ICT Sector Indicators - Home - Wits University · Development agreed set of 41 core indicators (2006), viz: – ICT infrastructure and access (11 indicators) – Access to, and use

1

ICT Sector IndicatorsICT Sector Indicators

What are we measuring?What are we measuring?

P&DM Wednesday Conversation,P&DM Wednesday Conversation,13 August 200813 August 2008

Charley Lewis, LINK CentreUniversity of the Witwatersrand, Johannesburg, South Africa

Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

Session RoadmapSession Roadmap

• Indicators & the ICT Sector• Fixed Line Teledensity• Mobile Teledensity• Internet users• ITU’s ICT Opportunity Index

2


ICT SectorICT Sector

Statistics Statistics &&

IndicatorsIndicators


South Africa in 2007 hadSouth Africa in 2007 had……Economy• 48 million inhabitants• GDP = $ 283 billion • GDP / capita = $ 5 724 ($ 10 600 PPP)• GINI coefficient = 57,8Fixed telephony• 4,6 million fixed lines (50% residential) = 9,8% fixed line teledensity• 2 fixed line operators (?)Mobile telephony• 42 million mobile subscribers (2007) (mostly prepaid) = 89% mobile teledensity• 3 mobile operatorsPCs & the Internet• 3,8 million Internet users (2007)• 658 000 broadband subscribers

– (100% growth since 2006) (ADSL subscribers = 58%)• 5,3 million PCs• 255 ISPsRadio & TV• 7 million households with TV (60%), 10 million with radio (80%)• 6 TV stations• 130 radio stations

3


Why Measure the ICT Sector?Why Measure the ICT Sector?

• Monitor sector trends & growth patterns– cf SA Telecomms Sector Performance Review– cf Millenium Development Goal 8(g)

• Determine contribution of ICT towards:– Economic growth (ICT infrastructure as business enabler)– Social development (‘Digital divide’, Universal Access,

ICT4D, gender etc)• Assess impact of policy & regulation

– eg Universal Service & Access targets• Guidance for policy formulation & regulatory

intervention • Benchmarking (SA vs ??)• Quantify digital divide


Sources of Statistics & Sources of Statistics & IndicatorsIndicators

• ITU database– 105 separate data categories– 214 countries– currently has data from 1960 – 2007– Emphasis on physical infrastructure (supply side)– Other sources of data: UN, UNCTAD, UNDP, World Bank,

OECD • ICT Indices

– ICT Opportunity Index (ITU) (SA=90/183 2007)– E-readiness (Economist) (SA=39/70 2008)– Knowledge Economy & Knowledge Indexes (World Bank)

(SA=51/132 53/132 2008)– Networked Readiness Index (World Economic Forum)

(SA=51/127 2008)

4


ITU Database containsITU Database contains……


IndicatorsIndicators

• UN Partnership for measuring ICT for Development agreed set of 41 core indicators (2006), viz:– ICT infrastructure and access (11 indicators)– Access to, and use of, ICT by households and

individuals (14 indicators)– Use of ICT by businesses (12 indicators)– ICT sector and trade in ICT goods (4 indicators)(Basic core + extended core + reference)

(see ITU (2006) Core ICT Indicators, available online at

www.itu.int/ITU-D/ict/partnership/material/CoreICTIndicators.pdf)

5


LetLet’’s look at a few of theses look at a few of these

• Fixed teledensity– (A1 - Fixed telephone lines per 100 inhabitants)– Collected by 193 countries (ITU, 2004)

• Mobile teledensity– (A2 - Mobile cellular subscribers per 100 inhabitants)– Collected by 202 countries (ITU, 2004)

• Internet users – (A4 - Internet subscribers per 100 inhabitants)– Collected by 195 countries (ITU, 2004)

• ITU’s Digital Opportunity Index


Fixed Line Fixed Line TeledensityTeledensity

6


Fixed Line TeledensityFixed Line Teledensity

• A1: Fixed telephone lines per 100 inhabitants– Fixed telephone lines refer to telephone lines

connecting a customer’s terminal equipment (eg telephone set, facsimile machine) to the public switched telephone network (PSTN) and which have a dedicated port on a telephone exchange.

– Fixed telephone lines per 100 inhabitants is calculated by dividing the number of fixed telephone lines by the population and multiplying by 100.

