bloomberg reported.

“However, once full adoption is approached, the price decline is sustained and rapid.

“As more of the population become asset holders, the share of the population available to become new buyers — the potential ‘host’ population — falls, while the share of the population that are potential sellers (‘recoveries’) increases.

“Eventually, this leads to a plateauing of prices, and progressively, as random shocks to the larger supply population push up the ratio of sellers to buyers, prices begin to fall. That induces speculative selling pressure as price declines are projected forward exponentially.

“This occurs with infectious diseases when the immunity threshold is reached, [that is], the point at which a sufficient portion of the population becomes immune such that there are no more secondary infections.”

I hadn't thought about the rise of Bitcoin as being like the short epidemic of SARS or bird flu, but having seen it in print, it does make a lot of sense. Of course, being infected by Bitcoin hasn't proved fatal for investors. Yet.

This couldn't backfire, could it?... Rescue dog breeding edition

The Washington Post reports:

An effort that animal rescuers began more than a decade ago to buy dogs for $5 or $10 apiece from commercial breeders has become a nationwide shadow market that today sees some rescuers, fueled by Internet fundraising, paying breeders $5,000 or more for a single dog.

The result is a river of rescue donations flowing from avowed dog saviors to the breeders, two groups that have long disparaged each other...

Bidders affiliated with 86 rescue and advocacy groups and shelters throughout the United States and Canada have spent $2.68 million buying 5,761 dogs and puppies from breeders since 2009 at the nation’s two government-regulated dog auctions, both in Missouri, according to invoices, checks and other documents The Washington Post obtained from an industry insider.

What happens when well-meaning dog rescuers start to buy dogs direct from breeders, in order to rescue them and reduce the number of these dogs in the market? A simple demand-and-supply analysis has the answer, as shown in the diagram below. More buyers in the market leads to an increase in the demand for 'rescue dogs' (from D0 to D1), and increasing the price of these dogs (from P0 to P1). However, the real unintended consequence of the dog rescuers is that their actions actually increase the number of dogs traded (from Q0 to Q1). Dog breeders respond to incentives, and because the price has increased, they breed more dogs.

This is very similar to one of my favourite examples from earlier editions of my ECONS102 textbook, The Economics of Public Issues, on slave redemption in the Sudan (which I have posted on before). In this case (as in the case of slave redemption), the do-gooders seem completely oblivious to the unintended consequences of their actions:

Rescuers at the auctions say their purchases save individual dogs and weaken the commercial breeding chain by removing, spaying and neutering dogs that would otherwise be bred again and again. They say donors ranging from average dog lovers to show-dog breeders understand, and financially support, their efforts.

The financial support of average dog lovers and show-dog breeders is part of the problem, not part of the solution! (Because it financially fuels the demand for these dogs). And the result is clear:

The majority of the $2.68 million The Post documented was spent since 2013 at Southwest Auction Service, the biggest commercial dog auction in the country, with some additional spending at its smaller, only remaining competitor, Heartland Sales...

“I’m not going to lie about this: Rescue generates about one-third, maybe even 40 percent of our income,” says Bob Hughes, Southwest’s owner. “It’s been big for 10 years.”...

Hank Grosenbacher, owner of Heartland, says rescuers usually account for 15 to 25 percent of his business.

A little economic literacy would go a long way.

[HT: Marginal Revolution]

Read more:

• The economics of slave redemption

Book Review: The Butterfly Defect

I just finished reading "The Butterfly Defect: How Globalization Creates Systemic Risks, and What to Do About It" by Ian Goldin and Mike Mariathasan. This felt like an appropriate follow-up to reading Dani Rodrik's The Globalization Paradox (which I reviewed here). This was a very thought-provoking and well-researched book, but perhaps a little more academic than it needed to be. The authors note that it is the fourth in a series on globalisation that Ian Goldin has been writing, and it is very self-referential of the other three books.

The key theme of the book is that globalisation increases systemic risk - the type of risk that occurs when systems are highly inter-connected and which results from the complexity of those systems. A good summary of their narrative comes at the start of the concluding chapter:

The complexity of the world that we have built may well have escaped our models and cognitive abilities. We are overloading the global networks; we are stretching their capacity beyond what prudence recommends, and - as we have shown - too often we neglect the accumulation of a large variety of risks and the geographical concentration of activities in a small number of pivotal nodes.

