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Mapping the asymmetric dynamics between ESG uncertainty and clean energy: A quantile-wavelet framework
1Sivas University of Science and Technology, Sivas, Türkiye.
Sustainability uncertainties, measured by the ESG-based Sustainability Uncertainty Index (ESGUI), significantly impact clean energy markets. These effects are nonlinear and asymmetric, particularly negative during market downturns, influencing investor strategies and policy development.
Area of Science:
- Environmental, Social, and Governance (ESG) factors
- Financial markets
- Clean energy economics
Background:
- Growing importance of sustainability in investment decisions.
- Need to understand the volatility drivers in clean energy markets.
- ESG-based Sustainability Uncertainty Index (ESGUI) as a novel metric.
Purpose of the Study:
- To investigate the impact of ESGUI on various clean energy market indices.
- To analyze these impacts across different quantiles and time scales.
- To reveal the dynamic relationship between sustainability uncertainties and clean energy market performance.
Main Methods:
- Utilized monthly data from July 31, 2015, to June 30, 2025.
- Employed Quantile on Quantile Regression (QQR), Wavelet Quantile Regression (WQR), and Quantile on Quantile Granger Causality (QQGC).
- Analyzed five key clean energy indices: GCEI, KCEI, RENIXX, MSCIGA, and MSCIACWI IMI.
Main Results:
- ESG uncertainties exhibit heterogeneous, nonlinear, and asymmetric effects on clean energy markets.
- Strong negative impacts observed during market declines, with persistent effects in the medium to long term.
- ESG uncertainties demonstrate predictive power, guiding investor behavior in various market conditions.
Conclusions:
- Sustainability uncertainties pose significant risks and opportunities in clean energy markets.
- Findings inform investor risk management and policymaker strategies for accelerating the energy transition.
- The study underscores the need for robust frameworks to navigate ESG-related market dynamics.
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