Source: ITU, 2006

SA: Fixed Lines SA: Fixed Lines (1997-2008)

4 259 000

4 645 000

5 075 000

5 493 000

4 962 000 4 924 000 4 844 000 4 821 000 4 725 000 4 708 000 4 642 0004 532 000

0

1 000 000

2 000 000

3 000 000

4 000 000

5 000 000

6 000 000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Fixed LineFixed LineTeledensityTeledensity

= 9,5%= 9,5%

Fixed LineFixed LineTeledensityTeledensity= 12,8%= 12,8%

7


Fixed Line Teledensity Fixed Line Teledensity as an Indicatoras an Indicator

• Historically easy to derive & calculate• Provides simple basis of comparison• Understates number of fixed telephony subscribers• Tells us “more about the history of the national telecom sector

than about its future” (Jensen & Mahan, 2007)• Problems of inclusion

– ISDN (SA 16%); Payphones (SA 3%); ADSL (SA n/a)• Problems of disaggregation

– Geography, gender, race, income• Problems of convergence

– Is WLL fixed or mobile? (eg Neotel’s CDMA2000)• Problems of bias

– No of business users (50% in SA vs 27% worldwide) obscures individual access

• But fixed infrastructure is basis for broadband, triple/multi-play


Household Access may be a better measureHousehold Access may be a better measure

Percentages of Households with TelephonesPercentages of Households with Telephones(by district, 2003)

Source: Tlabela et al, HSRC, 2006

National Avg= 23,6%

8


Access Overlaps with PovertyAccess Overlaps with PovertySA: Gini Coefficient (by district, 2001)

Source: Craig Schwabe, HSRC

< 0.223

0.224 - 0.597

0.598 - 0.669

0.670 - 0.725

0.726 - 0.819


Fixed Line Household AccessFixed Line Household Access

Source: LINK Centre, 2008Research ICT Africa Household Survey

Prepaid fixed telephone at home:= 35,5% (LINK Centre Survey)= 32,5% (Telkom Annual Report)

9


Fixed Line Household AccessFixed Line Household Access

Source: LINK Centre, 2008Research ICT Africa Household Survey


Disaggregation of Statistics by Disaggregation of Statistics by Race Remains Important for SARace Remains Important for SA

South Africa: Percentage of households with either a fixed line or cell phone in the household

Source: Stats SA

10


Mobile Mobile TeledensityTeledensity


Mobile TeledensityMobile Teledensity

• A2: Mobile cellular subscribers per 100 inhabitants• Mobile cellular subscribers refer to users of

portable telephones subscribing to an automatic public mobile telephone service using cellular technology, which provides access to the PSTN.

• Users of both post-paid subscriptions and pre-paid accounts are included.

• Mobile cellular subscribers per 100 inhabitants is obtained by dividing the number of mobile cellular subscribers by the population and multiplying by 100.

Source: ITU, 2006

11

SA: Mobile SubscribersSA: Mobile Subscribers(1999 (1999 –– 2007)2007)

0

5 000 000

10 000 000

15 000 000

20 000 000

25 000 000

30 000 000

35 000 000

40 000 000

45 000 000

1999 2000 2001 2002 2003 2004 2005 2006 2007

Cell C Vodacom MTN

MobileMobileTeledensityTeledensity= 88,9%= 88,9%

4 800 000

23 004 000

14 799 000


Mobile Teledensity Mobile Teledensity as an Indicatoras an Indicator

• Easy to derive & calculate• Provides simple basis of comparison• Provides good estimate of personal access to

telecomms services• Overstates number of fixed telephony subscribers

– By how much??• Problems of comparability

– Different operators use different definitions for “subscriber”• Proposals to use “Effective Teledensity “ or “Total

Teledensity”

12


What is a Mobile Subscriber?What is a Mobile Subscriber?• Mobile subscriber = active SIM card• What is an “active SIM card”?• Cell C

– “Made or received a call or recharged” in the last 3 months– Includes Virgin Mobile subscribers

• MTN– “Made or received a revenue-generating call” in last 90 days

• Vodacom– SIM card with “revenue-generating activity” in the last 3 months– Excluded voice-mail in June 2006 (much unretrieved)– Led to deletion of 3 million “active customers”

- inactive >215 days– Re-included voice-mail from Sept 2006

• Figures are in annual reports (except Cell C – press releases)• Problems of date comparability

– Cell C & Vodacom report as at 31 December, MTN as at 31 March


Active SIM Cards & CustomersActive SIM Cards & Customers

• Goldstuck (2005) estimates 20% - 30% over-reporting in SA due to:– Recharge arbitrage (using & discarding starter packs)– Dual contracts (13% of upper income subscribers)– Churn (customers moving networks)

