ICT as a tool of development Chenai Chair Researcher, Research ICT Africa 13 October 2015 Prepared for the Film and Publication board: Classification and online protection conference. 11-14 October 2015
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ICTs and development?
- Being part of information society, facilitated by information technology leads to changes in interaction, economic and business practices amongst others (Sandys, 2005).
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ICTs and development How does technology play a part in development? - ICTS recognised as cross enablers to achieve SDGs - ICTs as a tool in development could foster: - economic growth and job creation - reduction of transaction cost - inclusion alternatives - creation of social cohesion - better informed citizens
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ICTs as a tool for development ‣ Reduction of transactional cost-real time information exchange without mobility ‣ Opportunities for inclusion e.g. mobile money “banking the unbanked” ‣ Social cohesion-increased communication ‣ Better informed and engaged citizenry ‣ Innovation in creation of local and relevant content
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ICTs as a tool for development ‣
Economic growth and job creation from ICTs, specifically mobile connectivity
GDP and fixed, mobile,broadband penetration issues of causality (Waverman and Roller)
10% broadband penetration growth increased GDP growth by 1.4%. (World Bank, 2009)
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Estimates of increased mobile broadband could add $400billion annually to GDP and create 10million jobs (Mckinsey)
What are the challenges to making use of ICTS as a tool for development?
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Barriers to sector growth - Major barriers to sector growth: - Lack of investment/competitive or affordable backbone - Size/quality of infrastructure/ bandwidth - High costs/price of access to communications - Effective regulation/weak institutional arrangements - Beyond access- Human development: - Income - Education - Skills 7
Problems with evidence ‣
Unevenness of indicators, reflection of uneven development (self perpetuating, vicious or virtuous cycle).
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Assumptions behind global indicators and indices reflect the political economy of mature economies and democracies of the North.
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Very different access and use trajectories in Global South make some standard indicators meaningless and others very difficult to gather.
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What are the underlying data sources and how effective are they?
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Case of pricing/affordability
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Whose evidence and who sets the agenda?
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RIA - Lifting the veil on ICT gender indicators indindndicatorsstatistics
Sex-disaggregated descriptive statistics indicate that women and men are not equally able to access and use ICTs.
Women generally have less access to ICTs and use them sub-optimally and this increases as the technologies and services become more sophisticated and expensive.
Logit and probit modelling however demonstrate education and income have a positive impact on ownership and use of ICTs.
The gender disparities found in income and education, indicate they are key factor of exclusion and main point of intervention for inclusion.
The positive and causal relationship between education and income further points to the importance and need for ensuring equity in education (and therefore job/income generation opportunities).
Internet access seems to be wide spread in learning institutions, but women have less access to higher education where Internet provisioning is more available.
Women use public phones mainly because of affordability issues.
The points of policy intervention therefore need to focus on far more fundamental intergenerational issues of education and income equity than localised ICT aggregated access points, or discounted packages for women.
Poor women and men, with low income levels and income have more in common in relation to accessing and using ICTs than with women in many developing countries, though there may well be cultural factors the explain the concentration of women in lower income groups. 14
Where do indicators come from?
