Posts Tagged ‘ict4d statistics’

Broadband Penetration Over Time: Data Visualisation with Google Motion Chart, Gapminder and Excel

13 December 2009 2 comments

I’ve entered the ITU data on broadband penetration for all countries from 1998-2008 into a Google Docs spreadsheet, and then added the Motion Chart visualiser.

To access the spreadsheet data and Google Motion chart, go to:

The screenshot below gives an example. Also given below are two screenshot summary graphs derived from overview data about diffusion rates for broadband, which can be found at:

The most useful statistics are absolute growth rates (weighted by population), which show growth having peaked in 2005 for the richest fifth of nations, but generally still rising for the others. The percentage growth rates have been steadily declining, but mainly because those growth figures are insanely high in the first few years of broadband diffusion given the very low base they start from.

You can find similar visualisations that you can cross-match with a host of other data categories (demographics, economic/social development, and ICT diffusion) using World Bank data ( or a graph I’ve created at Gapminder: But these don’t go up to 2008, and you can’t see or access the underlying data.

Note the dynamic visualisation charts will not show up on slower PCs or Internet connections.

For similar data visualisation of mobile phone penetration, see my earlier blog entry at:


Mobile Phone Penetration: Google Motion Chart Data Visualisation

30 November 2009 7 comments

I’ve entered the ITU data on mobile phone penetration for all countries from 1998-2008 into a Google Docs spreadsheet, and then added the Motion Chart visualiser (the same engine made famous by Hans Rosling and TED, though they use the Gapminder Trendalyzer version).

Unfortunately, WordPress scripting rules mean I can’t post the active chart here. To access the spreadsheet data and Google Motion chart, you need to go to:

Screenshots below give an indicator of how you can visualise the data. The chart offers three main means to visualise (bubble, bar chart, and line graph) via tabs at the top right. You can change the axes and element colouring/size, and highlight individual countries. For bubble and bar, the main point of the chart is that you can click play (bottom left) and show how things change over time. (Note playback speed variation control, and also the ability to drag over and zoom in on parts of the chart.)

Not sure it adds a lot of analytic value but it’s engaging, helps give a sense of some overall trends, and identifies some interesting outliers. (Some older PCs and low-bandwidth connections will struggle to display.) I’ll repeat for other ITU data in later posts (e.g. broadband data visualisation here). You can find similar visualisation for mobile, Internet and a host of other development data at: (though currently up to 2007 only, no obvious access to underlying data, and the mobile data display doesn’t seem to work properly).  And, finally, on a separate blog entry you can find a set of rough converters to change mobile phone subscription data to data on ownership, access, use and non-use.

Worldwide Expenditure on ICT4D

6 April 2009 6 comments

How much money is spent every year on ICT4D?


We can calculate this two ways: top-down and bottom-up.


Top-Down Calculation: World Development Indicators


The World Bank’s World Development Indicators provide an entry for ICT expenditure as a % of GDP.  For 2007 – the latest year available – this expenditure was 5.93% for low- and middle-income countries (covering pretty well all those we tend to call developing and transitional economies; those with GNI per capita of less than US$11,455).  Given the GDP of those countries was US$14,155bn, that means spending on ICTs in all developing/transitional economies is estimated at US$840billion in 2007.


Of course this encompasses a very broad notion of ICT4D: as a random example, what Russian giant Gazprom spends on its information systems.  If we exclude upper middle income countries, and set the GNI bar at US$3,705 per capita (around the level of Indonesia, Philippines); then the figure drops to US$500bn.


Including just low-income countries (GNI <US$935 per capita; akin to Paul Collier’s “bottom billion”), we have to extrapolate, and get a figure of US$57bn: about US$44 spent on ICT per head.

WITSA data (see comments) seems to confirm these calculations.