• Sutherland (2008) estimates 17% global over-reporting– eg Bulgaria has 133% mobile teledensity (2007)– But 2006 household survey reports 53% penetration– Accounted for by multiple SIM card ownership &– Cross border movements (tourism, economic migrants etc)

13


Duplicate SIM cardsDuplicate SIM cards

11% of SA sample reportowning 2 or more SIM cards


Total duplicate SIM cardsTotal duplicate SIM cards

14


But thereBut there’’s mores more……

• Substantial numbers of SIM cards used in value-added services– Vehicle tracking devices

• Netstar = 440 000 (2007); Raptor; C-track…

– PABX Least-cost routers– 3G data access = 450 000 (2007)

• Impossible to quantify without detailed investigation


% of Households with Mobile Telephony% of Households with Mobile Telephony(by district, 2003)

Source: Tlabela et al, HSRC, 2006

RIA! data= 62% (2007)

National Avg= 33,1%

15


Internet Internet UsersUsers


Internet UsersInternet Users

• A4: Internet subscribers per 100 inhabitants• An Internet subscriber is someone who pays for

access to the public Internet (a TCP/IP connection)

• The statistic is measured irrespective of the type or speed of access, the type of device used to access the Internet, or the method of payment

• Internet subscribers per 100 inhabitants is obtained by dividing the number of Internet subscribers by the population and multiplying by 100

Source: ITU, 2006

16

SA: Internet Users SA: Internet Users (1996 (1996 –– 2007)2007)

0

500000

1000000

1500000

2000000

2500000

3000000

3500000

4000000

4500000

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Corporate users Dialup subscribers Academic Broadband

1 980 000

908 000

550 000

420 000

Total = 3 858 000 or 8,1% (2007)

ITU (2007) = 3 966 000 / 8,2%

Source: Goldstuck, 2007

The death of the dialThe death of the dial--up subscriberup subscriber

Source: Goldstuck, 2007

17


Internet Users Internet Users as an Indicatoras an Indicator

• Difficult to derive & calculate• Requires survey + extrapolation• Goldstuck’s methodology respected but open to

challenge– Broadband - operator data of subscriptions– Dial-up subscribers - ISP survey + extrapolation– Corporate users - no of leased lines + estimated 110

users per leased line– Academic users - guesstimate

• Each broadband & dial-up subscription multiple users

• But each user may have multiple access paths (at home, at work…)


18


Where do you use the Internet?Where do you use the Internet?


19


What do you using email for?What do you using email for?


Measuring the Measuring the Digital Divide:Digital Divide:

ICT Opportunity IndexICT Opportunity Index

20


ITUITU’’s ICT Opportunity Indexs ICT Opportunity Index• Attempts to track complex socio-economic role &

impact of ICTs• Based on InfoStates conceptual framework

(Sciadas, 2005) - Info-density & Info-use• Succeeds ITU’s Digital Access Index & Digital

Opportunity Index• Link to Millennium Development Goals • Tracks both ICT supply & ICT demand• Allows country cross comparison & progress

tracking• Some caveats:

– Statistical divide– Simplistic reliance on statistical indicators


ITUITU’’s Digital Opportunity s Digital Opportunity Index (DOI)Index (DOI)

21


ICT Supply & ICT DemandICT Supply & ICT Demand

22


Indicators & Clustering Indicators & Clustering

ITU Digital Opportunity Index 2006ITU Digital Opportunity Index 2006

23


High & low performersHigh & low performers(2001 (2001 –– 2005)2005)


Issues with ICT IndexesIssues with ICT Indexes

• Many are based on multiple indicators– ITU’s ICT Opportunity Index = 10– Harvard’s Network Readiness Index = 45– EIU’s E-readiness Index = 100

• Many indicators are of questionable accuracy• Some indicators are subjective• Problems with weighting and duplication

– Factor analysis? • Problems with correlation & causality

– eg only tertiary education correlates with ICT adoption (RIA!, 2008)

• Most only track readiness for ICT or adoption of ICT• How to track the impact of ICTs?

24

Proposal for an African eProposal for an African e--IndexIndex


Thank youThank you……

……questions????questions????

http://link.wits.ac.za [email protected]

Documents

ICT Sector Indicators - Home - Wits University · Development agreed set of 41 core indicators (2006), viz: – ICT infrastructure and access (11 indicators) – Access to, and use