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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Biophysical Economic...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Biophysical Economics and Sustainability
Article . 2020 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Modeling Causal Interactions Between Energy Investment, Pollutant Emissions, and Economic Growth: China Study

Authors: Munir Ahmad; Gul Jabeen; Muhammad Irfan; Marie Claire Mukeshimana; Naseer Ahmed; Maria Jabeen;

Modeling Causal Interactions Between Energy Investment, Pollutant Emissions, and Economic Growth: China Study

Abstract

This study is an empirical investigation of dynamic causal interactions among energy investment, pollutant emissions, and economic growth in China. Three simultaneous equation models have been estimated by employing ‘one-step system’ as well as ‘one-step difference’ generalized method of moments (GMM) estimator for 30 Chinese provinces from 2005 to 2014. This study contributes by developing a hybrid model of economic growth to incorporate energy investment and pollutant emissions. First, the empirical investigation found bilateral positive causal relationship between energy investment and economic growth. Second, bilateral causality between energy investment and economic growth is found to be existent. Third, bilateral causality has been found between pollutant emissions and energy investment. The results are consistent across all the four study samples. Based on empirics, following implications are extracted, among others. The negative bidirectional causal linkage between energy investment and pollutant emissions implicated that investment in fuel-based energy directed to improve the quality of fuels and energy industry technology is likely to curb pollutant emissions. In turn, high level of pollutant emissions may stimulate policies to reduce investment in fuel-based energy industry. Finally, the positive bidirectional causal linkage between energy investment and economic growth implied that energy investment and economic growth tend to promote each other in China. The prominence of this relationship in eastern economic zone further suggested that energy investment is likely to become strongest driver of economic growth and vice versa in this region, which is followed by intermediate economic zone and western economic zone.

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
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    Top 10%
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
42
Top 1%
Top 10%
Top 1%