1. Urban infrastructure in Sub-Saharan Africa
Harnessing land values, housing and transport
The Africa Land and Infrastructure City Scan:
A profile of 31 cities in Sub-Saharan Africa
Brandon Finn, ACC
20 July 2015

2. Purpose of the scan
Run a high level assessment of the potential of cities in Sub-Saharan Africa to apply Land- Based Financing
Recognition of the complexity of factors impacting in potential and the shortage of good data on SSA cities

3. Multi-criteria analysis: Assessing the relative potential of cities to apply land-based financing
Identify cities
Identify criteria
Identify indicators
Adjust indicators to scores
Assign weights
Calculate overall score
Examine results

4. Selection of cities Top 31 – all above 1 million people bar Lilongwe
UN Habitat - State of African Cities – escalated (plus some additional data)

5. Land-based financing relationships
Space (property) market
Supply
Demand
Economic growth;
Urbanisation
Planning and land use management
Local government
Developers
Financiers
Bulk, connector and social Infrastructure
Finance
State
Value capture

6. Primary Criterion Secondary Criterion Indicator (see key) C C
City or National
Well developed economy
City GVA/capita (OE) C
Growing economy
City GVA growth (OE) C
Demand for property
Growing population
Rate of population growth (OE) C C
Ability to pay for property
% High income households (OE)
Land use formally approved
Team rating C
Ease of getting land use approval
Team rating C
Access to land
Degree of secure tenure
Sum of EFW, MCC and WEF ratings N
Ease of registering ownership
Ease of business: registration ranking N
Supply of property
Active developers
Ease of doing business
Ease of business: other indicators N N
Access to finance
Access to banking
WDI – banks per 100,000 capita N
Functions devolved
UCLGA indicator on constitution
Service provision track record
Composite elec & watsan access C
Effective City
Financially viable
UCLGA indicator on own revenue N
Adequate technical capacity
WEF professional management; skills N
Effective planning and LUM
Existence of master plan C
Citizens willing to pay for services
% household income to services (OE) C
Effective State N
Sound governance
WB governance indicator N
Commitment to support LG
UCLG rating N
Level of transfers to LG
WDI indicator

7. Weighting –base position
Primary criterion
Primary Weight
Secondary criterion
Secondary Weight
Demand for property 10
Well-developed economy 20
Growing economy 30
Growing population
Ability to pay for property
Access to land
Land use formally approved
Ease of getting land use approval
Degree of secure tenure
Ease of registering land
Active developers
Extent to which developers can function easily
100
Ease of access to property related finance
Access to banking
Effective city
Functions devolved
Service provision track record
Financially viable
Adequate technical capacity
Effective planning and LUM
Citizens willing to pay for services
Effective State
Extent to which governance is effective 40
Commitment to support LG 50
Extent to which transfers are made to LG

8. Africa Land and Infrastructure City Scan
Interactive web-based database
Inputs:
Set up for any cities
Add any data
Calculate relationships between data (e.g. GDP/capita)
Apply multi-criteria analysis
Present results:
Map
Table
Graph
Download results
Developed by Sean Walsh of Webfresh – for ACC and DFID

9. Data for cities with link to Google maps

10. Set up Multi-Criteria Analysis and easy adjusting of weights
Primary and secondary criteria facility

11. Test different weightings
Criterion grouping
Weight shift
Relative weights
Swing in MCA score
Demand for property
Supply side factors
Effective city
Effective State
Default 10 50 30
30 to 50 7 36
0.22
30 to 10 13 64
0.21
10 to 30 39 23 8
0.24
Effective state 24
0.12
50 to 30 14 42
0.20

12. Plot against any other criteria – GDP per capita in this case
Headline results: MCA scores
Plot against any other criteria – GDP per capita in this case

13. End
Urban infrastructure in Sub- Saharan Africa – harnessing land values, housing and transport