Friday, 20 April 2018

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.

Wednesday, 18 April 2018

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]

Tuesday, 17 April 2018

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]

Monday, 16 April 2018

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.