Tuesday, 22 October 2013

Market competition and firm costs in the taxi industry

I've been in Wellington the last couple of days, presenting at the Pathways, Circuits and Crossroads Conference (more on that later). Anyway, I had a quite interesting conversation with my taxi driver on the way into the city from the airport, which I thought I should share.

This semester, my ECON110 students showed some scepticism over the mechanism/s through which costs increase when a market becomes more competitive. The standard explanation relates to economies of scale (smaller firms have higher average costs because the fixed costs such as administration, etc. are spread over a smaller quantity of output). However, my conversation with the taxi driver raised another potential explanation.

Some four or five years ago, the taxi industry in Wellington was deregulated. Prior to that, my driver says, special licenses were required in order to operate a taxi (possibly similar to taxi medallions in New York, but without the resale market). After deregulation, the number of taxi operators exploded - he wasn't sure of the exact numbers, but they may have doubled or more. The result was a large increase in competition in the market.

How does that increase in competition raise costs for taxi drivers? Of course, it doesn't materially affect direct out-of-pocket costs like fuel, taxi maintenance, etc. However, it does affect the cost-per-fare, through time (opportunity) costs. The explanation goes like this. Before de-regulation, there were fewer taxis. When a driver arrived at the airport with a fare, he could expect to wait a relatively short time before picking up a new fare, so faced only a small time cost for each fare. With a large increase in the number of taxis competing for fares, taxi drivers now wait much longer at the airport before collecting a new fare (my driver said that he had waited over 90 minutes before picking me up. This isn't unusual, or specific to the airport - he said there were often similar waiting times at the city taxi stands). This increases the opportunity costs for each taxi driver, since they could be doing something else with that time (like this, perhaps?), raising the costs per fare.

Anyway, that provides another alternative explanation for why costs might rise as competition increases - competitive firms must work much harder to attract customers, and working hard is costly.
Coming back to the Pathways conference: If anyone is interested, a video of my presentation on Subnational Stochastic Population Projections in New Zealand will soon be available on the Nga Tangata Oho Mairangi research project website. From the feedback I have received, my presentation was most memorable for my opening statement that "All population projections are wrong" (paraphrasing a quote from the British mathematician George E.P. Box). For more context on the wrongness of Auckland population projections recently, see here for example.

Thursday, 17 October 2013

Newsflash! Schools with more problem bullying are more likely to implement anti-bullying programs

OK, so that headline isn't really an attention grabber. At least, not as much as "Youth more likely to be bullied at schools with anti-bullying programs".

So, let's say are interested in whether anti-bullying programs are effective or not. You find yourself a dataset that includes individual-level data on students (including data on whether they have ever been physically or emotionally bullied at school), and school-level data on security climate (like, whether they have uniformed police, metal detectors, random bag/locker checks, etc.) and whether the school runs an anti-bullying program. Importantly, the dataset is collected at a single point in time (a cross-sectional dataset). You run a regression analysis (using whatever fancy analysis method is your flavour of the month - in this case because the data are at two levels (individual-level and school-level) and the dependent variable is binary (bullied - yes or no) you run a multi-level logit model). You find that students' experience of bullying is positively associated with anti-bullying programs. In other words, students at schools that have anti-bullying programs are more likely to have experienced bullying.

You could reasonably conclude that anti-bullying programs somehow create more problem bullying, right? Wrong. What you've done is confused causation with correlation, as the study cited in the article above (recently published in the open-access Journal of Criminology) has done (Quote: "Surprisingly, bullying prevention had a negative effect on peer victimization" - by negative, they mean undesirable).

A positive association between anti-bullying programs and bullying could be because "students who are victimizing their peers have learned the language from these anti-bullying campaigns and programs" (quote from the UTA news release). Alternatively, and possibly more likely, it could be because schools that have more problem bullying are more likely to implement anti-bullying programs in the first place. In the latter case, the observed positive association between anti-bullying programs and problem bullying is in spite of the anti-bullying program, not because of it. A third possibility (and equally plausible) is that students who are at a school that has anti-bullying programs are more aware of what bullying is, are less afraid and more secure in themselves, and consequently are more likely to report bullying.

So, while technically correct, the headline is a little misleading. Youth are more likely to be bullied at schools with anti-bullying programs, but not necessarily as a result of those programs. To be fair, the authors note in the limitations to their study that "the cross-sectional nature of the study limits one from making a causal inference about the relationship between individual and school-level facros and likelihood of peer victimization". However, their loose language in the conclusions and in the media release do just that.

The main problem here is that we have no idea of how much worse (or indeed, how much better) bullying would have been if those programs had not been in place. In order to tease that out, you would ideally need to have longitudinal data (data for schools both before, and after, their anti-bullying programs were implemented, and comparable data for schools that never implemented a program). Then you could see whether the anti-bullying programs have an effect or not (you would have a quasi-experimental design, and there are problems with this but I won't go into them here).

You could possibly argue that, because the results show a positive association, that the anti-bully programs are not effective (because they don't eliminate problem bullying in schools that have them). That's the angle taken by Time magazine columnist Christopher Ferguson ("Anti-Bullying Programs Could Be a Waste of Time"). Again the headline is technically correct but partly misses the point.

