Please use this identifier to cite or link to this item: https://hdl.handle.net/1822/74970

TitleFeed-in tariff contract schemes and regulatory uncertainty
Author(s)Barbosa, Luciana
Nunes, Cláudia
Rodrigues, Artur
Sardinha, Alberto
KeywordsInvestment analysis
Real options
Feed-in tariff
Regulatory uncertainty
Issue date16-Nov-2020
PublisherElsevier
JournalEuropean Journal of Operational Research
Abstract(s)This paper presents a novel analysis of two feed-in tariffs (FIT) under market and regulatory uncertainty, namely a sliding premium with cap and floor and a minimum price guarantee. Regulatory uncertainty is modeled with a Poisson process, whereby a jump event may reduce the tariff before the signature of the contract. Using a semi-analytical real options framework, we derive the project value, the optimal investment threshold, and the value of the investment opportunity for these schemes. Taking into consideration the optimal investment threshold, we also compare the two aforementioned FITs with the fixed-price FIT and the fixed-premium FIT, which are policy schemes that have been extensively studied in the literature. Our results show that increasing the likelihood of a jump event lowers the investment threshold for all the schemes; moreover, the investment threshold also decreases when the tariff reduction increases. We also compare the four schemes in terms of the corresponding optimal investment thresholds. For example, we find that the investment threshold of the sliding premium is lower than the minimum price guarantee. This result suggests that the first regime is a better policy than the latter because it accelerates the investment while avoiding excessive earnings for producers or excessive payments for consumers.
TypeArticle
URIhttps://hdl.handle.net/1822/74970
DOI10.1016/j.ejor.2020.04.054
ISSN0377-2217
Publisher versionhttps://www.sciencedirect.com/science/article/pii/S0377221720304070
Peer-Reviewedyes
AccessOpen access
Appears in Collections:NIPE - Artigos em Revistas de Circulação Internacional com Arbitragem Científica

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