Mobile telephony provides Africa with the additional economic growth that was experienced by OECD countries in the 80s by the deployment of fixed line telephony. Lower prices will increase access and usage and amplify this effect. A competitive ICT sector is the only recipe for low prices and high service delivery. Policy and regulatory environment are very important factors for establishing a competitive ICT sector

1. ICT for Development
ICT4D
Dr. Christoph Stork
1

2. researchICTafrica
Research network of universities and think
tanks in 20 African countries
No African
Year Research title
countries
2003 ICT Sector Performance Review 7
2004 Household e-Access & e-Usage Survey 11
2005 SME e-Access & e-Usage Survey 14
2006 ICT Sector Performance Review 17
Household e-Access & e-Usage Survey
2007 17
(with focus poverty and demand elasticities)
2

3. TOC
SME e-Access & Usage
(why ICT matters)
Access & Prices
(policy and regulation makes a difference)
Impact of Competition in Namibia
(how ICTs can help)
3

4. Small and Medium
Enterprise
e-Access & Usage
4

5. 5

6. BACKGROUND
• Aims:
• Looking at the impact of ICTs,
• Identifying obstacles and
• Providing guidance for policy recommendations
• SME sector is the sector in which most of the world’s
poor are working and it contributes significantly to
economic growth and employment
• No random sampling: qualitative interviews, 3967 SMEs
across 14 countries, 280 each
• Intensive training of enumerators for them to understand
every single participating business
6

7. Distinguishing by formality
• Form of ownership?
• Is your business registered with the Receiver
of Revenues? (pay taxes?)
• Is your business registered for VAT?
• How many of your employees have a written
employment contract?
• Does your business strictly separate
business from personal finances?
• Does your business keep financial records?
7

8. Access to ICTs by formality
Fixed Line Phones
100% Informal
Semi formal
80% Formal
60%
Internet Connection Mobiles
40%
20%
0%
Computer Fax
Post Box
8

9. ICT perceptions: ICTs are important
or very important!
Fixed Line Phones Don't have it
99%
Have it
61%
Internet Connection Mobiles
95% 41% 99%
71%
52% 31%
26%
Computer Fax
98% 95%
83%
Post Box
9

10. The more formal a SME is the more
ICTs it has and uses. Usage intensity is
the same (access/usage)
Formality N Mean Rank Chi-Square df Asymp. Sig.
Informal 1606 1275.4
ICT
Semi-formal 1234 2112.36
Possession 1327.61 2 0
Index Formal 1126 2852.24
Total 3966
Informal 1606 1361.15
ICT Usage Semi-formal 1234 2069.24
1034.54 2 0
Index Formal 1126 2777.19
Total 3966
Informal 1606 1989.19
ICT Usage
Semi-formal 1234 1962.71
Intensity 0.64 2 0.726
Index Formal 1126 1998.17
Total 3966
10

11. Turnover and ICT expenditure
= significantly and positively correlated
across sector!
Correlation coefficients that are significant at the 0.01 level
D: Manufacturing 0.483
F: Construction 0.808
G: Wholesale and retail trade; repair of motor vehicles, motorcycles and 0.736
personal and household goods
H: Hotels and restaurants 0.219
I: Transport, storage and communications 0.99
J & K: Financial intermediation & real estate, renting and business activities 0.544
M & N & O: Education, health, social work, other community, social and 0.905
personal service activities
11

12. Informal business operate
on a higher profit margin
Mean Chi- Asym
Ranks Formality N df
Rank Square p. Sig.
Informal 1590 2081.59
Profit Semi-
margin: 1230 1913
formal
after tax
26.051 2 0.000
profits Formal 1120 1875.94
divided by
turnover
Total 3940
12

13. Informal businesses are
more profitable
Mean Chi- Asym
Ranks Formality N df
Rank Square p. Sig.
Informal 1504 2020.61
Profitability:
after tax Semi-
1139 1761.75
profit formal
70.846 2 0.000
divided by
total fixed Formal 1048 1686.98
assets
Total 3691
13

14. Formal businesses have
higher labour productivity
Mean Chi- Asymp
Ranks Formality N df
Rank Square . Sig.
Labour
productivity:
Informal 1571 1546.48
Value added
(Sales minus Semi-
direct costs, 1223 1968.59
rent, water, formal
electricity etc.:) 479.988 2 0.000
divided by full- Formal 1114 2514.43
time employees
including owners
that manage the
business Total 3908
14

15. Formal businesses
re-invest more
Mean Chi- Asymp.
Ranks Formality N df
Rank Square Sig.
Informal 1559 1834.37
Re-
investment Semi-formal 1217 1908.94
rate: Invest
44.438 2 0.000
ment divided
by fixed Formal 1100 2118.79
assets
Total 3876
15

