Author
Listed:
- Maria Tsiodra
- Michail Chronopoulos
Abstract
Meeting ambitious sustainability targets motivated by climate change concerns requires the structural transformation of many industries and the careful alignment of firm- and Government-level policymaking. While private firms rely on Government support to achieve timely the necessary green investment intensity, Governments rely on private firms to tackle financial constraints and technology transfer. This interaction is analysed in the real options literature only under risk neutrality, and, consequently, the implications of risk aversion due to the idiosyncratic risk that green technologies entail are overlooked. To analyse how this interaction impacts a firm’s investment policy and a Government’s subsidy design under uncertainty and risk aversion, we develop a real options framework, whereby: (i) we solve the firm’s investment problem assuming an exogenous subsidy; (ii) conditional on the firm’s optimal investment policy, we address the Government’s optimisation objective and derive the optimal subsidy level; (iii) we insert the optimal subsidy level in (i) to derive the firm’s endogenous investment policy. Contrary to existing literature, results indicate that greater risk aversion lowers the amount of installed capacity yet postpones investment. Also, although greater uncertainty raises the optimal subsidy under risk neutrality, the impact of uncertainty is reversed under high levels of risk aversion.
Suggested Citation
Maria Tsiodra & Michail Chronopoulos, 2022.
"A bi-level model for optimal capacity investment and subsidy design under risk aversion and uncertainty,"
Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(8), pages 1787-1799, August.
Handle:
RePEc:taf:tjorxx:v:73:y:2022:i:8:p:1787-1799
DOI: 10.1080/01605682.2021.1943021
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tjorxx:v:73:y:2022:i:8:p:1787-1799. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjor .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.