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- W4280492522 endingPage "121743" @default.
- W4280492522 startingPage "121743" @default.
- W4280492522 abstract "This study investigated time-frequency transmission and connectedness among green indexes dealing with clean energy, environmental preservation, and technological innovation and information uncertainty related to economics news, the COVID-19 pandemic, and Twitter usage. First, by employing a quantile vector autoregression framework, we assessed how the static and dynamic connectedness between markets switched across a broad spectrum of market conditions, particularly bear, normal, and bull markets. Second, we examined the dynamics of the co-movement between green financial markets and the level of uncertainty in the time-frequency domain using novel vector wavelet coherence analysis. Our analysis yielded the following major findings: Statically, high spillover and volatility effects existed among the indexes; dynamically, evidence of very strong connectedness between climate change indexes was reported at extreme lower and extreme upper quantiles. The findings further exhibit the switching of climate change between net contributing/net receiving shock behavior during the pandemic. Technological innovation, the COVID-19 pandemic, and uncertainty have strong effects on climate change markets as revealed by multiple, quadruple, and vector wavelet analysis. Implications for both environmental investors and policymakers were revealed." @default.
- W4280492522 created "2022-05-22" @default.
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- W4280492522 date "2022-08-01" @default.
- W4280492522 modified "2023-10-01" @default.
- W4280492522 title "Dynamic spillover effects and connectedness among climate change, technological innovation, and uncertainty: Evidence from a quantile VAR network and wavelet coherence" @default.
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- W4280492522 doi "https://doi.org/10.1016/j.techfore.2022.121743" @default.
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