16. Turnover or Sales Model
F1 F2 F3 F4 F5 F6
= β1 + β 2 + β3 + β4 + β5 + β6 +ε
FA FA FA FA FA FA
F1= Turnover
F2= AVERAGE water, electricity, cost
F3= AVERAGE cost for your premises in terms of rent, land taxes
mortgage payments
F4= AVERAGE business expenditure on telephone calls, fax,
postage, Internet
F5= AVERAGE Wage Bill
F6= AVERAGE Direct Cost (raw materials and other intermediary
inputs or goods bought for resale)
FA=Total value of fixed assets
16

17. ICT expenditure contributes
significantly to higher sales
Robust regression of turnover function Formal Semi-formal Informal
N 1048 1139 1504
R Square 0.7775 0.9199 0.9481
F 74.39 208.58 193.52
Sig. For equation 0 0 0
Mean Variance
InflationFactor (VIF) 1.5 1.82 1.19
Unstandardized Coefficients
3.93 2.77 51.28
for ICT Usage Expenditure
Sig. of ICT Usage Expenditure 0.000 0.000 0.000
17

18. Labour Productivity
• V= Value Added
• W= AVERAGE Wage Bill
• ICTU= ICT Usage Index
• ICTP = ICT Possession Index
• EA=Full-time employees + owners that manage the business
• W/EA is hence the average wage and V/EA labour productivity
18

19. Access to ICTs is linked to
higher labour productivity
N R Square F Sig. Mean VIF
3908 0.5695 32.21 0 1.01
Unstandardized
t Sig. VIF
Coefficients
(Constant) -21836.49 -2.32 0.021
Average Wage 5.641971 7.75 0 1.01
ICT Possession Index 12284.54 2.6 0.009 1.01
19

20. Usage of ICTs is linked to
higher labour productivity
N R Square F Sig. VIF
3908 0.5701 30.69 0.0000 1.02
Unstandardized
t Sig. VIF
Coefficients
(Constant) -25785.1 -1.73 0.083
Average Wage 5.64 7.81 0 1.02
ICT Usage Index 7659.58 2.24 0.025 1.02
20

21. No doubt!
ICTs help SMEs to
become more profitable
21

22. Main Obstacle to ICT
adoption remains high cost
informal semi formal formal average
Network problems / unreliable infrastructure 11.3% 11.7% 10.5% 11.2%
Lack of financial resources 10.6% 4.5% 7.3% 8.0%
Lack of awareness & knowledge of ICTs 10.3% 8.4% 10.5% 9.7%
High cost, too expensive 55.6% 60.8% 58.8% 57.9%
Lack of skills & ICT illiteracy 2.8% 7.4% 6.9% 5.1%
No need 9.5% 7.2% 6.1% 8.0%
22

23. Conclusion Part 2
• Mobile phones are the most used tools in supporting
the running of SMEs
• Designing mobile financial applications to integrate
informal SMEs into the formal economy (for example
formal financial services) are promising avenues
• The main constraint to ICT usage remains high
investments and us age costs
• Hence, effective regulations and policies that enable a
competitive ICT environment will facilitate economic
growth, employment and social inclusion - in particular
for the poor
23

24. ICT Access & Prices
24

25. Access to fixed-line phones
2006 Fixed-line Subscribers per 100 inhabitants
South Africa 9.93
Botswana 8.75
Uganda 7.09
Namibia 6.84
Senegal 2.23
Ghana 1.48
Ivory Coast 1.40
Benin 1.02
Ethiopia 0.97
Burkina Faso 0.93
Kenya 0.84
Nigeria 0.82
Zambia 0.78
Cameroon 0.65
Tanzania 0.41
Mozambique 0.38
Rwanda 0.24
Source: ResearchICTafrica.net, (population based on IMF data)
25

26. Access to mobile phones
2006 Mobile Subscribers per 100 inhabitants
South Africa 68.15
Botswana 57.54
Cameroon 27.51
Namibia 26.86
Kenya 19.05
Nigeria 16.88
Mozambique 14.97
Tanzania 14.55
Senegal 14.49
Ghana 12.59
Benin 11.31
Zambia 9.30
Ivory Coast 8.22
Uganda 6.73
Burkina Faso 5.17
Rwanda 2.94
Ethiopia 1.15
Source: ResearchICTafrica.net, (population based on IMF data)
26

27. OECD Usage Baskets
Minutes or units Low User Medium User High User
Cell2Cell own Network Peak 6.91 15.60 39.48
Cell2Cell own Network Off Peak 3.60 7.49 12.50
Cell2Cell own Network Off Off Peak 3.17 7.49 17.11
Cell2Cell other Network Peak 4.32 10.08 27.72
Cell2Cell other Network Off Peak 2.25 4.84 8.78
Cell2Cell other Network OffOffPeak 1.98 4.84 12.01
Cell2Fixed Peak 3.17 6.83 16.80
Cell2Fixed Off Peak 1.65 3.28 5.32
Cell2Fixed Off Off Peak 1.45 3.28 7.28
SMS Peak 16.16 25.33 33.60
SMS Off Peak 8.42 12.16 10.64
SMS Off Off Peak 7.41 12.16 14.56
27

