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A chance constrained programming method to determine optimal capital structure for privatized infrastructure

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Listed:
  • Xiuqin Wang
  • Bing Wang
  • Yantao Xu
  • Lanmin Shi

Abstract

Capital structure optimization is an important aspect to ensure the success of public–private partnership (PPP) financing. Existing optimization methods fail to provide certain confidence level of the optimization result of PPP capital structure. The aim of this paper to optimize the capital structure of PPP projects by developing a chance-constrained programming (CCP) method with a certain confidence level under project risks. The results show that compared with existing methods, CCP method yields a greater optimal equity share, smaller NPV value, and higher confidence level depending on private sector’s risk preference. Besides, the optimal equity share is mainly determined by banks’ requirement and government regulation on commitment and it shrinks as banks’ risk preference grows. Theoretical calculation and simulation technique were adopted to make the result more convincing. The paper can help the private sector to more reasonably and reliably determine the optimal capital structure according to their risk preference.

Suggested Citation

  • Xiuqin Wang & Bing Wang & Yantao Xu & Lanmin Shi, 2021. "A chance constrained programming method to determine optimal capital structure for privatized infrastructure," Construction Management and Economics, Taylor & Francis Journals, vol. 39(7), pages 579-594, July.
    • Handle: RePEc:taf:conmgt:v:39:y:2021:i:7:p:579-594
    DOI: 10.1080/01446193.2021.1930081
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    Cited by:

    1. Juan David González-Ruiz & Sergio Botero-Botero & Alejandro Peña, 2022. "Analysis of the Capital Structure in Sustainable Infrastructure Systems: A Methodological Approach," Sustainability, MDPI, vol. 14(19), pages 1-21, October.

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