Spark's new overseas roaming charges and price discrimination

I've just gotten back home from three weeks in Europe. One irksome but necessary aspect of travelling is mobile phone roaming. While I was away, Spark introduced new roaming charges, and their new options both increase the price per day of roaming for most overseas trips, and price discriminate so that those staying overseas for longer pay a higher price for roaming. As the New Zealand Herald reported:

Spark customers travelling overseas for the school holidays face new charges to stay connected, with the telco scrapping its cheapest $25 fortnightly roaming pack.

The company is overhauling its roaming plans, with the new charges taking effect this Friday, including an automatic $10-a-day fee if customers don’t turn roaming off...

Previously, pay monthly customers could use 2GB of data on one of the provider’s 14-day roaming packs, priced at $25 and $30...

Three new packs will replace the old plans, alongside a new daily roaming option.

A $30 14-day pack will still be available to prepaid customers.

The other options will provide travellers with 20GB to use over 30 days, a change the company believes will make roaming simpler and more predictable.

“This helps our customers to stay connected for longer, with fewer top-ups, less uncertainty, and greater confidence about what they’ll pay.”

While the $50 and $65 packs have a higher upfront cost, customers would receive five times more data to use than under the previous plans, the spokesperson said.

If you look at the price per gigabyte of data, the new roaming packs are clearly much better value. Customers are paying twice the price, but getting ten times the data. So, high data users are likely to be better off under these plans. I want to focus instead on travellers who are not using large amounts of data (and for simplicity, I'm going to focus on the data-only packs, not the more expensive packs that include roaming calls and texts). For those travellers, when you look at the cost per day of roaming, the new packs are far more expensive. This is illustrated in the diagram below, which shows the costs for up to 30 days of roaming. The bold green line shows the existing pricing for a 14-day data-only roaming pack ($25 for each 14-day period). The light blue dashed line shows the cost using the new $10 daily roaming rate. The orange dashed line shows the cost for the new 30-day data-only roaming pack ($50 for each 30-day period).

For a Spark customer roaming for one or two days only, the new daily roaming pack is the cheapest option. So, if you're travelling to Australia for a day or two of shopping or to attend a concert or a sporting event, the new option is a better deal than what was previously on offer. With the new options, daily roaming is lower cost than buying a 30-day pack for up to four days of roaming, and the same cost as the 30-day pack for five days of roaming. Beyond that, you would be better off buying the 30-day roaming pack, even if you are only roaming for seven days.

The comparison between the old 14-day roaming pack and the 30-day roaming pack makes it clear that anyone roaming between five days and 14 days will now be paying twice as much as before. From 15 to 28 days, the cost of roaming with the new packs is the same as for the old packs. For someone like me, who typically goes overseas for a conference and might be away for 10-14 days at a time, this is clearly going to increase the cost of roaming.

It may be that Spark has determined that the new pricing options better reflect actual customer usage. That is what a Spark spokesperson argues in the New Zealand Herald article. However, it is also clearly an example of price discrimination in action. Travellers going overseas for a few days likely have more elastic demand for roaming than travellers going overseas for a longer time. That's because of the availability of close substitutes. If you go overseas for a few days, you could make use of free hotel and airport WiFi, or be prepared to just switch off mobile data for the time you are away, rather than paying for roaming. So, travellers who go overseas for a few days are likely to be relatively price sensitive. Travellers going overseas for a longer time are less likely to be able to switch off mobile data for that length of time, making them less price sensitive. The optimal pricing therefore is to set a higher price for travellers going overseas for a longer time than for those going overseas for a few days.

Price discrimination is very common in practice. In this case, Spark is using price discrimination and that will likely increase their profits. And that means that many travellers who are not high data users, myself included, will be paying more for roaming in the future.

This week in research #133

This week I attended the 18th International Conference on Education and New Learning Technologies in Palma de Mallorca. Often, conferences in holiday locations are little more than an academic junket, but this conference certainly bucks that trend, which is why I keep coming back to it every few years. As you might expect given the title of the conference, this year it was heavily dominated by research on generative AI in education (at all levels, from K-12 to postgraduate). My own presentation was on the impact of introducing Harriet, our ECONS101 tutor, on student performance and experiences in ECONS101. I'll be giving a longer version of that presentation at a seminar at the University of Exeter in the UK later today. Anyway, here are some of the highlights I found from the conference:

• Chris Godfrey outlined the factors associated with student persistence at Manchester Business School, showing that at-risk students can be identified early by the extent of their engagement in their studies, as well as quantitative difficulties
• Ioannis Famelis presented on designing a custom GPT and Perplexity Space that can guide students on questions related to their graduate studies, specifically on curriculum regulations and identifying the most appropriate thesis supervisor
• Deniz Iren presented in detail on the development of custom AI tutors using a bespoke platform that looks very promising, called WiseTutor.ai
• Jonathon Cohen discussed how scenario-based learning and assessment could be used to maintain authenticity of assessment and real-world contexts in the face of generative AI
• Soeren Dressler looked at student perceptions of oral examinations as an assessment tool, and found that students had a strong preference for written examinations over oral examinations, potentially due to fear of the oral examination format, but students also believed that oral examinations were better at ensuring their learning
• Marian Hurley presented on student perceptions of continuous assessment, showing that students recognised the challenges to continuous assessment arising from generative AI, and showed a strong preference for a move to more invigilated assessment

