Crossing the Brownian Bridge: valuing infrastructure capacity expansion policies as real options

Abstract

In countries where transportation infrastructure is underdeveloped, newly built facilities tend to attract and increase demand. This can lead to situations where future traffic levels exceed the concession capacity limit, and additional investments in expansion is required. One common solution is to mandate this investment as a firm obligation in concession contracts, either after a set number of years or when demand reaches capacity. In this article, we show why these policies are suboptimal and propose a model that combines flexible capacity expansion decisions with conditional term extensions. We model this flexibility under the real options approach and the project value uncertainty during the life of the concession as a Brownian Bridge. As a novel contribution, we take into account the fact that concession revenues are bounded by the current traffic capacity of the road, which represents an upper absorbing barrier that has implications for the expansion decision. As a numerical application, this model is applied to a typical toll road project in Brazil. The results show that flexible expansion policies, coupled with conditional term extensions, have significant advantages. These findings can be of use to government officials involved in developing policies to attract private investment in public infrastructure projects.

Keywords:

• Infrastructure projects
• capacity expansion
• real options
• project valuation
• term extension

Acknowledgments

The authors wish to thank Elizabeth Whalley, Artur Rodrigues, and other participants of the 24th International Conference on Real Options in London, UK, for their comments on an earlier version of this paper.

Disclosure statement

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

Data availability statement

The data that support the findings of this study are openly available in the Zenodo data repository at https://doi.org/10.5281/zenodo.3874946.

Additional information

Funding

This work was supported in part by the National Council for Scientific and Technological Development – CNPq Brazil [grants number 303908/2018-1 and 406198/2018-7] and by the Foundation for Research Support of the State of Rio de Janeiro (FAPERJ) [grant E-26/202.868/2018].