Carbon Emission and Economic Growth of SAARC Countries: A Vector Autoregressive (VAR) Analysis

Mirza Md. Moyen Uddin; Md. Abdul Wadud

Carbon Emission and Economic Growth of SAARC Countries: A Vector Autoregressive (VAR) Analysis

Mirza Md. Moyen Uddin * §

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Md. Abdul Wadud

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§ Rajshahi University

Carbon Emission and Economic Growth of SAARC Countries: A Vector Autoregressive (VAR) Analysis

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Abstract

This paper examines the causal relationship between carbon (CO 2 ) emissions and economic growth in seven SAARC countries using time series data for the period from 1972-2012. We applied Vector Error Correction Modeling (VECM) approach. We have also applied Augmented DickeyFuller (ADF) and Phillips-Perron (P.P) test and Johansen’s cointegration approach to check time series properties and cointegration relationship of the variables. Results exhibit a cointegration relationship between environmental pollution and economic growth. Results also show that the estimated coefficients of (CO 2 ) emissions have positive and significant impacts on GDP in the long run. These results will help the environmental authorities to understand the effects of economic growth on environment for degradation and manage the environmental problems using macroeconomic methods.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Mirza Uddin, Md. Wadud. 2014. "Carbon Emission and Economic Growth of SAARC Countries: A Vector Autoregressive (VAR) Analysis". Global Journal of Human-Social Science, Global Journal of Human-Social Science - E: Economics GJHSS-E Volume 14 (GJHSS Volume 14 Issue E3).

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GJHSS Volume 14 Issue E3

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Journal Specifications

Crossref Journal DOI 10.17406/GJHSS

Print ISSN 0975-587X

e-ISSN 2249-460X

Keywords

Causality Emission GDP SAARC VECM

Classification

GJHSS-E Classification FOR Code: 910103

Submission ReceivedDecember 9, 2013
Peer Review Double Blind
Handling Editor
Accepted January 3, 2014
Published January 15, 2014

Version of record

v1.2

Issue date

July 11, 2014

Language

English

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Article Matrices

Total Score: 101

Country: Bangladesh

Subject: Global Journal of Human-Social Science

Authors: Mirza Md. Moyen Uddin and Md. Abdul Wadud (PhD/Dr. count: 0)

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Publish Date: 2014 01, Wed

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