Dynamic and casual association between green investment, clean energy and environmental sustainability using advance quantile A.R.D.L. framework

This study examines the dynamic and causal relationship between green investment (G.I.), clean energy (C.E.), economic growth, and environmental sustainability with the help of an innovative approach named as quantile autoregressive distributed lagged (Q.A.R.D.L.) model using quarterly data from Q1-...

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Autores principales:	Yunpeng Sun, Haoning Li, Kun Zhang, Hafiz Waqas Kamran
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2021
Materias:	green investment (g.i.) clean energy (c.e.) carbon emission quantile autoregressive distributed lagged (q.a.r.d.l.) china Economic growth, development, planning HD72-88 Regional economics. Space in economics HT388
Acceso en línea:	https://doaj.org/article/b0b1607eac57465893b4cc33e748e8d8
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spelling	oai:doaj.org-article:b0b1607eac57465893b4cc33e748e8d82021-12-01T14:40:58ZDynamic and casual association between green investment, clean energy and environmental sustainability using advance quantile A.R.D.L. framework1331-677X1848-966410.1080/1331677X.2021.1997627https://doaj.org/article/b0b1607eac57465893b4cc33e748e8d82021-11-01T00:00:00Zhttp://dx.doi.org/10.1080/1331677X.2021.1997627https://doaj.org/toc/1331-677Xhttps://doaj.org/toc/1848-9664This study examines the dynamic and causal relationship between green investment (G.I.), clean energy (C.E.), economic growth, and environmental sustainability with the help of an innovative approach named as quantile autoregressive distributed lagged (Q.A.R.D.L.) model using quarterly data from Q1-1995 to Q4-2019 for China. Our preliminary findings confirm data non-normality and structural breaks in all data series. Therefore, we have applied Q.A.R.D.L. that efficiently deals with these issues. We have further applied the Granger-causality in quantiles to check the causal association among the variables of interest. The findings through Q.A.R.D.L. estimation confirm that the error correction parameter is statistically significant with expected negative sign across major quantiles. In the long run, the results confirm that both C.E., and G.I. are significant mitigants of environmental pollution, however their emissions mitigating effects varies across lower, middle, and higher emissions quantiles. Furthermore, the findings through Granger-causality test confirm the existence of two-way causality between G.I., C.E., and carbon emissions across all quantiles. These results offer valuable policy implications.Yunpeng SunHaoning LiKun ZhangHafiz Waqas KamranTaylor & Francis Grouparticlegreen investment (g.i.)clean energy (c.e.)carbon emissionquantile autoregressive distributed lagged (q.a.r.d.l.)chinaEconomic growth, development, planningHD72-88Regional economics. Space in economicsHT388ENEkonomska Istraživanja, Vol 0, Iss 0, Pp 1-20 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	green investment (g.i.) clean energy (c.e.) carbon emission quantile autoregressive distributed lagged (q.a.r.d.l.) china Economic growth, development, planning HD72-88 Regional economics. Space in economics HT388
spellingShingle	green investment (g.i.) clean energy (c.e.) carbon emission quantile autoregressive distributed lagged (q.a.r.d.l.) china Economic growth, development, planning HD72-88 Regional economics. Space in economics HT388 Yunpeng Sun Haoning Li Kun Zhang Hafiz Waqas Kamran Dynamic and casual association between green investment, clean energy and environmental sustainability using advance quantile A.R.D.L. framework
description	This study examines the dynamic and causal relationship between green investment (G.I.), clean energy (C.E.), economic growth, and environmental sustainability with the help of an innovative approach named as quantile autoregressive distributed lagged (Q.A.R.D.L.) model using quarterly data from Q1-1995 to Q4-2019 for China. Our preliminary findings confirm data non-normality and structural breaks in all data series. Therefore, we have applied Q.A.R.D.L. that efficiently deals with these issues. We have further applied the Granger-causality in quantiles to check the causal association among the variables of interest. The findings through Q.A.R.D.L. estimation confirm that the error correction parameter is statistically significant with expected negative sign across major quantiles. In the long run, the results confirm that both C.E., and G.I. are significant mitigants of environmental pollution, however their emissions mitigating effects varies across lower, middle, and higher emissions quantiles. Furthermore, the findings through Granger-causality test confirm the existence of two-way causality between G.I., C.E., and carbon emissions across all quantiles. These results offer valuable policy implications.
format	article
author	Yunpeng Sun Haoning Li Kun Zhang Hafiz Waqas Kamran
author_facet	Yunpeng Sun Haoning Li Kun Zhang Hafiz Waqas Kamran
author_sort	Yunpeng Sun
title	Dynamic and casual association between green investment, clean energy and environmental sustainability using advance quantile A.R.D.L. framework
title_short	Dynamic and casual association between green investment, clean energy and environmental sustainability using advance quantile A.R.D.L. framework
title_full	Dynamic and casual association between green investment, clean energy and environmental sustainability using advance quantile A.R.D.L. framework
title_fullStr	Dynamic and casual association between green investment, clean energy and environmental sustainability using advance quantile A.R.D.L. framework
title_full_unstemmed	Dynamic and casual association between green investment, clean energy and environmental sustainability using advance quantile A.R.D.L. framework
title_sort	dynamic and casual association between green investment, clean energy and environmental sustainability using advance quantile a.r.d.l. framework
publisher	Taylor & Francis Group
publishDate	2021
url	https://doaj.org/article/b0b1607eac57465893b4cc33e748e8d8
work_keys_str_mv	AT yunpengsun dynamicandcasualassociationbetweengreeninvestmentcleanenergyandenvironmentalsustainabilityusingadvancequantileardlframework AT haoningli dynamicandcasualassociationbetweengreeninvestmentcleanenergyandenvironmentalsustainabilityusingadvancequantileardlframework AT kunzhang dynamicandcasualassociationbetweengreeninvestmentcleanenergyandenvironmentalsustainabilityusingadvancequantileardlframework AT hafizwaqaskamran dynamicandcasualassociationbetweengreeninvestmentcleanenergyandenvironmentalsustainabilityusingadvancequantileardlframework
_version_	1718405015022862336

Dynamic and casual association between green investment, clean energy and environmental sustainability using advance quantile A.R.D.L. framework

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