Goldin and Mariathasan illustrate their theme with examples from the financial sector, global supply chains, infrastructure, the environment, global health, and inequality. Only the last of these seemed to me to be a little forced, and there was a certain overlap between their views and Rodrik's, especially in terms of the financial sector.

My main takeaway from the book was the increased vulnerability of global systems to risk, with this vulnerability arising because of a lack of diversification. One of the principles of finance is diversification in order to deal with risk, and most (if not all) of the examples in the book illustrate how as societies we have reduced our diversification, relying on monocultures of certain plants and concentrated land use, lean management practices, supply chains that rely heavily on individual suppliers, financial institutions that have become 'too big to fail', and so on. We have ignored the necessity to plan for low-probability events. As Goldin and Mariathasan write:

The general problem seems to be that our current institutions fail to be prepared for the fact that "low risk is not no risk".

This is a real problem, as we have seen time and again in recent years. However, while Goldin and Mariathasan despair about the short-term decision-making of managers and policy makers, they ignore the role of customers, shareholders, and taxpayers in shaping that decision-making. It is difficult for managers to build additional redundancy into their global supply chains, when that redundancy comes at additional cost and would either impose higher costs on customers (at which point, other firms that avoid those costs would be at an advantage) or lower returns for shareholders (who should be focused on long-term returns, but in the real world are not). Similarly, it is difficult for policy makers to advocate for increasing spending on infrastructure repair when that would require higher taxes (and we've been seeing the result of that in New Zealand this week). These are challenges that no amount of lessons from the past will help us deal with - we, as customers, shareholders, and voters, need to be willing to accept higher prices, lower dividends, and higher taxes, if we really want to mitigate these systemic risks and develop a "resilient globalisation".

Overall, it is a good book. It doesn't contain much that will be new to readers who have been awake to the consequences of globalisation, but the academic links are important and the overall theme is too.

'Pay-what-you-want pricing' is not price discrimination

Back in March, Adrian Camilleri (University of Technology Sydney) wrote an article in the Conversation about 'pay what you want pricing'. Essentially, this is where a firm allows the customer to pay whatever price they want to for the good or service - anything from zero upwards. In economics, we more often call this type of pricing a 'voluntary purchase scheme'. However, one point in particular caught my attention:

There are a few reasons why pay as you want could be profitable.

Pay as you want allows for price discrimination. Normally this means companies try to extract the most a customer would be willing to pay by offering different services, such as extra legroom on planes, for example.

Think about how much you would pay for a smashed avocado breakfast. For some people, the answer is A$10. For others it is A$20. A restaurant that prices its smashed avo at A$15 may be losing some customers (those willing to pay only A$10) and also fail to capture the full value from other customers (those who would have been willing to pay A$20).

By allowing people to pay as they want the restaurant can successfully cater to both types of customers.

Price discrimination occurs when a firm sells the same product to different customers for different prices, and when those different prices do not relate to differences in cost. Is a voluntary purchase scheme (or 'pay-what-you-want pricing', if you prefer) an example of price discrimination? On the surface, it would seem so - certainly different customers are paying different prices for the good or service. However, I would argue that voluntary purchase schemes are not price discrimination, for two reasons.

First, with price discrimination, firms must have market power. That is, firms must have the power to set their own price. If you let the customer set the price, then as a firm you've given away your market power. It is the customer who has the market power in a voluntary purchase scheme (which explains why many customers will choose to pay zero).

Second, with price discrimination the firm is looking to extract additional profits by charging a higher price to consumers who have a higher willingness-to-pay for the good or service (or who have more inelastic demand for the good or service). In order to do this, you need some way of sorting customers into those with high willingness-to-pay and those with lower willingness-to-pay. Movie theatres do this by sorting the students and seniors out from the other adults. Airlines do this by sorting those who buy a ticket shortly before a flight from those who purchase well in advance. Online sellers might be able to sort based on the data they have collected about you. And so on.

However, with voluntary purchase schemes the price that the customer actually pays need not depend on their actual willingness-to-pay. It is based more on their 'willingness-to-share' with the seller. It is based on their altruism, or how pro-social the customer is, or social norms, or moral incentives, or some combination of all these things. So, there is no certainty that a customer with a high willingness-to-pay will pay a high price, while a customer with a lower willingness-to-pay will pay a lower price. And so, 'pay-what-you-want pricing' isn't price discrimination.

