Title
Does Climate Policy Uncertainty Drive Renewable Energy Returns? Asymmetric Evidence from 21 Developed Economies
Authors
Abstract
Purpose – This study asks whether climate policy uncertainty drives renewable energy returns and whether its influence depends on the state of the market. Mean-based evidence cannot tell a decision maker how large climate-policy exposure becomes precisely in the states where it binds.
Design/methodology/approach – A panel quantile autoregressive distributed lag model is estimated in error-correction form on daily data for 21 developed economies over an unbalanced 2000–2025 window. Estimation uses the unrestricted linear specification with long-run parameters recovered ex post, the cointegrating vector is confined to I(1) level series, and inference rests on a 1,000-replication moving-block bootstrap and a cross-sectionally augmented check.
Findings – The effect is negative, state-dependent, and asymmetric. A one-standard-deviation rise in climate policy uncertainty is associated with a long-run equilibrium index level about 0.1810 percent lower at the fifth percentile, against about 0.0480 percent at the median, and equilibrium correction is faster when markets are stressed.
Originality/value – No prior study delivers, within a single estimator and for a broad developed-economy panel, quantile-specific long-run cointegrating coefficients, quantile-specific adjustment speeds, and a formal sign-asymmetry decomposition together.
Implications – Climate-policy exposure should be treated as a tail risk rather than a fixed average sensitivity, and hedges sized to the bearish-tail and asymmetry estimates.
Keywords
climate policy uncertainty, renewable energy, panel quantile ARDL, asymmetric spillovers, developed economies, energy transition
Classification-JEL
G12, G15, Q42, Q54, C22
Pages
157-187
How to Cite
Laurinavicius, A., Laurinavicius, A., Ghanem, M. E. A., Kalra, A., & Khan, M. A. I. (2026). Does Climate Policy Uncertainty Drive Renewable Energy Returns? Asymmetric Evidence from 21 Developed Economies. Advances in Decision Sciences, 30(4), 157-187.