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Broadband in Africa
Where are we and where are we going ?
CITPO, InfoDev, AICD
Mark Williams
January 27, 2010
Investment into privately-owned operators has driven
network expansion
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
US
$b
n
East Asia and Pacific Europe and Central Asia
Latin America and the Caribbean Middle East and North Africa
South Asia Sub-Saharan Africa
*Excludes China
Investment into privately-owned
operators has driven network expansion
Advent of mobile competition
0
10
20
30
40
50
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
>2 operators
Duopoly
Monopoly
No network
Mobile competition, number of countries with:
Investment has been driven by rapid
market reforms
Network coverage has expanded dramatically
8%
67%
56%
86%
21%
91%90%
99%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1999 2001 2003 2005 2007 2009
% p
op
ula
tio
n c
overa
ge
LIC LMC UMC HIC
Mobile network coverage has expanded
dramatically
Mobile growth in Africa has been
exponential but…
0%
10%
20%
30%
40%
50%
60%
70%
-
20
40
60
80
100
120
140
160
180
200
2000 2001 2002 2003 2004 2005 2006 2007
Mill
ion
s
Nigeria
South Africa
Others
Annual growth
6
…broadband in Africa remains
very expensive
0.0
50.0
100.0
150.0
200.0
250.0
300.0
North America LAC North Africa ECA Sub-Saharan
Africa
US
$ p
er
10
0kb
it/s
(2
00
6)
Broadband in Africa is
currently very expensive
Internet usage remains very low
-
2
4
6
8
10
12
14
16
18
20 A
ng
ola
Be
nin
Bo
tsw
an
aB
urk
ina
Fa
soB
uru
nd
iC
am
ero
on
Ca
pe
Ve
rde
Ce
ntr
al …
Ch
ad
Co
mo
ros
Co
ng
oC
on
go
, D
.R.
Co
te d
'Iv
oir
eD
jib
ou
tiE
qu
ato
ria
l …E
ritr
ea
Eth
iop
iaG
ab
on
Ga
mb
iaG
ha
na
Gu
ine
aG
uin
ea
-Bis
sau
Ke
ny
aL
eso
tho
Lib
eri
aM
ad
ag
asc
ar
Ma
law
iM
ali
Ma
uri
tan
iaM
au
riti
us
Mo
zam
biq
ue
Na
mib
iaN
ige
rN
ige
ria
Rw
an
da & …
Se
ne
ga
lS
ey
ch
ell
es
Sie
rra
Le
on
eS
om
ali
aS
ou
th A
fric
aS
ud
an
Sw
azi
lan
dT
an
zan
iaT
og
oU
ga
nd
aZ
am
bia
Zim
ba
bw
e
Internet users per 100 people
Africa
SSA
North Africa
8
Policy attention is shifting to broadband:
What are we aiming for ?
Widely available
(50%+ of the
population can
access it
<$15 per month
Pre-payment
systems
Shared access
models (e.g.
through internet
cafes, educational
institutions)Private-sector
aggressively
marketing services
in a competitive
market
Wireless last-mile
infrastructure
Fiber backbone
infrastructure
Competition
between
infrastructure
providers
Policy questions
• What will it take to get low-cost access to broadband
in Africa ?
o How far is the successful voice policy model applicable to
broadband ?
o Is public support for broadband needed?
o What is the right policy mix?
• What can we learn from other regions about
appropriate policies for Africa ?
o Regulatory reforms
o Competition
o Targeted public intervention
9
How far will the market drive broadband
coverage ?
10
Modeling analysis based on Regulatel
methodology
Highest revenue potential
Lowest revenue potential
Lowest cost per subscriber
DEMAND
SUPPLY
Highest cost per subscriber Universal Coverage Gap
Sustainable Coverage Gap
Coverage Gap
Efficient Market Gap
Existing Coverage
• Spatial modeling using geo-coded data on network coverage, geo-type,
population density, income distribution
• Data: GSMA coverage database, GRUMP, Pyramid cost data
Spatial modeling process
• Identify uncovered areas, divide into cell-sized grid
• Estimate cost and revenue for each cell
PopulationSuperimposed grid
defining cell sites in
uncovered areas
GSM
coverage
Modeling parameters
Parameter Value or definition Source
Capital costs (capex) $167,000 per cell site in 2005, declining by an average of 2.1
percent per year.
Winrock International /
Pyramid Research
Operating costs (opex) $50,000 per cell site per year, plus diesel fuel costs. Fuel costs
are not included in the baseline scenario but can be explored in
the user-input sensitivity analyses.
