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THE IMPACT OF GLOBALIZATION ON CO2 EMISSIONS IN CHINA

SHAHBAZ, MUHAMMAD, KHAN, SALEHEEN, ALI, AMJAD, BHATTACHARYA, MITA·2017·The Singapore Economic Review

Abstract

This paper examines the environmental kuznets curve (EKC) hypothesis for China in the presence of globalization. We have applied Bayer and Hanck combined cointegration test as well as the auto regressive distributed lag (ARDL) bounds testing approach to cointegration by accommodating structural breaks in the series. The causal relationship among the variables is investigated by applying the vector error correction method (VECM) causality framework. The study covers the period of 1970–2012. The results confirm the presence of cointegration among the variables. Furthermore, the EKC hypothesis is valid in China both in short and long runs. Coal consumption increases carbon dioxide (CO 2) emissions significantly. The overall index and sub-indices of globalization indicate that globalization in China is decreasing CO 2 emissions. The causality results reveal that economic growth causes CO 2 emissions confirming the existence of the EKC hypothesis. The feedback effect exists between coal consumption and CO 2 emissions. CO 2 emissions Granger causes globalization (social, economic and political).

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Metadata

Authors
SHAHBAZ, M., KHAN, S., ALI, A., & BHATTACHARYA, M.
Venue
The Singapore Economic Review
Published
2017-09
Volume
62
Issue
04
Pages
929-957
ISSN
  • 0217-5908 (ISSN-L)
  • 1793-6837
OpenAlex
W2508272329
Cited by
340
References
4
FWCI
21.28
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: THE IMPACT OF GLOBALIZATION ON CO2 EMISSIONS IN CHINA. https://app.cochat.ai/papers/10.1142/s0217590817400331
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SHAHBAZ, M., KHAN, S., ALI, A., & BHATTACHARYA, M. (2017). THE IMPACT OF GLOBALIZATION ON CO2 EMISSIONS IN CHINA. The Singapore Economic Review. https://doi.org/10.1142/s0217590817400331

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.