Modeling the behavior of renewable energy market: Understanding the moderation of climate risk factors

Avik Sinha, Sunil Tiwari and Tanaya Saha

Energy Economics, 2024, vol. 130, issue C

Abstract: The behavior of the renewable energy market largely depends on the impact of renewable energy generation drivers. The susceptibility of these drivers to climatic adversities shapes their impact. Moreover, renewable energy generation projects are also vulnerable to climate risk factors, i.e., physical and transition risks. Existing climate resilience frameworks in the United States of America might be inconclusive to address this concern, and this inability is reflected in non-accomplishment of the Sustainable Development Goal (SDG) 7 objectives. It indicates a policy void concerning the internalization of the climate risk factors for realizing the potential of renewable energy market. Therein lies the focus of the present study. The study analyzes the impacts of the returns on renewable energy drivers on the renewable energy market returns by controlling the climate risk factors from August 01, 2014, to July 06, 2023. The analysis is carried out by cross quantile correlation and multivariate quantile-on-quantile regression methods. The results show that the impact of the returns on renewable energy drivers on the renewable energy market returns reduces in presence of the climatic risk factors, i.e., natural disasters (physical risk) and climate policy uncertainty (transition risk). The climatic resilience-oriented policy framework developed in the study is aimed at internalizing the physical and transition climate risk factors, and thereby, progressing towards attaining SDG 7 objectives.

Keywords: Renewable energy market; Climate risk; United States of America; Sustainable development goal; Multivariate quantile-on-quantile regression (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:130:y:2024:i:c:s0140988323007880

DOI: 10.1016/j.eneco.2023.107290

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