[Note: “Information and communications technology expenditures include computer hardware (computers, storage devices, printers, and other peripherals); computer software (operating systems, programming tools, utilities, applications, and internal software development); computer services (information technology consulting, computer and network systems integration, Web hosting, data processing services, and other services); and communications services (voice and data communications services) and wired and wireless communications equipment.”]


Bottom-Up Calculation: Individual Organisations/Groups


A bottom-up approach would look at the ICT4D expenditure of individual organisations or groups.  We can identify four main spenders: development agencies; developing country governments; the private sector; and consumers.  Unfortunately, data here is a threadbare patchwork.


I will present the data I have available: if you have other/new data, please comment in order to update.


Donor/Development Agencies


Data from the World Bank Group shows it invests around US$800m per year in specific loans and guarantees on ICTs and development, and US$1-1.5bn per year on projects with ICT components (at present, it cites a total of nearly US$8bn invested in such projects).

Some very rough estimates from personal contacts with USAID suggest perhaps something like US$800m being spent on all ICT components of development work per year.  Even rougher estimates from JICA’s annual reports suggest it is spending at least US$200m per year, and probably significantly more.


Data from various bits of the International Telecommunication Union Web site suggests an expenditure of around US$60m per year on its development activities (c.20% of total expenditure).  The EU’s 9th European Development Fund (2000-2007; focused on Africa, Caribbean, Pacific development) included about US$20m per year (c.US$150m in total) for ICTs.  There is also expenditure on ICT4D as research collaboration under the EU’s Framework Programmes.


Canada’s IDRC spends 15.8% of its budget on ICT4D; that budget spending was C$190m in 2008, meaning a total spend of around US$25m per year on ICT4D.  Korea’s International Cooperation Agency seems also to spend around US$25m per year on ICT4D; about 13% of budget.


SIDA appears to be spending around US$3m per year on ICT4D.


Delivery agencies with a specific focus on ICT4D have similarly small budgets, and will not make a significant dent on the overall figures.  Examples would include IICD which spends around US$6m per year, and the Global Knowledge Partnership which may spend about half that.  Quite a bit of this money would come from donor agency funds.


Developing Country Governments


Few if any developing country governments appear to compile comprehensive figures on their ICT investments.  Instead, they quote expenditure that is specifically identified as “ICT”; for example, the budget of the Ministry of ICT.  This will probably exclude the majority of what the government spends on ICT.  For example, Ghana seems to budget ICT spending on health and education under health and education respectively, not under ICT.


Quoted annual government expenditures on ICTs via this narrow definition for some “typical” medium-/large-sized developing countries are in the few hundreds of millions of dollars.  E.g. Indonesia (US$340m); Thailand (US$300m); South Africa (US$130m).  These are about 0.5% of total government budget; and just under 0.1% of total GDP.


Extrapolating that latter figure, for low and lower-middle income countries, that would suggest investments of about US$7.5bn per year, but the actual figure must be significantly higher than this.  As one example, the Indian government in the mid-2000s was already in the process of increasing its total spending on ICTs (i.e. not just that specifically allocated to the ICT heading) from 2% to 3% of budget: a figure of around US$3bn.  By comparison, its direct spending on ICT (mostly allocated to e-government) was around one-tenth of this.


Private Sector


Private sector investment levels in mobile telephony are, according to the GSMA, around US$10bn per year in Africa; very roughly US$10 per capita.  If at least that amount is also spent in the other developing country markets, that suggests a total investment per year of at least US$50bn.


Other ICT investments in computers, software, non-mobile-based Internet connectivity, and so forth, would be in addition to this figure.


The private sector also has specific development-oriented activities.  Examples would be Microsoft Research India, and parts of Microsoft’s Unlimited Potential programme, or Intel’s World Ahead.


Consumer Expenditure


Individual consumers spend money on ICTs that are part of ICT4D; for example, the amount they spend on mobile telephony, and on use of telecentres.