Winrock International /
Pyramid Research
Size of cell sites Rural = Up to 1,662 square kilometers (km2) (radius of 23 km)
Urban = 4 or 8 km2 (radius of 1.1–1.6 km)
Winrock International /
Pyramid Research
Terrain factor (rural
areas only)
An integer factor ranging from 1 to 4 that is used to adjust the
number of base stations per cell site based on terrain. The
factor is calculated based on the percentage of raster cells with
unobstructed line of sight to a centrally located high point in the
cell site representing a hypothetical antenna position.
Winrock International /
Pyramid Research. Line of
sight analysis was conducted
using SRTM digital elevation
data at 90m resolution.
GRASS GIS software was
used.
Revenue potential 4 percent of gross domestic product (GDP) per capita, weighted
for urban and rural income distribution. Where data is available,
revenue potential is reduced by applicable VAT and excise taxes
as identified in Minges (2007).
World Bank review team,
Winrock International /
Pyramid Research, Minges
(2007)
Results: GSM is profitable for 92% of the
population in Africa
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Central African Republic
Liberia
Congo-DRC
Madagascar
Eritrea
Zambia
Mauritania
Djibouti
Gambia, The
Congo, Republic
Niger
Mozambique
Zimbabwe
Sao Tome and Principe
Chad
Mali
Guinea
Sierra Leone
Botswana
Namibia
Lesotho
Tanzania
Ethiopia
AFRICA
Cameroon
Libya
Gabon
Cape Verde
Burkina Faso
Malawi
Sudan
Burundi
Togo
Kenya
Senegal
Algeria
Angola
Cote d’Ivoire
Benin
Ghana
Swaziland
Uganda
Morocco
Egypt
Rwanda
Nigeria
South Africa
Comoros
Equatorial Guinea
Mauritius
Seychelles
Tunisia
Percent of Population
Existing Coverage Efficient Market Gap Coverage Gap
• Overall coverage gap for Africa (51 countries) is 8% of the population
• Wide variety in extent of gap: Mauritius = 0% gap, CAR = 53%
Cost of extending networks
763.3
105.9
966.8
238.2
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Sub-Saharan Africa North Africa
US
$ m
illi
on
p
er y
ea
r
Efficient market gap Coverage gap
• Although coverage
gap is small, it is
expensive to fill
because of low
population density
• Total amount is
c.US$1.2bn/year
Broadband modeling assumptions
Parameter Value or definition Source
Type of coverage Outdoor Winrock International / Pyramid
Research, Alvarion
Capex $20,25,000 per 4-sector WiMax 802.16d cell site (single radio per sector)
$12,97,000 per single-sector WiMax 802.16d cell site
$216,000 per CDMA 450 1x EV-DO cell site
$450 per subscriber for outdoor coverage customer premise equipment (CPE)
(including installation)
Winrock International / Pyramid
Research, Alvarion
Opex $50,000 per cell site per year Winrock International / Pyramid
Research
Size of cell sites Rural = 5,024 square kilometers (km2) (radius of 40 km)
Urban = 78.5 km2 (radius of 5 km)
Ho 2005, Seybold 2006, Alvarion
Terrain factor An integer factor ranging from 1 to 4 that is used to adjust the number of base stations
per cell site based on terrain. The factor is calculated based on the percentage of
raster cells with unobstructed line of sight to a centrally located high point in the cell
site representing a hypothetical antenna position.
Winrock International / Pyramid
Research. Line of sight analysis was
conducted using SRTM digital elevation
data at 90m resolution. ESRI ArcGIS
9.2 software was used.
Subscriber
penetration
One broadband connection per 100 urban inhabitants plus one broadband connection
per 400 rural inhabitants
Winrock International / Pyramid
Research
Revenue potential 1 percent of GDP per capita, weighted for urban and rural income distribution. Where
data is available, revenue potential is reduced by applicable VAT and excise taxes as
identified in Minges (2007).
Winrock International / Pyramid
Research, Minges (2007)
Market will deliver a low-cost, low-quality,
public access model
Figure 2.9 Broadband coverage gap analysis
Source: Winrock International / Pyramid Research.
