ICT as a tool of development

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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

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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How does technology play a part in development? ICTs and 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

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Estimates of increased mobile broadband could add $400billion annually to GDP

and create 10million jobs

(Mckinsey)

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)

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

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Problems with evidence

‣  Unevenness of indicators, reflection of uneven development (self perpetuating, vicious or virtuous cycle).

‣  Assumptions behind global indicators and indices reflect the political economy of mature economies and democracies of the North.

‣  Very different access and use trajectories in Global South make some standard indicators meaningless and others very difficult to gather.

‣  What are the underlying data sources and how effective are they?

‣  Case of pricing/affordability

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Whose evidence and who sets the agenda?

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  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.

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RIA - Lifting the veil on ICT gender indicators indindndicatorsstatistics

Where do indicators come from?

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No good and bad indicators, just some measure somethings better than others

ICT indicators

‣  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.

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Problems with data

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Up to a two line subtitle, generally used to describe the takeaway for the slide

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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)

‣  ICT Readiness (infrastructure, access)

‣  ICT Intensity (use)

‣  ICT Capability (skills)

ICT Development Index (IDI)

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Share of households with fixed-lines

18,2%

17,4%

11,0%

7,6%

2,6%

2,3%

1,8%

0,9%

0,3%

0,1%

18,0%

11,5%

15,0%

4,0%

1,8%

0,6%

2,2%

0,4%

1,5%

0,2%

0,3%

South Africa

Namibia

Botswana

Ethiopia

Ghana

Kenya

Cameroon

Tanzania

Uganda

Rwanda

Nigeria

2007/8 2011/12

Fixed-lines on the way out except Botswana,

Cameroon, Uganda and Rwanda

Share of households with a working computer

24,5%

15,7%

14,7%

12,7%

8,6%

8,5%

6,6%

2,2%

2,0%

1,6%

0,7%

South Botswana

Namibia Kenya

Cameroon Ghana Nigeria

Uganda Rwanda Tanzania Ethiopia

Share of households with a working Internet connection

19,7%

12,7%

11,5%

8,6%

3,4%

2,7%

1,3%

0,9%

0,8%

0,7%

0,5%

South Kenya

Namibia Botswana

Nigeria Ghana

Cameroon Uganda

Tanzania Rwanda Ethiopia

Less than a quarter of households have a computer and even fewer Internet access

Where was the Internet used first?

82,1%

70,8%

70,6%

70,5%

68,9%

65,1%

50,1%

45,8%

45,2%

33,3%

28,2%

17,9%

29,2%

29,4%

29,5%

31,1%

34,9%

49,9%

54,2%

54,8%

66,7%

71,8%

Cameroon

Rwanda

Botswana

Ghana

Kenya

South

Namibia

Tanzania

Nigeria

Ethiopia

Uganda

Computer Mobile phone

Where the Internet was used in past 12 months

30% 61% 64% 71% 71% 75% 75% 78% 81% 81% 87% 10%

35% 51% 36% 52% 45% 29% 31% 17% 55% 48%

0,201

0,509 0,322 0,209

0,307 0,244 0,196

0,388 0,209

0,512 0,36

0,8

0,847 0,583

0,325

0,502 0,628 0,451

0,724

0,422

0,74

0,225

Cam

eroo

n

Gha

na

Bots

wan

a

Sout

h Af

rica

Rw

anda

Tanz

ania

Nig

eria

Ken

ya

Ethi

opia

Uga

nda

Nam

ibia

Mobile phone Work Place of education Internet cafe

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Broadband issues

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: off-

net/on-net ratio depends on market share ‣  Only dominant operators - new entrants and

small operators are likely to be price challengers

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OECD Basket Methodology

Comparing Countries

Comparing Operators

Comparing Products

‣  Comparing the difference between

-  cheapest in country - cheapest from dominant operators

-  cheapest in country - cheapest from most expensive operator

‣  Comparing cheapest product available from

-  dominant operators -  cheapest operator -  most expensive operator

‣  Benchmarking

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

South Africa pricing trends

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  OECD basket price in rands for South Africa

And the cost of data?

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Prepaid data (USD)

Cheapest 1GB price from operator with dominance in country!

Cheapest operator 1GB price in country!

4,4 4,4 5,2

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

35,0 37,7

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

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

Tanzania Kenya

Rwanda Mozambique

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 Swaziland

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%...

‣  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://

‣  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

‣  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

‣  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

‣  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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South Africa data price 1

GB(

ZAR)

0

50

100

150

200

Q1 201

4

Q2 201

4

Q3 201

4

Q4 201

4

Q1 201

5

Q2 201

5

Vodacom MTN Cell C Telkom MobileVirgin Mobile

And the cost of data?

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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%...

‣ 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://

‣ 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

‣ 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

‣ 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

‣ 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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