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

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.

Keywords:

• PPP Projects
• Capital Structure
• Chance-constrained Programming

Acknowledgements

The authors would like to appreciate this financial support for this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data and models generated or used during the study are available from the corresponding author by request (Specific model derivation process, simulation result, case study data).

Additional information

Funding

This research was financially supported by the National Natural Science Foundation of China [Grant nos. 71202083, 71572124 and 72031008] and Humanities and Social Science Research and Planning Foundation of the Ministry of Education [Grant no. 20YJA630066].