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Photo by: Markus Spiske

Photo by: Markus Spiske

Measurement matters: why looking at income is crucial to internet affordability

Web Foundation · May 10, 2019

Research Director Dhanaraj Thakur looks at different methods for calculating the price of mobile broadband data — and why it matters for policymakers.

The biggest barrier for people getting online today is the cost of data. While many of us have seen prices fall to low levels, billions around the world are still kept offline by high costs.

Through the Alliance for Affordable Internet (A4AI), we advocate for reducing the cost to connect so that everyone can use the internet, regardless of where they live or the weight of their wallets. As part of this mission, we established the ‘1 for 2’ affordability target for mobile data — which says everyone should be able to access a minimum of 1GB mobile data for no more than 2% of average monthly income.

However, in our latest survey of 99 low and middle-income countries, only 31 reached this target. On average, people in these countries are asked to pay 5.76% of average monthly income for 1GB data — well above the ‘1 for 2’ threshold.

While people in high-income countries typically pay less than 1% of the average monthly income for 1GB data, the figure in Africa is 9%. If someone in the United States who earned the average monthly income of approximately US$59,160 was to pay for 1GB at the same 9% level, they’d have to come up with US$443 per month. For just 1GB data!

Two surveys, different conclusions

Our mobile data pricing research tells a clear story of global digital inequality. However, other measures come to quite different conclusions. Take a recent study from This survey of mobile data prices in 230 countries found that high-income countries like the US, Norway and South Korea have some of the world’s most expensive mobile data plans.

The report concluded that: “Contrary to what one might expect, ten out of the top 50 cheapest countries in the world for mobile data are in Sub-Saharan Africa.”

Why do two studies of the same thing come to quite different conclusions? It is crucial that policymakers and journalists understand the differences in such studies so that they are interpreted and used properly to inform policy decisions.

Looking beyond prices to affordability

There are two primary differences between the A4AI and research on mobile broadband prices and affordability. The first and most substantial difference is that A4AI looks not only at the absolute price of mobile data but at how affordable it is for people to buy. We do this by relating the price of data to the average monthly income in a country. For example, in Mozambique, 1GB of data is priced at US$2.5, the third lowest in Africa. However, relative to income, that’s actually quite expensive at 7.2% (ranked 26th of 48 African countries in our pricing database).

Calculating the costs

The second difference is simply how we arrive at data prices. To find the price consumers pay for a 1GB plan, we look for the cheapest 1GB plan (or combination of plans) offered by the largest mobile provider in a given country, valid for at least 30 days. This approach is based on the International Telecommunications Union’s (ITU) methodology, developed in partnership with governments, civil society groups and the private sector.

To arrive at the average price of 1GB data, looks at the prices all plans from all operators in a country (up to 60 plans), then calculates the average price of 1GB from these plans. Because some of these plans could have been for, say 10GB, consumers would not have been able to buy them on a 1GB basis. This method also includes plans that are valid for less than 30 days, even as low as 1 day. So, while the 1GB price given by is an indicator of the overall price of data in a country, it is not a good representation of what people actually pay. While they do also provide data on the cheapest and most expensive plans that people can buy, this has not been the focus of media reports.

What you measure matters

Does this matter? Absolutely! When prices are reported in the press, readers may misinterpret them to represent plans people can actually buy and how affordable plans are between countries. This is not the case.

We applaud data for providing a source of freely available mobile pricing data that gives a useful measure of absolute data prices and trends. And’s transparent methodology is also welcome.

However, if the data is used as a measure of affordability, it must be supplemented with a relative measure of cost. Policymakers need clear evidence to improve broadband affordability. It is therefore crucial that journalists, researchers and policymakers using datasets understand the differences and limitations in the methods used to calculate these.

For updates about our work, sign up to our newsletter and follow us on Twitter at @webfoundation. Follow Dhanaraj at @thakurdhanaraj.

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