28. 2006 Mobile Nominal Usage Costs
2006 Low OECD User Basket - cost in US$ using nominal end of 2006 exhange rates
Nigeria 12.5
South Africa 10.9
Kenya 10.6
Côte d'Ivoire 10.2
Burkina Faso 9.7
Namibia 9.6
Cameroon 8.6
Zambia 7.9
Mozambique 7.6
Benin 7.4
Senegal 7.3
Uganda 7.3
Botswana 7.0
Ghana 6.5
Tanzania 5.8
Rwanda 5.6
Ethiopia 2.2
28

29. 2006 Mobile PPP Usage Costs
2006 Low OECD User Basket - cost in US$ using implied PPP conversion rates
Uganda 36.2
Mozambique 32.4
Ghana 30.8
Rwanda 30.5
Burkina Faso 29.2
Namibia 27.5
South Africa 27.2
Kenya 20.5
Nigeria 20.0
Botswana 18.4
Cameroon 18.4
Senegal 18.4
Côte d'Ivoire 17.9
Benin 16.3
Tanzania 14.3
Ethiopia 13.3
Zambia 11.6
29

30. 2006 Fixed-line Nominal Usage Costs
Cost of a local 1 minute call (peak rate)- cost in US$ using
end of 2006 nominal exchange rates
Burkina Faso 0.15
Côte d'Ivoire 0.12
Mozambique 0.12
Kenya 0.11
Tanzania 0.10
Cameroon 0.10
Uganda 0.10
South Africa 0.07
Rwanda 0.07
Senegal 0.06
Namibia 0.05
Ghana 0.05
Nigeria 0.05
Botswana 0.05
Zambia 0.05
Benin 0.04
Ethiopia 0.00
30

31. 2006 Fixed-line PPP Usage Costs
Fixed-Line: Cost of a local 1 minute call (peak rate)
cost in US$ using implied PPP conversion rates
Mozambique 0.49
Uganda 0.48
Burkina Faso 0.46
Rwanda 0.39
Tanzania 0.26
Ghana 0.25
Kenya 0.21
Cameroon 0.21
Côte d'Ivoire 0.21
South Africa 0.19
Namibia 0.16
Senegal 0.15
Botswana 0.13
Benin 0.09
Nigeria 0.08
Zambia 0.07
Ethiopia 0.02
31

32. 2006 Fixed-line Nominal Usage Costs
Cost of a local 3 minute call to US (peak rate)- cost in US$
using end of 2006 nominal exchange rates
Zambia 4.77
Burkina Faso 3.90
Ethiopia 3.42
Rwanda 3.00
Kenya 2.41
Namibia 2.20
Tanzania 2.14
Cameroon 1.81
Uganda 1.54
Benin 1.45
Botswana 1.15
Mozambique 1.02
Ghana 1.01
Senegal 0.90
Côte d'Ivoire 0.90
South Africa 0.52
Nigeria 0.35
32

33. 2006 Fixed-line PPP Usage Costs
Fixed-line: Cost of a 3 minute call to the US (peak rate)
cost in US$ using implied PPP conversion rates
Ethiopia 20.7
Rwanda 16.5
Burkina Faso 11.7
Uganda 7.7
Zambia 7.0
Namibia 6.3
Tanzania 5.3
Ghana 4.7
Kenya 4.7
Mozambique 4.3
Cameroon 3.8
Benin 3.2
Botswana 3.0
Senegal 2.3
Côte d'Ivoire 1.6
South Africa 1.3
Nigeria 0.6
33

34. Conclusion Access
• Access and usage varies considerably across Africa
• Usage costs vary equally
• Link between Tele-density and price is not straight
forward: GDP per capita, competition in the
sector, market structure, policies, regulation are all
important factors
34

35. Affect of
Competition in
Namibia
35

36. Nominal Prices
Nominal cost of OECD Usage Baskets in N$
Cheapest MTC September 2005
Cheapest MTC October 2007 296
Cheapest Switch October 2007
Cheapeast Cell One October 2007 250
228
210
174
147
101 106
83
70
48 51
Low User Medium User High User
36

37. Real Prices
Real cost of OECD Usage Baskets in N$ (September
2005 prices)
Cheapest MTC September 2005
Cheapest MTC October 2007 296
Cheapest Switch October 2007
Cheapeast Cell One October 2007
221
202
186
174
130
89 94
83
62
43 45
Low User Medium User High User
37

38. Price Change MTC
MTC price change compared to September 2005
nominal prices real prices (in Sep 2005 prices)
85% 85%
84%
75% 75% 75%
Low User Medium User High User
38

39. Price Change of Cheapest overall
Overall price change (cheapest available in
Namibia) compared to September 2005
nominal prices real prices (in Sep 2005 prices)
71%
63%
58% 58%
52% 51%
Low User Medium User High User
39

40. Conclusion
• Mobile telephony provides Africa with the additional
economic growth that was experienced by OECD
countries in the 80s by the deployment of fixed line
telephony.
• Lower prices will increase access and usage and
amplify this effect.
• A competitive ICT sector is the only recipe for low
prices and high service delivery.
• Policy and regulatory environment are very
important factors for establishing a competitive ICT
sector
40