Climate policy uncertainty and world renewable energy index volatility forecasting

Chao Liang, Muhammad Umar, Feng Ma and Toan L.D. Huynh

Technological Forecasting and Social Change, 2022, vol. 182, issue C

Abstract: Since the signing of the Paris Agreement in 2015, the global energy structure has undergone unprecedented adjustment, and renewable energy has ushered in a new period of development opportunities. From the perspective of energy stability and sustainable development, this paper uses the generalized autoregression-conditional heteroscedasticity mixed data sampling model (GARCH-MIDAS) to explore the predictive power of climate policy uncertainty (CPU) on the index volatility of renewable energy. At the same time, eight uncertainty indices, including the economic policy uncertainty index and geopolitical risk index variable, are introduced to discuss the impact on the volatility of renewable energy. Furthermore, the out-of-sample prediction accuracy of each model is tested by the out-of-sample ROS2, Model Confidence Set (MCS), direction-of-change (DoC) and other evaluation methods. Climate policy exhibits a superior ability to predict renewable energy volatility, offers a new perspective for the accurate prediction of renewable energy volatility, and provides a reliable guarantee for the sustainable development of the energy market and financial market.

Keywords: Climate policy; Renewable energy volatility; Forecasting; Uncertainty (search for similar items in EconPapers)
JEL-codes: C53 G17 Q47 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (113)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:182:y:2022:i:c:s0040162522003341

DOI: 10.1016/j.techfore.2022.121810

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