Why might schools with effective anti-bullying programs still show great levels of bullying than schools without such programs? This could be because, even though the program is effective in reducing bullying, it doesn't eliminate bullying entirely (relative to schools with no such program in place). In that case, schools with anti-bullying programs could still have higher-than-expected levels of bullying, even though their programs are effective.

So, because the study was poorly designed to determine the effectiveness of anti-bullying programs - it essentially tells us nothing about how effective (or ineffective) they are. I am much more happy to believe meta-analysis of results from many experimental and quasi-experimental studies, such as that by Ferguson and others reported here. They found that anti-bullying programs show a small significant effect. However, they also noted it is likely that their estimated effect was largely due to publication bias, and as a result they concluded that these programs "produce little discernible effect on youth participants". So, the question of whether these programs are effective or not remains somewhat open.

I guess the overall point here is that as researchers, we need to be careful about interpreting and not over-stating our results, and where possible we also need to be careful about how the media interpret our results. It is far too easy for the general public to misinterpret our results if they are not clearly stated.

Tuesday, 15 October 2013

An un-recognised additional cost of higher education

In my ECON110 Economics and Society class, one of the topics we cover is the economics of education. Specifically, part of the topic looks at the private education decision - under human capital theory, we would choose another year of education (or to study a course, certificate, degree, etc.) provided the incremental benefits outweigh the incremental costs. The incremental benefits include higher lifetime earnings, which may arise from productivity gains, but also from signalling to employers that you are a better hire, as well as social capital gains from interacting with a cohort of like-minded students who will each go onto future careers. The incremental costs include direct costs such as tuition, textbooks, accommodation (provided it costs more than accommodation would if not studying), and so on. The incremental costs also include opportunity costs, such as foregone income while studying, foregone leisure time, and so on.

The Becker-Posner blog this week discussed the increasing costs of education (see here for Becker's post, and here for Posner's). These increasing costs are happening in New Zealand, not just the U.S. However, Becker and Posner also note that the returns to higher education are also increasing (though, New Zealand doesn't do so well on this front compared with the rest of the OECD). So, in spite of the increasing tuition costs, the cost-benefit calculation will still often come out in favour of university study for most students.

However, there may be other costs of higher education that are less well recognised. A paper published in the journal Kyklos last year (gated) by Helmut Rainer (University of Munich) and Ian Smith (University of St Andrews) raising the prospoect of an additional (and unrecognised) cost of higher education - lower sexual satisfaction. Rainer and Smith showed that education had two effects on sexual satisfaction. On the one hand, education improves communication between partners, which makes them more likely to coordinate their sexual preferences and leads to higher sexual satisfaction. On the other hand, education increases earnings and therefore increases the opportunity costs of leisure activities (including sex). Their empirical findings based on German data show that the opportunity cost effects dominate, leading higher education to be associated with lower sexual satisfaction overall.

The Rainer and Smith papers sits alongside an earlier paper in Economic Inquiry by Hugo Mialon of Emory University (ungated version here), on the economics of faking orgasm. Mialon found that both men and women with higher education were more likely to fake orgasms. His argument was along similar lines - higher earnings for more educated people led to higher opportunity costs of time, making them "more likely to fake just to get it over with".

So, when considering the private decision on education based on human capital grounds, there is an additional cost to consider!

Tuesday, 8 October 2013

Why Sex, Drugs and Economics?

Welcome to my new blog, "Sex, Drugs and Economics". You might rightfully ask, why call your blog "Sex, Drugs and Economics"? Well, some time ago I was asked to describe my research interests in a single (short) sentence. I have always had a pretty wide portfolio of research interests (if you are interested, my Google Scholar profile is here), but at the time my main research interests were in the economics of HIV/AIDS (my PhD thesis was on the relationships between poverty and HIV/AIDS in the Northeast of Thailand), and I was embarking on a new project on the spatial economics and impacts of liquor outlet density (research which has since generated a significant amount of publicity as liquor licensing laws have been reviewed and subsequently changed in New Zealand). Thus: sex, drugs and economics.

Why blog at all?
Until a few years ago, my first year elective economics paper (ECON110 Economics and Society - still my favourite paper to teach) students had to complete a blog as part of their assessment for the paper. Students found this to be one of the most challenging, and most rewarding, aspects of the paper (I've published on their this innovative assessment here, with a much longer ungated version here).

It was also a great way to launch discussions of how even basic economics applies in the real world. So, in part this blog is a way for me to create a discussion space for my students, and help them to recognise the value in the economic approach to looking at real-world situations.

I'm not entirely unselfish though. There is research to suggest that blogging boosts the reputation of the blogger above economists with similar publication records, and it would be silly not to try and milk some of those benefits. And it's a good way to talk about some of the quirky research that others are doing, using economics.

What can you expect from this blog?
It's unlikely that I'll become a daily (or more frequent) blogger in the way that some of my favourite bloggers are, like Jodi Beggs at Economists Do It With Models. But I'll aim to post once or twice a week - sometimes on contemporary issues, and sometimes on quirky applied economics papers from the recent past. I'm hoping that most of my posts will apply some fairly basic economic principles, to make them accessible to my students.