0% 20% 40% 60% 80% 100%
Congo-DRC
Liberia
Central African …
Guinea-Bissau
Gambia, The
Zimbabwe
Madagascar
Guinea
Eritrea
Djibouti
Mozambique
Zambia
Mauritania
Niger
Mali
Namibia
Chad
Congo, Republic
Burundi
Malawi
Lesotho
Botswana
AFRICA
Sierra Leone
Tanzania
Gabon
Cameroon
Ethiopia
Seychelles
Libya
Cape Verde
Burkina Faso
Sao Tome and …
Senegal
Angola
Comoros
Kenya
Sudan
Cote d’Ivoire
Algeria
Benin
Uganda
Togo
Morocco
Ghana
Rwanda
South Africa
Egypt
Nigeria
Tunisia
Equatorial Guinea
Mauritius
Swaziland
Percent of Population
Efficient Market Frontier Coverage Gap
86% of the population would gain access to broadband through this model of public internet access points
Would require $3.6 billion in up-front capital investment plus $454.4 million per year in operating expenses
A more ambitious policy objective would
require more assertive public support
• Modeling strategy:
o Assume target penetration rates (urban and rural)
o Assume ARPUs
o Calculate profitability/subsidy requirement by cell
o Test impact of assumptions
•Key assumptions:
o Wimax/CDMA networks
o Partial infrastructure sharing
o International = current costs
o Cost of capital = 20%
o 10 year modeling horizon
18
Total subsidy requirements for mass-market
broadband penetration
19
$.0
$.5
$1.0
$1.5
$2.0
$2.5
$3.0
$3.5
$4.0
$4.5
$5.0
To
tal su
bsid
y r
eq
uir
em
en
t N
PV
(U
S$b
n)
ARPU = $10.00 per month ARPU = $5.00 per month
Urban penetration rate =
20%, rural penetration rate =
10%
Total revenue = 2.7%/1.4%
of GDP
International connectivity
prices = $2000/Mbps
International bandwidth prices have a major
impact on financial viability
20
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
20%/10% 10%/5% 5%/2%
To
tal s
ub
sid
y r
eq
uir
ed
NP
V (
US
$b
n)
Penetration rate (Urban/Rural)
International bandwidth = US$2000/Mbps International bandwidth = $400/Mbps
Model for Ghana
ARPU = $5 per month
Backbone networks
21
22
Broadband supply-chain
International
connectivity
Domestic
backbone
Switching/
Routing
Access
Retail
services
Connection to the rest of the world,
provided by satellite or fiber-optic
cable (usually submarine)
Carries traffic between fixed points within a
network. Provided by satellite, microwave
or fiber-optic cable
The ‘intelligence’ in the network, ensuring
that communications traffic is sent in the
right direction
Link between the customer and the network.
Usually xDSL or cable networks. In Africa,
wireless is used (where it exists)
All the ‘soft’ inputs required (e.g. sales,
customer care, billing etc.)
Regional
connectivity
Connection from the border to the nearest
connection to the rest of the worldBackbone
newtorks could
be a major
constraint on
market
development
Rapid market
entry is easing
infrastructure
constraints
23
Broadband supply-chain
International
connectivity
Domestic
backbone
Switching/
Routing
Access
Retail
services
Connection to the rest of the world,
provided by satellite or fiber-optic
cable (usually submarine)
Carries traffic between fixed points within a
network. Provided by satellite, microwave
or fiber-optic cable
The ‘intelligence’ in the network, ensuring
that communications traffic is sent in the
right direction
Link between the customer and the network.
Usually xDSL or cable networks. In Africa,
wireless is used (where it exists)
All the ‘soft’ inputs required (e.g. sales,
customer care, billing etc.)
Regional
connectivity
Connection from the border to the nearest
connection to the rest of the world
Backbone
newtorks could
be a major
constraint on
market
development
Why are fiber backbones important ?
24
0.4 0.2 0.2
24.9
151.2
98.1
249.1
0
50
100
150
200
250
300
PSTN+WLL mobile narrowband access
broadband access
PSTN+WLL narrowband access
broadband access
ba
ck
bo
ne
ba
nd
wit
dth
pe
r u
se
r (k
bp
s)
Residential users Corporate users
25
Is fiber different from wireless telecoms
infrastructure?
