2022
DOI: 10.3389/fenvs.2022.857225
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Spatial Effect of Economic Growth Targets on CO2 Emissions: Evidence From Prefectural-Level Cities in China

Abstract: Since the GDP-oriented evaluation system was introduced in China, setting ambitious economic growth targets has become a norm for governments at all levels, which promotes rapid economic growth but also causes serious carbon emissions. To achieve high-quality sustainable development, a key issue is to optimize the role of economic growth targets by studying their impact on the environment. In this context, this paper employs the spatial Durbin model to investigate the impact of economic growth targets on CO2 e… Show more

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Cited by 11 publications
(11 citation statements)
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“…Geographic distance is an essential factor affecting the frequency of economic ties. Therefore, referring to the common practices of previous scholars ( 14 , 40 ), we use a geographical distance weight matrix (W 1 ) to estimate the spatial effect, and the robustness test is performed using an economic matrix (W 2 ) and an adjacency matrix (W 3 ).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Geographic distance is an essential factor affecting the frequency of economic ties. Therefore, referring to the common practices of previous scholars ( 14 , 40 ), we use a geographical distance weight matrix (W 1 ) to estimate the spatial effect, and the robustness test is performed using an economic matrix (W 2 ) and an adjacency matrix (W 3 ).…”
Section: Methodsmentioning
confidence: 99%
“…Environmental pollution affects the sustainability of economic development and human health ( 14 16 ). Innovation, environmental supervision, and urbanization are essential factors affecting environmental pollution.…”
Section: Introductionmentioning
confidence: 99%
“…Spacial spillover is the specific property of air pollution, many articles regarding adopt spacial models to conduct the empirical research. Ge et al, (2022) (Ge et al, 2022) used the spatial Durbin model to study the impact of economic growth targets on CO 2 emissions. Han et al, (2022) (Han et al, 2022) used panel data from 282 prefecture level cities in China, and adopted spatial Durbin and STIRPAT models to study the impact of industrial agglomeration on nitrogen dioxide emissions.…”
Section: Literature Review and Hypothesis Developmentmentioning
confidence: 99%
“…Due to the lack of independence among spatial data, spatial autocorrelation is a common phenomenon (Fujita et al, 2000). Subsequently, spatial econometrics has been widely used to explain various economic phenomena with spatial correlation (Elhorst, 2014), and many important theoretical and practical achievements are made in IEE and industrial agglomeration (Chen et al, 2020;Ge et al, 2022).…”
Section: Literature Reviewmentioning
confidence: 99%