Aside from the conference, here's what caught my eye in research over the past week:

• The Nobel lectures by Joel Mokyr, Philippe Aghion, and Peter Howitt
• Bluhm, Lessmann, and Schaudt (with ungated earlier version here) find that cities that gain the status of being a capital city grow faster in the medium term, and this growth spills over to nearby cities, and this arises through migration of educated individuals to capital cities and increased public and private investment

Airports and regional development

Most large regional cities have their own airports. Is that because growing regions are more likely to open an airport, or because having an airport leads to faster population growth for small regions? Probably, it is a combination of both, but empirically they are difficult to disentangle. However, this 2025 article by Jørn Rattsø (Norwegian University of Science and Technology) and Nicholas Sheard (Deakin University), published in the Journal of Economic Geography (open access) attempts to answer the question of how much regional airports contribute to growth.

Rattsø and Sheard focus on the example of Norway, where the number of regional airports grew rapidly from the 1950s, with fifty new airports opening between 1950 and 2019. They apply an event study difference-in-differences approach with synthetic controls. That means that they compare regions where an airport opened with synthetic controls made up of a weighted average of other regions, between the time before and the time after the opening of the airport. The outcome variable they concentrate on is the regional population, but they also look at employment (in total and by broad industry category).

Rattsø and Sheard find that:

...regions where airports were opened subsequently experienced growth in both population and employment, relative to otherwise similar regions that had been on similar growth paths before the airports were opened...

The size of the effect is relatively modest, with population growth about 0.4 percent higher after 1-5 years, 0.9 percent highers after 6-10 years, 0.5 percent higher after 11-15 years, and no difference after 16-20 years of the airport opening. Rattsø and Sheard also report a number of heterogeneity analyses, which are interesting too:

The population growth effects of new airports are largest and most significant for airports established in the first decade studied (the 1950s) and for new airports opened where there were no other airports within 100km... the growth effects are relatively large and more often statistically significant for airports that are physically larger (measured by length of runway) and that have a connection to at least one of the four largest cities in the country.

The first of those heterogeneity results points to a potential problem with the analysis. Airports are not opened randomly. Governments are more likely to open airports in regions where those airports are likely to have the largest effects first. And so, the effects being largest for the airports that were opened in the 1950s may be because those regions were going to grow rapidly regardless of whether an airport was located there or not. The synthetic control method attempts to deal with this by comparing regions with an airport with a weighted average of other regions without an airport, where the weighted average control 'looks like' the region that received an airport. However, this approach can only ever provide an imperfect control, because the reality is that the regions that are part of the control did not receive an airport, and if airports are allocated first to regions that are likely to grow faster, then the comparison with the synthetic control may simply pick up that fact.

The other heterogeneity results are consistent with what we would expect if regional airports do lead to faster population growth. If airports increase growth, then larger airports should increase growth by more. And connectivity matters, particularly to larger regions (although it is worth noting that when you have an airport, the flights go in both directions, and so it is by no means a given that increasing connectivity leads to net in-migration). The results for employment are also consistent with expectations, with increases in employment in the 'transport and communications' sector, as well as services.

Rattsø and Sheard rightly conclude that:

...the effects were concentrated in the early era of expansion when the air network was much less developed and similar benefits are not likely to be available today. In addition, the effects of having a small airport are limited: having an airport with little air traffic and few connections is not helpful for regional development. For peripheral regions, it may be better to improve road and other infrastructure to reduce travel times to larger airports with better connections, rather than building their own airports.

None of those conclusions should be surprising. However, the results from this study should caution against small regions in modern times arguing strongly for the opening of a new airport. Taking the results from this study at face value, where the air network is already extensive, adding an additional small airport will have little effect on population growth. There may be other good reasons to open a small regional airport, but expecting an increase in population growth should not be among them.

This week in research #132

Here's what caught my eye in research over the past week (a very quiet one, as I've been travelling in the UK, which also explains the lack of blog posts this week):

• Skryabin tests the proposition that 'stolen food tastes better', finding that 'high-risk covert taking' increases pleasantness of food by 39.3 percent compared with legitimate consumption
• Cortinhas et al. (open access) find that lecture absenteeism at UK universities is strongly associated with access to recorded lectures, inconvenient scheduling, less engaging sessions, and high student workload (no surprises there), and that tutorial attendance is higher when tutorials feature exclusive content, interactive problem-solving, and opportunities to ask questions