Towards Evidence Based ICT Policy: Access & Usage in 17 African Countries

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1 Towards Evidence Based ICT Policy: Access & Usage in 17 African Countries Alison Gillwald Research ICT The EDGE Institute Telecommunications Infrastructure and Economic Performance ENTS - Paris October 2008

2 Research ICT Africa! Network of researchers conducting ICT policy and regulatory research in 20 African countries across the continent in the absence of data and analysis required for evidence based policy

3 Towards evidence based policy Policy research based on series of supply and demand side research undertaken by the network which is triangulated with a telecommunications regulatory environment perception survey. Integrate into an index of indicators that will provide decision-makers with an understanding of policy performance and identify points of intervention

4 Infostate of Africa S. Africa Senegal Kenya Zambia Ghana Cameroon Uganda Ethiopia HYPOTHETICA Sciadas, G. (2005). From the Digital Divide to Digital Opportunities : Measuring infostate for developme Montreal: NRC Press.

5 Sector performance as policy outcomes

6 Supply side - policy outcomes

7 Supply side - mobile pricing

8 Telecommunication Regulatory Environment

9 Investment Nigeria vs SA

10 Demand side survey Nationally representative surveys in 17 African countries (Nigeria incomplete) Comprehensive data 23,000 households and individuals 3 Step Cluster sampling - urban, metropolitan, rural

11 Step 1: Metropolitan / Other Urban / Rural Metropolitan: Benin Cotonou / Porto Novo / Parakou Botswana Gaborone / Fransistown /Lobatse / Selebi Phikwe Burkina Faso Ouagadougou / Bobo-Dioulasso Cameroon Duala / Yaounde Ethiopia Addis Abeba Ghana Accra/ Kumasi Ivory Coast Abidjan Kenya Nairobi / Mombassa Mozambique Maputo Namibia Windhoek / Walvisbay / Swakopmund Nigeria Lagos / Abuja Rwanda Kigali Senegal Dakkar South Africa Johannesburg / Pretoria /Cape Town / Durban / PE Tanzania Dar es Salaam Uganda Kampala /Entebbe Zambia Lusaka / Livingston / Ndola Step 2: PPS Random Sample of EAs Step 3: Simple Random Sample of Households within Eas Focus groups in five countries

12 WTP: Exponentially distributed Payment Ladder

13 EA Map example 1

14 EA Map example 2

15 QuickTime and a decompressor are needed to see this picture.

16 Gender disaggregations - mobile

17 Fixed Lines

18 Urban share of residential fixed lines

19 Fixed line expenditure vs willingness to pay South Namibia Kenya Mozam Cameroon Benin Cote Burkina Ghana Uganda Botswana Ethiopia How much did you spend on your fixed line last month (charges and line rental) US$ 5,93 4,3 20,21 19,16 16,37 15,7 14,47 13,27 12,71 12,27 31,31 27,51

20 Continued use of public phones

21 Willingness and ability to pay

22 Mobile WTP

23 Mobile monthly mobile expenditure in US$ / monthly disposable income US$ top 25% in terms of despoable income monthly mobile expenditure in US$ / monthly disposable income US$ for bottom 75% in terms of disposable Income Zambia* Uganda Tanzania South Africa Senegal Rwanda Nigeria Namibia Mozambique Kenya Ghana Ethiopia Cote d Ivoire Cameroon Burkina Faso Botswana Benin 0% 10% 20% 30% 40% 50% 60% 70% 80%

24 Anticipated usage and expenditure in case of price change for existing users

25 Home computer + Connection Households with computer at home Households with working Internet connection South Africa Namibia Kenya Ghana Nigeria Botswana Senegal Cameroon Mozambique Benin Burkina Faso Cote d Ivoire Uganda Tanzania Rwanda Ethiopia 2,2% 0,3% 0,6% 0,1% 0,9% 1,2% 0,9% 1,9% 0,1% 1,3% 0,0% 1,3% 0,5% 1,2% 0,0% 1,0% 0,0% 0,3% 0,0% 0,2% 0,1% 4,8% 3,3% 5,5% 5,1% 5,1% 4,5% 4,4% 4,1% 3,8% 11,2% 14,8%