Extrapolating figures from Nigeria, which suggest an average per capita spend on all telecommunications of US$55 per year, would indicate spending of around US$55bn per year on telecoms in Africa.  Much of that, of course, would be spent by business rather than individuals, and that money then recirculates for further private sector investment.  If those same figures could be extrapolated across all developing countries, they would suggest a spend of around US$300bn per year, but that is likely a significant underestimate since Nigerian expenditure will be below developing country averages.  That US$55 per year is actually MORE than the US$44 figure indicated from the World Development Indicator figures, and yet it only covers telecommunications.


Alternatively, Mpogole’s work in Tanzania found rural mobile phone owners spending around US$22 per month (US$270 per year) on their mobiles.  Using ITU’s 2007 figures (21% subscription rate) and the corrector discussed in a previous blog, we arrive at a spend just on mobiles of US$43 per person per year.  At least, then, all these figures are not wildly dissimilar, given that spending on mobiles will be by far the major expenditure on ICT4D in developing countries.




The figures here cover some very different things.  Some cover a lot of what many would regard as outside the boundaries of ICT4D.  Nonetheless, it seems reasonable to conclude that hundreds of millions of US dollars per year are invested in ICT4D projects; and that tens of billions of US dollars per year are invested in ICT4D infrastructure, with consumers in developing countries spending even more on the use of ICTs, amounting on average to a few tens of US dollars per person per year.


As noted above, additions and updates are welcome.


Note: the SIDA source cited above contains, in its Chapter 4, a quick review of some of the main actors investing in ICT4D.


Beyond Subscriptions: Actual Ownership, Use and Non-Use of Mobiles in Developing Countries

22 March 2009 15 comments


As widely reported, the number of mobile phone subscribers in the world passed the four billion mark at some point around the end of 2008, in a global population of around 6.7bn of whom about 80% (5.4bn) live in developing countries.


At first sight, that might suggest that 60% (4 / 6.7) of the world’s population has a mobile phone.  Given (ITU stats) that the subscriber rate in industrialised countries is roughly 100 per 100 inhabitants, that might also suggest that 50% ((4 – 1.3) / 5.4) of those living in developing countries had a mobile phone at the start of 2009.


We arrive at similar figures if we extrapolate the ITU 2007 stats using the CAGR% for 2002-2007 (minus population growth for the per 100 inhabitants data), to get a 2008 figure:

– Africa: 409m mobile subscribers; 41 subscriptions per 100 inhabitants

– Americas minus US/Canada: 483m subscribers; 84 subscriptions per 100 inhabitants

– Asia minus Japan/S. Korea/Israel/Singapore: 1736m subscribers; 45 subscriptions per 100 inhabitants

– All developing countries: 2.63bn subscribers; 49 subscriptions per 100 inhabitants


BUT . . . These figures have a number of problems.  I summarise below what little I have found: if you know more, please comment.


Actual Ownership


First, mobile subscription figures are overestimates of in-country mobile ownership for at least four reasons (see James & Versteeg 2007, and Kalba 2008):

– Some individuals have multiple subscriptions

– Visitors (both foreigners (tourists, business visitors) and nationals who currently reside abroad) buy a subscription/card for their phone during a short-term visit

– Some people living in neighbouring countries may subscribe when they live close to the border within service range

– Subscriptions are counted for some period of days/months after the last use; some of these subscriptions may be on cards/phones that are now discarded


How big is this effect?  Of course it varies, but a gratingly rough estimate is that in-country ownership is 75% of the subscription figure.  Ewan Sutherland reports an EU-wide figure of 103 subscriptions per 100 population in 2006, but on-the-ground surveys indicating 79 per 100 own a mobile phone.  Gillwald et al report 44 subscriptions per 100 population in South Africa in 2004, but on-the-ground surveys indicated 33 per 100 mobile phone ownership.  de Silva et al (2008) surveyed in India in 2006 and found 9 mobiles owned per 100 respondents, compared to ITU data for the same period of 15 subscriptions per 100: a converter of 60%; in Sri Lanka, the converter was 85%.  Wireless Intelligence produced a report indicating real penetration as a percentage of reported penetration for 2006 was: Romania (80%); Turkey (79%); South Africa (76%).


