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contributor authorKe Feng
contributor authorWei Xiong
contributor authorShouqing Wang
contributor authorChunlin Wu
contributor authorYanguang Xue
date accessioned2017-12-16T09:18:19Z
date available2017-12-16T09:18:19Z
date issued2017
identifier other%28ASCE%29CO.1943-7862.0001349.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4241178
description abstractPublic–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.
publisherAmerican Society of Civil Engineers
titleOptimizing an Equity Capital Structure Model for Public–Private Partnership Projects Involved with Public Funds
typeJournal Paper
journal volume143
journal issue9
journal titleJournal of Construction Engineering and Management
identifier doi10.1061/(ASCE)CO.1943-7862.0001349
treeJournal of Construction Engineering and Management:;2017:;Volume ( 143 ):;issue: 009
contenttypeFulltext


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