Risk analysis in social housing delivery: A public–private partnerships approach. Issue 3 (17th January 2022)

• Record Type: Journal Article
• Authors: Chiang, Lee‐Yun; Earl, George; Liu, Benjamin; Reid, Sacha; Roca, Eduardo
• Is Part Of: Australian journal of public administration. Volume 81:Issue 3(2022)
• Page Start: 455
• Page End: 476
• Publication Date: 2022-01-17
• Subjects: housing policy -- Monte Carlo simulation -- public sector comparator -- public–private partnerships -- risk analysis; Public administration -- Australia -- Periodicals; Policy sciences -- Australia -- Periodicals; Australia -- Politics and government -- Periodicals; 351.9405
• DOI: 10.1111/1467-8500.12535
• Languages: English
• ISSNs: 0313-6647

Abstract

Abstract: Faced with fiscal pressure and concerns over bureaucratic inefficiency, policymakers at Australia's state government level are evaluating instruments to improve social housing services. A public–private partnerships (PPPs) procurement approach is one such instrument for increasing housing supply to address housing affordability in Australia. To determine the value of pursuing a project through a PPP delivery versus a traditional procurement approach, public administrators need to determine discount rates for comparing different cash flows streams on a consistent basis. Additionally, they must estimate public sector comparator (PSC) to determine public sector's risk exposure in social housing delivery and allocating constrained housing budgets. This research assesses the discount rates and estimates the risk profile of social housing delivery faced by public agencies. Three case studies were utilised to present project estimate probability distributions for gaining insight into risk exposure in social housing delivery and helping housing budget allocation at the state government level. The findings recommend the use of an estimated 30‐year treasury bond rate (3.14%) as the PSC discount rate for social infrastructure. Additionally, the results suggest the use of a PPP discount rate for social housing of 6.01%, given a risk‐free rate of 3.14% and a systematic risk premium of 2.87%. Abstract : This research assesses the discount rates and estimates the risk profile of social housing delivery faced by public agencies. Three case studies were utilised to present project estimate probability distributions for gaining insight into risk exposure in social housing delivery and helping housing budget allocation at the state government level.