Despite this, Camilleri's article is worth reading, because the voluntary purchase schemes is a fad that has been coming in and out of fashion on a fairly rapid cycle over the last decade or more. Although, that may just be because the sellers who think it is a good idea run with it for just long enough to run out of money and go out of business, and then there is a little break before the next idealists try it out.

Make sure you get your cocaine loyalty card stamped

In ECONS101, we cover many different pricing strategies. One of my favourites to discuss is customer lock-in and the associated multi-period pricing. This is because I get to use the example of drug dealers, who have been known to give away their highest quality product for free.

To see why, we need to take a step back. In order to lock customers into buying from them (enigmatically called 'customer lock-in'), there needs to be a switching cost - a cost of switching to some other seller. Switching costs might include contract termination fees, for example, but in the case of drug dealers it might be as simple as it being difficult for the buyer to find some other seller (drug dealers can't exactly advertise themselves in the yellow pages, after all). Drug dealing syndicates might reinforce these switching costs by using violence to ensure that rival sellers stay out of their turf, meaning that addicted customers really have no other option but to come to the syndicate to get their fix.

Why give away product for free then? Having established switching costs, you need to find some way to get customers to start buying your product (and then, having started buying from you, the customers find it difficult to switch to some other seller or to stop buying). Some firms give away free samples - this is also why cellular networks are so keen to give you a free or heavily discounted phone. In the case of drug dealers, they give away their product for free. The reason they give away the highest quality product is because it is also the most addictive. There's nothing like having an addicted customer, locked into buying from you because it is too costly for them to switch, if you want to increase your profits.

And one way you increase your profits is using multi-period pricing. Initially you give away the product for free, and then once your customers are locked into buying from you, you can raise the price and reap the profits. In the case of drugs, you can also lower the quality by cutting them with something worthless (after all, if the customers are locked in, they aren't going anywhere else for their fix).

Which brings me to this story from The Telegraph (paywalled, or try this version from the New Zealand Herald):

With its smiling face logo and tempting offer to buy five and get the sixth free, this loyalty card at first appears as innocuous as those offered by any High Street coffee shop or supermarket.

But, it is being handed out to wealthy cocaine users to boost sales and loyalty and reveals just how fierce competition between drug dealers fighting turfs wars for ‘market dominance’ has become...

The card 'scheme' offers stamps for bulk purchases giving the sixth and then 12th wrap of cocaine free, said the source who handed it to the Daily Telegraph.

A wrap of cocaine generally costs between £50 and £80, depending on the quality, the source said, adding that it is understood a network of couriers deliver the drug.

The loyalty card reads: "One freebie for every five stamps you collect!! Love Loyal-T". The smiley face design on the front is evocative of the 1980's acid dance scene.

Given how easy it is to profit from locked-in customers as per my description above, why would cocaine dealers offer a loyalty card? You only profit if your customers are locked into buying from you. If there are many competitors selling the same (or a very similar) product, then you haven't really locked those customers in. This is why drug syndicates try to keep competitors out of their turf.

But say that, for whatever reason, you couldn't keep competitors out of your market. Maybe your competitors are sending drugs into your town from outside and it is difficult to intercept their couriers. Or perhaps your customers have realised that they can get their fix by travelling to the next town, or by navigating to the right site on the dark web. How do you lock those customers in to buying from you? One answer is to offer a loyalty card.

How do loyalty cards generate customer lock-in? Remember, there needs to be a switching cost. In the case of loyalty cards (whether we are talking about coffee cards, cocaine loyalty cards, or even airline miles or Flybuys points), there is a cost of going to an alternative seller - you miss out on a stamp on your loyalty card (which would have taken you one step closer to a free fix). In the case of loyalty cards, the switching cost is small, so the lock-in is fairly weak. But overall, it explains why cocaine dealers would be willing to offer a loyalty card to their customers.

Don't fear minimum wage increases because of their effects on the cost of living

Mike Hosking wrote in the New Zealand Herald this morning, about the increasing minimum wage:

Costs are market-driven, market and demand. The prices for something are based, or should be, on what the market can bear.