Within the EU, the ratios vary from about 50% (wealthy Luxembourg where multiple subscriptions are very common) to roughly 100% in France.  In accession state Bulgaria, the figure was about 55%, perhaps due to it having so many foreign second home owners, nationals working overseas, and transit visitors.  So the 75% estimate covers quite a wide variation that will depend on specific national conditions.  We also need a lot more data from developing countries themselves (where there may be a fifth reason for overestimation according to James & Versteeg: those who own SIM cards but not phones).


Actual Use


Second, mobile subscription figures are underestimates of in-country mobile phone access and use for at least two reasons:

– Private mobile phones are shared with family, friends, neighbours, etc.

– Public mobile phones are accessible to large numbers of people.


How big is this effect?  James & Versteeg cite an estimate of two users on average per privately-owned mobile phone on the basis of Vodafone Tanzania data; and 70 users on average per public mobile on the basis of Grameen Phone Bangladesh data.  But they also note that levels of sharing seem to vary a lot between countries.


If we take the 75% figure and the “two users” figure, this would mean that usage rates of private mobile phones in developing countries are 1.5 times the cited subscription rates.  So, for example, that would estimate in 2008 there were around 615m private mobile phone users in Africa: about two-thirds of the population.  That’s also (citing GSM Association data) about the proportion of the population that was covered by a mobile signal.


Of course, that excludes those who use public mobiles and other public phones.  Looking at de Silva et al’s Asia data, we might estimate that in the poorer developing countries, for every mobile phone owner, there are about three others who don’t own any phone, but find a way to access and use one.  However, the figures vary wildly and the ratios decrease rapidly as mobile phone ownership rises.  It may be better to lump all phone use together and ask our final question . . .


Levels of Non-Use


Thirdly, how many people still do not use a phone?  In the 1990s, we circulated the much-quoted “fact” that half the world’s population had never made a phone call.  How do things look now?  Let us reduce the 350m in Africa who live outside cell phone coverage with Gillwald et al’s data that around 25% of rural populations in Africa had used public payphones in the past three months.  We get roughly 250m non-phoners.  About 40% of these will be under 15; we’ll exclude those, to reach 150m adult non-phoners.


In Asia, de Silva et al’s survey work from late 2006 suggested only 4.5% of adult lower-income group members in the countries they studied had not made a phone call in the previous 3 months.  That suggests 120m non-phoners.  And we might guess roughly the same proportion for Latin America, giving about 20m non-phoners there.


So, a very rough and ready estimate suggests about 300m adult non-phoners in developing countries.  This number becomes larger if we start adding in children: around 10% of the developing world’s population (some 500m) is under 5; something like a further 1.5bn are aged 5-14.  Many of them will have made phone calls, but many will not.


And Finally


Finally, some additional confusions:


– The 75% conversion from subscriptions to ownership might get messed up by age demographics.  Gillwald et al did draw from all age ranges to get their survey figures.  It’s not clear if the EU and Bulgaria figures cited by Sutherland do the same, and the de Silva et al data does not seem to have done so.  We can at least estimate that about 25% of Africa’s population and perhaps 20% of Asia’s and Latin America’s population might be seen as too young (10 or under) to own a mobile phone.  That would mean, ironically, that the mobile subscription per capita figures and the actual ownership per capita of adult populations could be about the same.


– The basis for the figures is not totally clear, but in a number of surveys (some sub-Saharan African countries covered by Gillwald et al; some Asian countries covered by de Silva et al), the reported mobile ownership per capita figures were the same, or even higher, than the ITU-reported mobile subscriber per capita figure for that country.  This may reflect the exact population from whom the survey data was gathered (e.g. more urban than the general population), but it may well also reflect just how ropey are the statistics on mobiles in developing countries, where ballpark figures and trends are all we can really talk about.


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