Modeling renewable energy market performance under climate policy uncertainty: A novel multivariate quantile causality analysis DOI Open Access
Avik Sinha, Muntasir Murshed, Narasingha Das

и другие.

Risk Analysis, Год журнала: 2025, Номер unknown

Опубликована: Фев. 5, 2025

Abstract The renewable energy market in the United States of America (USA) has experienced several crests and troughs owing to changes climate policies. These policies have impacted risk management scenario USA. This impact changed behavioral pattern drivers, a supply‐side analysis this aspect is largely ignored literature. In pursuit, present study aims at analyzing moderating role policy uncertainty shaping behavior drivers Given perspective, novel multivariate quantile‐on‐quantile causality test introduced address five aspects analysis, i.e., tail dependence, co‐movement, predictability, multivariate, asymmetric impact. Moreover, also addresses omitted variable bias absence ortho‐partiality distribution, which were inherent Granger test. Along with national level, firm‐level done by taking top‐5 generation firms results show that dampening effect on differs firm level. impacts significant dimension for addressing climatic concerns USA, while achieving Sustainable Development Goal (SDG) 7 objectives.

Язык: Английский

Modeling renewable energy market performance under climate policy uncertainty: A novel multivariate quantile causality analysis DOI Open Access
Avik Sinha, Muntasir Murshed, Narasingha Das

и другие.

Risk Analysis, Год журнала: 2025, Номер unknown

Опубликована: Фев. 5, 2025

Abstract The renewable energy market in the United States of America (USA) has experienced several crests and troughs owing to changes climate policies. These policies have impacted risk management scenario USA. This impact changed behavioral pattern drivers, a supply‐side analysis this aspect is largely ignored literature. In pursuit, present study aims at analyzing moderating role policy uncertainty shaping behavior drivers Given perspective, novel multivariate quantile‐on‐quantile causality test introduced address five aspects analysis, i.e., tail dependence, co‐movement, predictability, multivariate, asymmetric impact. Moreover, also addresses omitted variable bias absence ortho‐partiality distribution, which were inherent Granger test. Along with national level, firm‐level done by taking top‐5 generation firms results show that dampening effect on differs firm level. impacts significant dimension for addressing climatic concerns USA, while achieving Sustainable Development Goal (SDG) 7 objectives.

Язык: Английский

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