The Government coming in over the top of that equation and arbitrarily handing out instruction disrupts the markets. It brings an artificiality into it that the market might not be able to bear, and if it can't, the only loser is the person out of work. Or worse, the owner out of business.

Further, the more cost you put into the market, the more inflationary it is. The higher the tax on petrol, the more literally everything costs because everything has a transport component to it...

So are you prepared to pay for more for your coffee? Can you afford for your cost of living to rise?...

Life is about to get more expensive, the Government is arguing this is a good thing. Let's see shall we.

It is true that wages are a cost to business and that, when costs rise, businesses tend to increase their prices. Indeed, that's what has been in the news this week and what prompted Hosking's column. However, how much will prices rise as a result of an increase in the minimum wage? It turns out, not much. As I wrote earlier this year, a research paper by Tobias Renkin (University of Zurich) and co-authors found that:

...a 1 percent increase in the minimum wage would increase grocery prices by around 0.02%.

That is, increases in the minimum wage are passed onto consumers. However, the actual impact on consumer prices is only small. Granted, the Renkin et al. research was on grocery stores, and minimum wages will be a greater proportion of costs for cafes, etc., but because consumers don't spend a high proportion of their income at cafes the impact on the overall cost of living of a change in the minimum wage will still be small overall.

That doesn't mean that the news for minimum wage increases is all rosy though. The latest evidence does still say that minimum wage increases decrease employment, which is a point that Hosking makes in his column as well.

Read more:

• Increases in the minimum wage are effectively paid by consumers, but they lower inequality anyway
• Raising the minimum wage to $20
• The latest evidence supports negative employment effects of the minimum wage
• Latest research suggests the minimum wage DOES reduce employment

Flipped classrooms are still best only for the top students

Back in 2016, I wrote a couple of posts about blended learning, specifically related to the evidence on blended or online learning, and flipped classroom models (see here and here). My takeaway from this literature has been, and continues to be, that it works very well for highly-engaged high-achieving students, but it is rubbish for less-engaged low-achieving students. So, I was interested to see this new paper by Nathan Wozny (USAF Academy), Cary Balser (Notre Dame), and Drew Ives (USAF Academy), published in the Journal of Economic Education (sorry, I don't see an ungated version online).

This article is interesting because it applies a randomised-controlled trial (RCT) approach. If implemented well, RCTs are the gold standard for evaluating the impacts of interventions because the randomisation should lead the treatment and control groups to be similar on the whole range of observed and unobserved characteristics that might affect the impact of the intervention. That means that if you observe a difference between the two groups after the intervention, it is highly likely to be due to the intervention and not due to a difference between the two groups. There's a bit more to it than that, but in short that's why RCTs are usually the best approach.

Anyway, Wozny et al. randomized their third-year econometrics class at the USAF Academy (137 students) into sections that would receive a mix of traditional lectures and flipped classroom lessons, where each section would receive a different mix of lessons that were traditional and flipped. Each section received five flipped classroom lessons, and five traditional, within the ten experimental lessons. They explain:

For each flipped lesson, the instructor reviewed comprehension questions, using student responses as a basis for discussion. Next, the instructor facilitated independent or small group work on exercises and provided mini-lectures as appropriate for topic and student needs. Students did not have any assignment in advance of each lesson selected as a traditional lecture but listened to the instructor lecture, during class, on the same material covered in the video for the flipped lesson. Students in lecture lessons had access to the same exercises offered in the flipped classes, but the lecture group generally did not have available class time to complete the exercises. The key difference in the two conditions is therefore timing rather than the primary learning resources provided: both groups received a lecture (before class for the flipped group and during class for the lecture group) and exercises (during class for the flipped group and after class for the lecture group).

They then evaluated the impact on student learning at three points in time:

Six classes ended with an online, unannounced, ungraded formative assessment testing comprehension of content covered in approximately the three lessons preceding the assessment. Four announced, written graded exams administered throughout the semester measured medium-term comprehension on content covered in approximately the eight lessons preceding the exam... A comprehensive written final exam administered at the end of the semester measured long-term comprehension.