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ICT indicators
No good and bad indicators, just some measure somethings better than others
‣ Access indicators: measure what people or businesses have in terms of ICTs or how many exist in a country. ‣ Usage indicators: measure how and for what ICTs are being used by households, individuals, businesses or governments etc. ‣ Impact indicators capture the impact of access and usage on economic growth, employment creation, improvement in public service delivery on a macro level; and company performance, household poverty levels and social inclusion on a micro level. •
Impact indicators are usually derived from analysis of primary or secondary data. 16
Problems with data
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Up to a two line subtitle, generally used to describe the takeaway for the slide
Most of the indicators are per capita measures which is the traditional method of illustrating individual access to ICTs. One reason for this is that virtually all ICT service providers compile administrative records for operational and billing purposes. It is then a simple mathematical exercise to divide the installed base of a particular ICT device or service by the population to derive a per capita indicator. PARTNERSHIP ON MEASURING THE INFORAMTION SOCIETY, CORE INDICATORS (2005: 5)
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ICT Development Index (IDI) ‣ ICT Readiness (infrastructure, access) ‣ ICT Intensity (use) ‣ ICT Capability (skills)
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Share of households with fixed-lines 2007/8
2011/12
South Africa
18,2% 18,0% 17,4%
Namibia
11,5% 11,0%
Botswana
15,0% 7,6%
Ethiopia
4,0% 2,6% 1,8%
Ghana Kenya
2,3% 0,6% 1,8% 2,2%
Cameroon Tanzania Uganda
0,9% 0,4% 0,3% 1,5%
Rwanda
0,1% 0,2%
Nigeria
0,3%
Fixed-lines on the way out except Botswana, Cameroon, Uganda and Rwanda
Share of households with a working computer South
24,5%
Botswana
15,7%
Namibia
14,7%
Kenya
12,7%
Share of households with a working Internet connection South Kenya
Nigeria
Ghana
8,5%
Ghana
Uganda
2,2%
Rwanda
2,0%
Tanzania
1,6%
Ethiopia
0,7%
11,5%
Botswana
8,6%
6,6%
12,7%
Namibia
Cameroon Nigeria
19,7%
8,6% 3,4% 2,7%
Cameroon
1,3%
Uganda
0,9%
Tanzania
0,8%
Rwanda
0,7%
Ethiopia
0,5%
Less than a quarter of households have a computer and even fewer Internet access
Where was the Internet used first? Computer
Mobile phone
Cameroon
82,1%
17,9%
Rwanda
70,8%
29,2%
Botswana
70,6%
29,4%
Ghana
70,5%
29,5%
Kenya
68,9%
31,1%
South
65,1%
34,9%
Namibia
50,1%
49,9%
Tanzania
45,8%
54,2%
Nigeria
45,2%
54,8%
Ethiopia
33,3%
66,7%
Uganda
28,2%
71,8%
Where the Internet was used in past 12 months Mobile phone
Work
Place of education
Internet cafe
0,74 0,847
0,36
31%
0,209 17%
55%
48%
36%
52%
45%
61%
64%
71%
71%
75%
75%
78%
81%
81%
87%
South Africa
Rwanda
Tanzania
Nigeria
Kenya
Ethiopia
Uganda
Namibia
0,388
0,422
Botswana
0,244
0,512
51%
35%
Cameroon
0,209
0,307
0,451
0,225
0,196 29%
0,8 0,201 10% 30%
0,322
0,325
0,724
0,628
Ghana
0,509
0,502
0,583
Broadband issues
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Broadband introduces levels of complexity in policy, regulation, business models and consumer choice
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Cost of communication
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OECD 2010 Definition: Basket Methodology Weaknesses ‣ No one is average ‣ Baskets do not reflect the most popular package but the cheapest product ‣ The same basket is used for all operators: offnet/on-net ratio depends on market share ‣ Only dominant operators - new entrants and small operators are likely to be price challengers 27
Comparing Countries
OECD Basket Methodology
Comparing Operators
Comparing Products
‣ Comparing the difference between -
cheapest in country cheapest from dominant operators
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cheapest in country cheapest from most expensive operator
‣ Comparing cheapest product available from -
dominant operators
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cheapest operator
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most expensive operator
‣ Benchmarking 28
Challenges ‣ OECD only updates every 3-4 years ‣ ITU introduced annual basket ‣ Relevance of voice data dichotomy ? ‣ Policy work requires quarterly/monthly ‣ Dynamic pricing ‣ Dynamic discounts ‣ Flexible, self constructed baskets
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http://www.researchictafrica.net/prices/Fair_Mobile_PrePaid.php
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South Africa pricing trends
OECD basket price in rands for South Africa 31
And the cost of data?
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Prepaid data (USD) Rwanda Mozambique Tunisia Tanzania Madagascar Niger Senegal Burkina Faso Kenya Ghana Sao Tome and Principe Ethiopia Benin Algeria Malawi Uganda Liberia South Africa Mali Namibia Nigeria Togo Chad Cote d'Ivoire Zambia Cameroon Gabon Sierra Leone Sudan Angola Lesotho Bostwana Zimbabwe Swaziland
Tanzania
4,4 4,4 5,2
Kenya Rwanda Mozambique
8,0 8,1 8,4 8,4 8,4 9,0 9,1 9,1 9,8 10,1 10,2 10,6 11,6 12,0 12,3 12,6 13,2 16,7 16,9 16,9 16,9 18,0 20,2 23,6 24,0 24,4 24,4 27,3 30,9
Ghana Tunisia Sudan Mauritius Malawi South Africa Niger Togo Senegal Burkina Faso Nigeria Sao Tome and Principe Uganda Ethiopia Benin Algeria Liberia Mali Namibia Cameroon Madagascar Lesotho Zambia Gabon Chad Cote d'Ivoire Angola Sierra Leone Bostwana Zimbabwe
35,0 37,7
Cheapest 1GB price from operator with dominance in country!