26 Points of Internet Access Cameroon 95,0% Burkina Faso 92,0% CYBER /Internet, Café Nigeria 89,0% Rwanda 86,5% at home Benin 85,1% Cote d Ivoire 84,9% 12,7% at another persons HOME Ghana 77,1% 19,3% Senegal Tanzania 70,0% 68,9% 15,7% 41,7% at an educational institution (school, university, etc.) Kenya 65,5% 20,2% Ethiopia 60,0% 26,5% 23,7% at work Uganda 51,5% 19,6% 52,9% South Africa 45,9% 29,2% 32,4% using a mobile phone Botswana 31,5% 28,1% 37,9% Mozambique 27,9% 21,2% 29,2% 33,3% 21,7% library Namibia 24,3% 21,7% 35,3%

27 Internet awareness and usage Do you know what the Internet is? Do you ever use the Internet? South Africa Senegal Zamibia Cameroon Nigeria Kenya Namibia Ghana Botswana Benin Cote d Ivoire Burkina Faso Tanzania Ethiopia Rwanda Uganda Mozambique 50,8% 45,0% 43,4% 38,9% 38,3% 32,2% 26,7% 26,6% 22,0% 5,8% 21,5% 8,7% 17,3% 6,7% 9,0% 4,3% 8,7% 2,2% 8,6% 0,7% 6,7% 2,0% 6,5% 2,4% 3,8% 1,0% 5,6% 8,8% 15,0% 3,3% 13,0% 12,7% 10,1% 15,0%

28 Internet usage/frequency Mozambique South Africa Kenya Namibia Ghana Botswana Tanzania Senegal Cote d Ivoire Uganda Ethiopia Burkina Faso Nigeria Benin Cameroon Rwanda Every day or almost every day At least once a month 60,0% 56,2% 41,0% 35,2% 31,9% 31,3% 18,7% 31,4% 17,7% 25,9% 15,8% 36,5% 15,4% 14,5% 48,9% 13,5% 31,5% 12,5% 52,0% 11,8% 54,7% 11,2% 36,6% 10,7% 37,5% At least once a week Less than once a month 35,3% 32,9% 35,2% 47,7% 20,8% 23,7% 30,4% 15,1% 13,6% 43,9% 7,9% 8,3% 9,4% 4,1% 17,2% 6,4% 16,8% 19,2% 14,1% 6,9% 5,9% 35,7% 27,8% 19,9% 78,5% 4,5% 9,0% 27,6% 30,6% 24,3% 24,0% 11,5% 21,5% 11,9% 29,5% 22,6% 38,9% 12,8%

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30 Conclusions Create conditions for investment through accountable, capacitated institutions, certain regulatory environments and flexible policy frameworks Remove protectionist strategies, open markets to competition to meet pent up demand, while developing strategies for backbone investment Reduce vertically integrated entities producing anti-competitive behaviour and resource intensive access regulation Create enabling regulatory environments through removal of barriers to entry, service neutral licensing, cost-based \ (removal of artificial priced asymmetrical termination), prevention of abuse of market dominance Open access regime for optimal use of networks and facilities and spectrum to enable entrepreneurship and innovation Development of dedicated human capital strategies for sector institutions Targeted, competitively implemented universal services strategies rather than scattergun approach

31 Director - Prof. Alison Gillwald Benin - University of Benin-CEFRES - Dr. Augustin Foster Chabossou Botswana - University of Botswana - Dr. Patricia Masego Burkina Faso - Université de Ouagadougou - Dr. Pam Zohonogo Cameroon - University of Yaoundé II - Dr. Olivier Nana Nzépa Côte d'ivoire - University of Abidjan-CIRES - Prof Arsène Kouadio Egypt - American University in Cairo - Dr. Nagla Rizk, Ethiopia - University of Addis Ababa - Dr. Lishan Adam Ghana Science and Technology Policy Institute - Dr. Godfred Frempong Kenya - University of Nairobi - Prof. Dr Tim Waema Mozambique - Universidade Eduardo Mondhlane - Francisco Mabila Namibia - Namibian Economic Policy Research Unit - Dr. Christoph Stork Nigeria - University of Lagos - Prof. Dr. Ike Mowete Rwanda - National University of Rwanda - Albert Nsengiyumva Senegal CRES - Prof. Dr. Abdoulaye Diagne South Africa - University of Witwatersrand - Prof. Alison Gillwald Dr. Christoph Stork Tanzanian - Tanzania Communications Regulatory Authority - Dr. Ray Mfungayema Tunisia - - Dr. Farouk Kamoun Uganda - Makerere University - Dr. Nora Mulira Zambia - University of Zambia - Sikaaba Mulavu QuickTime and a decompressor are needed to see this picture.