Readiness, riskiness, and renewables appear to form a "tripartite symbiosis" in the clean energy realm. Previous research underscores the significance of readiness as a prerequisite for a nation's advancement toward sustainable energy, urging careful navigation of uncertainties within this framework. Our research expands upon existing literature by delving into how country-level readiness influences a country's innovation in renewable energy in the face of uncertainty. Employing panel fixed effect threshold regression with four distinct models, we analyze this dynamic across 65 countries, representing both advanced and emerging economies. The results validate the presence of an uncertainty threshold effect across all model regressions, confirming a non-linear relationship among uncertainty, country-level readiness, and renewable energy innovation. Overall country-level readiness, along with its components-economic and social readiness-individually fosters renewable energy innovation under low uncertainty. However, this positive influence weakens as uncertainty exceeds the threshold. Conversely, governance readiness exerts a negative impact on renewable energy innovation under low uncertainty, with its detrimental effects becoming more significant at higher levels of uncertainty. The lagged uncertainty has a significant negative association with renewable energy innovation. Policymakers and investors should prioritize developing country level readiness to successfully manage the potential negative influence of uncertainties on renewable energy innovation.

While the process of carbon capture, utilization, and storage (CCUS) plays a pivotal role in mitigating climate change impacts, rising economic uncertainty, geopolitical conflict, and oil price volatility tend to retard CCUS deployment; which carbon emissions trading mechanisms can mitigate. The literature shows that such schemes are still immature in developing economies such as China, where carbon pricing seems to be a key strategy to lower CO2 power generation emissions. In this study, we thus investigate the Chinese carbon market’s volatility, concentrating on time-dependent jumps in emissions pricing. As jump-induced volatility represents an important risk, precise information thereon is important for increased carbon trading efficiency. The GARCH-jump process finds that such jumps do occur in the Chinese emissions market and that key uncertainty indicators including the aforementioned economic policy uncertainty, crude oil volatility index, and geopolitical risk can explain the resulting volatility, with important implications for policymakers and socially responsible investors.

While numerous empirical papers have investigated the volatility dynamics of Chinese clean energy equity markets, this is among the first studies to assess the impact of climate uncertainty on the risk levels of such assets. Given that China is extensively investing in green projects to achieve carbon neutrality, this strand of research offers important implications for investors and policymakers. Methodologically, we employ the GARCH-MIDAS model to examine the effect of the climate policy uncertainty (CPU) index on the volatility levels of the Chinese clean energy exchange-traded fund (ETF). We compare the effects of the CPU index with leading uncertainty indicators, including the crude oil volatility index, geopolitical risk, and technology sector volatility. The in-sample and out-of-sample analyses show that CPU has significant predictive contents for forecasting the volatility of renewable energy ETF and that the GARCH-MIDAS-CPU process outperforms other approaches. These results offer key implications for policymakers and socially responsible investors.