Exploring the Relationship Among Economic Growth, Energy Consumption, Carbon Emission and Trade: A Panel Vector Error Correction Model (VECM) Analyses

Hemant Kumar Sah; Gyanendra Singh Sisodia

doi:10.1007/978-981-19-3540-4_9

Exploring the Relationship Among Economic Growth, Energy Consumption, Carbon Emission and Trade: A Panel Vector Error Correction Model (VECM) Analyses

Hemant Kumar Sah
, Gyanendra Singh Sisodia

College of Business Administration

Ranchi University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

This study empirically examines the causality among economic growth, energy consumption, carbon emission and trade in Argentina, China, Ghana and India from the balanced dataset of 1990–2017. Using the Panel Vector Error Correction Model with the panel data we examine the long run and short run causality among the variables. The result of this study shows that long run relationship exists between the variables. The finding suggests that, promotion of an alternative energy sources like clean energy (renewable energy) is recommended that reduces carbon emission without hampering economic growth and trade.

Original language	English
Title of host publication	Industrial Ecology
Publisher	Springer
Pages	249-265
Number of pages	17
DOIs	https://doi.org/10.1007/978-981-19-3540-4_9
State	Published - 2022

Publication series

Name	Industrial Ecology
Volume	Part F11964
ISSN (Print)	2730-5775
ISSN (Electronic)	2730-5783

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 8 Decent Work and Economic Growth

Keywords

Carbon emission
Economic growth
Panel VECM
Renewable energy
Trade

Access to Document

10.1007/978-981-19-3540-4_9

Cite this

@inbook{c8b7521d4d1d44f7ad087dca865726ee,

title = "Exploring the Relationship Among Economic Growth, Energy Consumption, Carbon Emission and Trade: A Panel Vector Error Correction Model (VECM) Analyses",

abstract = "This study empirically examines the causality among economic growth, energy consumption, carbon emission and trade in Argentina, China, Ghana and India from the balanced dataset of 1990{\textendash}2017. Using the Panel Vector Error Correction Model with the panel data we examine the long run and short run causality among the variables. The result of this study shows that long run relationship exists between the variables. The finding suggests that, promotion of an alternative energy sources like clean energy (renewable energy) is recommended that reduces carbon emission without hampering economic growth and trade.",

keywords = "Carbon emission, Economic growth, Panel VECM, Renewable energy, Trade",

author = "Sah, \{Hemant Kumar\} and Sisodia, \{Gyanendra Singh\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.",

year = "2022",

doi = "10.1007/978-981-19-3540-4\_9",

language = "English",

series = "Industrial Ecology",

publisher = "Springer",

pages = "249--265",

booktitle = "Industrial Ecology",

address = "Germany",

}

Exploring the Relationship Among Economic Growth, Energy Consumption, Carbon Emission and Trade: A Panel Vector Error Correction Model (VECM) Analyses. / Sah, Hemant Kumar; Sisodia, Gyanendra Singh.
Industrial Ecology. Springer, 2022. p. 249-265 (Industrial Ecology; Vol. Part F11964).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Exploring the Relationship Among Economic Growth, Energy Consumption, Carbon Emission and Trade

T2 - A Panel Vector Error Correction Model (VECM) Analyses

AU - Sah, Hemant Kumar

AU - Sisodia, Gyanendra Singh

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

PY - 2022

Y1 - 2022

N2 - This study empirically examines the causality among economic growth, energy consumption, carbon emission and trade in Argentina, China, Ghana and India from the balanced dataset of 1990–2017. Using the Panel Vector Error Correction Model with the panel data we examine the long run and short run causality among the variables. The result of this study shows that long run relationship exists between the variables. The finding suggests that, promotion of an alternative energy sources like clean energy (renewable energy) is recommended that reduces carbon emission without hampering economic growth and trade.

AB - This study empirically examines the causality among economic growth, energy consumption, carbon emission and trade in Argentina, China, Ghana and India from the balanced dataset of 1990–2017. Using the Panel Vector Error Correction Model with the panel data we examine the long run and short run causality among the variables. The result of this study shows that long run relationship exists between the variables. The finding suggests that, promotion of an alternative energy sources like clean energy (renewable energy) is recommended that reduces carbon emission without hampering economic growth and trade.

KW - Carbon emission

KW - Economic growth

KW - Panel VECM

KW - Renewable energy

KW - Trade

UR - https://www.scopus.com/pages/publications/105043634156

U2 - 10.1007/978-981-19-3540-4_9

DO - 10.1007/978-981-19-3540-4_9

M3 - Chapter

AN - SCOPUS:105043634156

T3 - Industrial Ecology

SP - 249

EP - 265

BT - Industrial Ecology

PB - Springer

ER -

Exploring the Relationship Among Economic Growth, Energy Consumption, Carbon Emission and Trade: A Panel Vector Error Correction Model (VECM) Analyses

Abstract

Publication series

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this