0
200
400
600
800
1000
1200
100 200 300 400 500 600 700 800 900 1000
long
-run m
arg
ina
l cost of
capacity (
US
D$)
capacity (Mbps)
optical fiber microwave
Extending the backbone networks
in Burkina Faso
26
Peripheral areas are much more expensive to
serve than urban routes
27
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Traffic (Mbps) Long-run cost (US$/Mbps/month)
No
rma
lize
d c
os
t
core network periphery network
There is a lot of fiber backbone in Africa
28
Developing in from the
coasts
Growing rapidly
Very variable between
countries
There is a lot of fiber backbone in Africa
29
Developing in from the
coasts
Growing rapidly
Very variable between
countries
South Africa has almost
twice as much fiber as
the rest of SSA combined
There is a lot of fiber backbone in Africa
30
Developing in from the
coasts
Growing rapidly
South Africa has almost
twice as much fiber as
the rest of SSA combined
East Africa & Nigeria
have the fastest growing
fiber networks in the
region
Very variable between
countries
‘000 km of fiber optic
network
31
154.0
4.3
80.2
36.6
South Africa (operational) South Africa (under construction)
Rest of SSA (operational) Rest of SSA (under construction)
The regional pattern of backbone network
development is evolving rapidly
South Africa has most of the
region’s fiber but it is not
growing as quickly as in other
countries
32
0%
50%
100%
150%
200%
250%
300%
350%
400%
450%
-
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
Fibre under construction (kms) Fibre under construction as % of operational fibre
Wide variations in fiber network length
and growth rates across the region
33
Development of terrestrial and
submarine fiber are closely linked
34
Development of terrestrial and
submarine fiber are closely linked
Terrestrial network
development is linked to
landing points for
submarine cables
The pattern of ownership of fiber networks is
also evolving
35
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
50.0%
Private telecommunications
operator
Privatised telecommunications
operator
State-owned telecommunications
operator
State-owned electricity company
Government-owned
Operational Under construction
*SSA excluding South Africa
Market dynamics of fiber backbone
networks in Africa
Kenya: mixture of public and private
network competition
37
Competitive
privately-funded
routes
Non profitable
routes
Government-funded fiber
network reaching rural
areas
Zambia: 2 SOEs with national fiber networks
competing with each other
Zambia: 2 SOEs with national fiber networks
competing with each other
Government recently announced it is giving
control of ZESCO’s fiber to Zamtel to create
monopoly in order to raise privatization sale
value of Zamtel
Policy on backbone networks
40
41
Policy recommendations
• Governments can do a lot to stimulate infrastructure
competition
o Remove restrictions on infrastructure competition
o Provide cheap/free access to public infrastructure
o Reduce investment risk
o Aggregate service demand from public institutions
• Outside of main cities and trunk routes, public
support to backbone networks will be needed. Three
basic models are available:
o Competitive subsidies
o Shared infrastructure
o Incentive-based private-sector models
Remove restrictions on
backbone infrastructure competition
42
• What does this involve ?
o Remove restrictions on wireline network development
(Tanzania, Republic of Congo, Sudan)
o Remove restrictions on wholesale (Mozambique)
o Encourage entry through carrier licenses (Nigeria)
o Rights of way (?)
• Challenges
o Protection of incumbents
o Boosting privatization valuations
o Protecting existing private operators with explicit or implicit
exclusivity arrangements
o Collusion between operators
Provide cheap/free access to
public infrastructure
•What does this involve ?
o Types of infrastructure: electricity, pipelines, railways,
sewers
o Giving rights of way alongside roads to lay fiber
•Challenges
o Security – access by third party is almost impossible
o Revenue raising by parastatals or local authorities make this
difficult
o Some countries pass laws to limit revenue-raising by local
authorities
43
Reduce investment risk and
aggregate public demand
•What does this involve ?
o Risk guarantees
o Clearer licensing commitments
o Arbitration arrangements
o Government equity investments
o Government is often the biggest client so pooling this
demand into a single contract may help reduce transaction
costs.
•Challenges
o Risk guarantees are difficult and expensive
o Some governments are doing the opposite – extracting more
rents from the sector through taxes, license-fees and
relicensing ‘ransom’
o Pooling of government demand into single contract may
leave supplier vulnerable to non-payment (chronic problem
for other utilities) 44
Models from other countries
45
Australia – rural backbone
•Problemo Fully liberalized market but no competition to Telstra on small-
town/rural routes
o Limits to regulated access to Telstra’s network
•Strategyo Create competition to Telstra on 6 priority up-country routes
(6000km, 100 locations) through subsidizing new entrant (up to A$250).
o Routes selected by government and then contracts tendered.
o Winner required to provide on a non-discriminatory basis –enforced through PPP contract. Operation for 5 years
o Operator required to provide range of wholesale services (Managed wavelength, Carrier managed leased line services (SDH), Carrier managed Ethernet, interconnection)
o Contract and awarded to Nextgen (mid 2009).
Australia – extending backbone network
competition to small towns
Australia – rural backbone
Australia – extending backbone network
competition to small towns
Rwanda: facilitating network development
• Three backbone networks – 3 private, one public
• Direct government funding for backbone network
• Government network reaches unprofitable areas of
the country but also crowds out private investment ?
• Innovative decision to lay multiple ducts and allow
for private operators – shared passive infrastructure,
reduces costs and stimulates network development.
Also avoids planning problems
48
49
Putting backbone policy in Africa into context
• Downstream market competition
o Regulated access to existing operators’ infrastructure: Local
Loop Unbundling, tower access
o Spectrum
o Licensing
• Demand-side stimulation
o Aggregating public demand
o Providing subsidized computers
o Computer training