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Research of GSB

High-density affordable housing impact investing: a best-in-class project screening credit risk management model

Abstract

dc:description.abstract

Constrained housing supply coupled with rapid urbanisation and a volatile domestic credit market have put affordable rental housing development under the spotlight. Addressing this demands appropriate and deliberate capital provisions to induce the property development market to deliver the scale needed to tackle the supply-side of the problem. Inducements are needed for residential property developers to choose to develop high-density affordable rental housing on land that presents great accessibility to economically vibrant nodes, where land is priced at a premium. The greenfield residential property development space is in need of sophisticated and specific funding interventions to evolve it beyond the sporadic developments we observe located on the urban periphery on cheap land. The benefits of sophisticated funding models in commercial property have seen the widespread proliferation of building and investment activity. Rental housing, however, lags behind owing to an immature market, shallow investment analysis and rudimentary risk-weighted debt-funding solutions. These funding instruments impede developers building affordable housing schemes on well-located parcels of land near existing amenities and profoundly incorporate green technology into buildings. This research presents a proof of concept for a sophisticated model for high-density housing. A largely 'spatial economic' model for risk analysis, it is developed to attain a so-called Probability of Default Ratio ("PDR") by coalescing two formulae regarded as international best-practice: The risk types incorporated into the model are (1) borrower-level credit risk, (2) property/development-level risk, and (3) cash-flow risk factors. The research is proof of concept of a credit risk management tool for impact investment funding model using these formulae and Geographic Information Systems ("GIS"). It calculates the extent of credit risk for income-producing real estate fundamentals and uses endogenous factors- risk factors and drivers associated with the housing scheme to be build and the surrounding area it is to be built in. The study area covers the 336 contiguous municipal wards that make up the Johannesburg, Tshwane and Ekurhuleni metropolitan municipalities.

Degree

thesis:*
Grantor dc:publisher.institution
Research of GSB
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Lallie, Silimela
Advisors dc:contributor.advisor
  • Cheruiyot, Koech
  • Biekpe, Nicholas

Rights

Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11427/25095
OAI identifier oai:identifier
oai:open.uct.ac.za:11427/25095

Chain of custody

source
Harvested from
University of Cape Town
Base URL
open.uct.ac.za/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Lallie, Silimela. High-density affordable housing impact investing: a best-in-class project screening credit risk management model. Research of GSB, 2017. http://hdl.handle.net/11427/25095