Their key results are nicely summarised in Figure 1:

There is only a statistically significant difference for the medium-term (the four, written graded exams held throughout the semester), and not for the online assessments or, tellingly, for the final exam. Wozny et al. then looked at sub-groups, specifically separating their sample into students above and below the median GPA. Now, using the sub-group analysis, they find a statistically significant and positive effect of flipped classrooms for the above-median-GPA students, and a statistically insignificant effect on below-median-GPA students. They then conclude from this that:

Impacts are slightly larger and also persist to long-term assessments for high-performing students, but the relatively similar effects for above-median and below-median students support the generalizability of the results to a wide spectrum of students.

I disagree. The effect for below-median students may be statistically insignificant, but the point estimate is negative and relatively large. Here's the key table (you may need to enlarge it to see clearly):

The size of the negative effect on below-median-GPA students is a bit more than half of the positive effect on above-median-GPA students (and the overall effect for both groups combined is statistically insignificant, as shown in the figure above). The problem may be that their sample size is not large enough to create enough statistical power to identify the negative effect on below-median-GPA students, rather than that the effect is zero.

As far as I'm concerned, this study is not enough to convince me. As I concluded in 2016:

I'm still waiting for the research that will convince me that the flipped classroom model will have positive outcomes for the marginal (or even the median) student that I teach.

Read more:

• Flipped classrooms work well for top students in economics
• Online vs. blended vs. traditional classes

It's not a tax, it's an excise

I was laughing so hard this morning on my drive into work that I almost had to pull over. On Morning Report, Guyon Espiner was interviewing our PM Jacinda Ardern, about the government's policy statement on transport, which includes an increase in the fuel excise tax. You can listen for yourself here. Ardern seemed very focused on not referring to the petrol excise tax as a tax. She didn't quite take Espiner's bait to say, "It's not a tax, it's an excise", but she was really close. I don't think she referred to it as a tax at all in the interview, constantly referring instead to excise.

Of course, Ardern was being careful because the Taxpayer Union has been out in force noting that, according to the New Zealand Herald:

...the government's proposal to increase fuel levies breaks Jacinda Ardern's promise of "no new taxes".

So of course the PM wasn't going to refer to this as a tax. What's the difference? There is no difference. An excise tax is a tax on the sale or production of some good or service. So, when you refer to something as an excise, you are telling us it is a tax. This is pretty clear regardless of the definition of excise. Here's the OED definition:

Excise, n.

1. gen. Any toll or tax.

Or, perhaps you prefer the Merriam-Webster dictionary:

1 : an internal tax levied on the manufacture, sale, or consumption of a commodity

2 : any of various taxes on privileges often assessed in the form of a license or fee

Wikipedia might offer Jacinda some comfort:

An excise or excise tax is any duty on manufactured goods which is levied at the moment of manufacture, rather than at sale.

So, it's not a tax, it's a duty? That comfort lasts only until you look up what a duty is:

In economics, a duty is a kind of tax levied by a state.

It's pretty clear then. A tax by any other name is just as taxing (my apologies to Shakespeare). To be fair though, this isn't the first (and it won't be the last) government to try their hardest not to refer to taxes as taxes. Only a few years ago, the previous government introduced a new "bio-security and customs levy" (see my post on that here). It goes without saying that a levy is also a tax.

Book Review: The Globalization Paradox

I just finished reading The Globalization Paradox, by Dani Rodrik. The subtitle is 'Democracy and the future of the world economy'. Rodrik is one of the foremost thinkers in international economics, and on that front, the book doesn't disappoint.

The ideas that Rodrik puts forward in the book can be summarised in two points. First, markets and governments are complements, not substitutes. If you want markets to work best, you need more (and better) governance, not an absence of governance. In other words, laissez faire actually works against global welfare. Second, there is no one unique model of successful capitalism, so there is no one formula that will work for all countries. Each country needs to make its own decisions about the rules and institutional arrangements that will work best for their needs and preferences. There is a lot of good to be said for both of those points.

Rodrik is definitely a globalisation-sceptic, but he has a lot of love for China's approach to globalisation. That is, keeping the international economy at arms' length just long enough so that the economy can gain strength:

China's experience offers compelling evidence that globalization can be a great boon for poor nations... China's ability to shield itself from the global economy proved critical to its efforts to build a modern industrial base, which would be leveraged in turn through world markets.

