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

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

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

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

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

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

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

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

Data for cities with link to Google maps

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

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

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

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