Swaziland
3,8 4,3 4,4 4,4 4,5 5,2 5,8 7,3 8,1 8,2 8,4 8,4 8,4 8,4 9,1 9,1 9,3 9,8 10,1 10,2 12,0 12,6 13,2 13,5 14,6 14,9 16,5 16,9 16,9 16,9
22,6 24,0
28,3 30,0
37,7
Cheapest operator 1GB price in country!
South Africa data price References ‣
Stork, C Calandro E and Gillwald A (2013) I Internet Going Mobile: Internet access and usage in eleven African Countries . Understanding ICT in Vodacom MTN Cell C Telkom Mobile Africa Series, Policy Paper no www.researchictafrica.net/.../2012%20Calandro%20Stork%20Gillwald%...
Virgin Mobile
Raul Katz: Economic Impact of Broadbandhttp://www.itu.int/ITU-D/treg/broadband/ITU-BB-Reports_Impact-of-Broadband-on-the-Economy.pdf
100Emmanuelle Auriol and Alexia Lee González Fanfalone - Copenhagen Consenus Read more at
http://www.project-syndicate.org/commentary/broadband-access-lower-poverty-by-bj-rn-lomborg-2015-01#1hbPpa9l7ubvMXMl.99 Mackinsey(2010). Fostering the Economic and Social Benefits of ICT in The Global Information Technology Report 2009-2010 @ 2010 World Economic Forum. http://goo.gl/WLWZdm
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Pantelis Koutroumpis The Economic Impact of Broadband on Growth: A simultaneous approach.
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State of Broadband 2013: Universalising broadband http://www.broadbandcommission.org/Documents/bb-annualreport2013.pdf
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150
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1 GB(ZAR)
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RIA (2104) Fall from grace: protectionism and monopolies push Cameroon down broadband index available at www.researchictafrica.net/policy/mobile_retail_price_comparison/2014_RIA_Policy_Brief_No_4_-_Cameroon.pdf
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...Stork, C and Gillwald, A (2014) Link between termination rates and retail prices in Namibia, Kenya and South Africa, Telecommunications Policy, Volume 38, Issues 8–9, September 2014, Pages 783-797, Elsevier, Pergamon.http://
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200Mar 13, 2013 - African countries. Enrico Calandro, Christoph Stork & Alison Gillwald. Research
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References ‣
Stork, C Calandro E and Gillwald A (2013) I Internet Going Mobile: Internet access and usage in eleven African Countries . Understanding ICT in Africa Series, Policy Paper no www.researchictafrica.net/.../2012%20Calandro%20Stork%20Gillwald%...
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Mar 13, 2013 - African countries. Enrico Calandro, Christoph Stork & Alison Gillwald. Research ...Stork, C and Gillwald, A (2014) Link between termination rates and retail prices in Namibia, Kenya and South Africa, Telecommunications Policy, Volume 38, Issues 8–9, September 2014, Pages 783-797, Elsevier, Pergamon.http://
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RIA (2104) Fall from grace: protectionism and monopolies push Cameroon down broadband index available at www.researchictafrica.net/ policy/mobile_retail_price_comparison/2014_RIA_Policy_Brief_No_4_-_Cameroon.pdf
And the cost of data? ‣
State of Broadband 2013: Universalising broadband http://www.broadbandcommission.org/Documents/bb-annualreport2013.pdf
‣
Pantelis Koutroumpis The Economic Impact of Broadband on Growth: A simultaneous approach.
‣
Raul Katz: Economic Impact of Broadbandhttp://www.itu.int/ITU-D/treg/broadband/ITU-BB-Reports_Impact-of-Broadband-on-the-Economy.pdf
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Emmanuelle Auriol and Alexia Lee González Fanfalone - Copenhagen Consenus Read more at http://www.project-syndicate.org/commentary/ broadband-access-lower-poverty-by-bj-rn-lomborg-2015-01#1hbPpa9l7ubvMXMl.99
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Mackinsey(2010). Fostering the Economic and Social Benefits of ICT in The Global Information Technology Report 2009-2010 @ 2010 World Economic Forum. http://goo.gl/WLWZdm
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