Rodrik spends quite a bit of the book arguing for a more reasoned approach to globalisation. In particular, he presents a trilemma: societies can only be two out of three of: (1) globally integrated; (2) completely sovereign; and (3) democratic. He doesn't nearly devote enough space to this trilemma for my liking, but enough to make the case that full global integration should be the option to be foregone. Rodrik's preferred solution is a new Bretton-Woods compromise - that we should opt for a 'thin' globalisation, if we want to retain nation states (since global government is infeasible) and democratic governance. The examples of financial globalisation that Rodrik uses throughout the book certainly present a strong case that unfettered globalisation has gone too far. However, there are some aspects of integration - communications and information technology, and labour migration in particular, that Rodrik barely touches on.

Despite those omissions, this is an important book to read if you want to see a reasonable argument against 'hyperglobalisation'. There are many great soundbites as well, such as:

...The scope of workable global regulation limits the scope of desirable globalization...

...Trade is a means to an end, not an end in itself. Advocates of globalization lecture the rest of the world incessantly about how countries must change their policies and institutions in order to expand their international trade and become more attractive to foreign investors. This way of thinking confuses means for ends. Globalization should be an instrument for achieving the goals that societies seek: prosperity, stability, freedom, and quality of life...

...But what generates higher incomes, better jobs, and economic progress is not more trade as such... What makes us better off is the ability to consume those goods at lower cost and sell our produces at better prices abroad...

Especially, given this book was published back in 2011, this seems quite prescient:

If China's trade surplus does not shrink, the United States likely will resort to trade barriers directed at Chinese exports, inviting retaliation from China and similar tactics from other countries.

Rodrik's key contribution in the book is seven principles for a 'new globalisation'. Unfortunately, it appears that these principles are being overlooked as the drive for greater global integration (the current US trade tantrums notwithstanding) continues apace. Overall, this book is not an easy read, but it continues to be an important one.

Why study economics? Better than operations research and computer science edition...

I've written a number of posts on why students should study economics (see the end of this post for the thread). In several of those posts, I've highlighted the job opportunities in the tech sector, and a few people have asked me why tech companies would be interested in economists to do jobs that computer science graduates might be more suited to. My answer is that economists bring unique skills to the types of questions that firms, including tech firms, want to answer. However, don't just take my word for it. Greg Lewis (senior researcher at Microsoft Research in New England) provides a similar answer in this interview transcript on the MIT Initiative on the Digital Economy site:

Andrey  F.: That's really interesting, because those are quite diverse activities and they are not typically things that economists actually study in their PhD. What is the advantage of an economist looking at this type of problem, as opposed to let's say in the case of logistics for Amazon? You would think that there is a person in operations research or in the case of search engine design, you'd think that there is a computer scientist focusing on machine learning, that would be the appropriate person. What is the economists' perspective on this?

Greg L.: Yes. I think what economists bring to the table is really a good idea of how we think about economic remodeling. If you think about the case of logistics, Amazon does have many highly talented operations research professionals working in these kinds of questions. The way Pat described this to me is you have to know what to optimize. In order to know what to optimize, you have to know what the economic trade-offs are that Amazon is making by, say, delivering things in one day relative two days.

Economists would sit there and think, "One day delivery attracts customers a little bit better. People like one day delivery. In the long run, this may make a big difference to Amazon's growth trajectory, versus the standalone retail store that we're used to every day." Economist are very good at thinking of those trade-offs and then working out how one might think about quantifying things.

The key difference that Lewis is highlighting is the way that economists approach research questions, and the way they go about answering them. Later in that same interview, there is a good bit about how machine learning won't replace economic modelling, which should be required knowledge for computer scientists. Well worth a read (albeit a long one).

Read more:

• Why study economics? Economics and computer science edition...
• Why study economics? Understand the world edition...
• Why study economics? More tech sector jobs edition...
• Why study economics? Law and economics edition...
• Why study economics? More on jobs in the tech sector edition...
• Why study economics? Tech firm jobs edition...
• Why study economics? AEA video edition...
• Why study economics? Even if you won't be an economist edition...
• Why study economics? PhD edition...
• Why study economics? It could make you rich...
• Why study economics? Sheepskin effects edition
• Why study economics? NZ graduate earnings edition
• Why study economics?