Optimizing an Equity Capital Structure Model for Public-Private Partnership Projects Involved with Public Funds

  • Ke Feng
  • , Wei Xiong
  • , Shouqing Wang*
  • , Chunlin Wu
  • , Yanguang Xue
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Public-private partnerships (PPPs) have been utilized worldwide as an effective tool to fill the gap between a surging demand for infrastructure and a shrinking public fiscal budget. However, the successful implementations of large PPP projects are hindered by huge capital investments and high uncertainties. To solve this challenge, hosting governments may choose to offer public funds, including public equity and government subsidy, to the financing of special purpose vehicle (SPV) on the purpose of strengthening projects' financial viability and increasing transparency of SPV's operation. The involvement of public funds reforms the traditional equity capital structure and needs to be carefully studied. To facilitate relevant decision-making for both private and public sector, this research developed a genetic algorithm based model to simultaneously optimize private equity, public equity and government subsidy for PPP projects. The effects of risk factors are incorporated by utilizing Monte Carlo simulation. The Beijing No. 4 Metro Line project is presented to demonstrate the applicability of the model. Optimization results show that the proposed model achieves balance between satisfying project's financial viability and saving public funds. And it will significantly facilitate both private and public sector in determining an optimal equity capital structure which are involved with public funds.

Original languageEnglish
Article number04017067
JournalJournal of Construction Engineering and Management
Volume143
Issue number9
DOIs
StatePublished - 1 Sep 2017

Keywords

  • Equity capital structure
  • Genetic algorithm
  • Monte Carlo simulation
  • Project planning and design
  • Public funds
  • Public-private partnerships

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