Heterogeneous effects of urbanization, economic growth, and energy consumption on carbon emissions in China: evidence from a PVAR model

Zhang, Yangyang; Hong, Wenxia; Huang, Qiaran; Liu, Chuanyu

doi:10.1007/s11869-023-01419-9

Cited by 6 publications

(3 citation statements)

References 126 publications

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“…After having seen the different theoretical aspects in the previous sections, we considered it wise in this empirical framework to examine the quantitative interactions likely to occur between the economic growth process and the variables inherent to the consumption of different types of energy. Considering the predictive and dynamic nature of our problem, where we aimed to determine the interdependence of our variables in both static and dynamic contexts, we resorted to PVAR modeling (Öztürk et al, 2023;Wu et al, 2023;Zhang et al, 2023). Thus, this section is dedicated to measuring the effects of the current economic growth model on the ecological and environmental dimensions in a geographical area comprising 35 developing countries.…”

Section: Empirical Methodologymentioning

confidence: 99%

The Effects of Economic Cycle Shocks on Polluting Emissions in Developing Countries: Insights from a Panel Vector Autoregression Analysis

Fakhri,

Meshari,

Othayman

et al. 2024

CiS

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This study explores the dynamic relationship between polluting emissions and economic cycle shocks in developing countries using a panel vector autoregressive (PVAR) framework. Recognizing the limitations of prior models that focused primarily on causality between emissions and economic variables without forecasting capabilities, this research incorporates a PVAR methodology aligned with innovative local gray forecast models to generate dynamic forecasts and conduct structural analyses. Employing the PVAR model, impulse-response functions (IRFs) were analyzed to assess the impacts of economic shocks on pollution levels and the challenges these pose to both renewable and non-renewable energy sources. The analysis further involved the decomposition of variance among the variables. Key findings reveal that economic growth in these countries often correlates with increased use of carbon dioxide-emitting energies. However, the substitution of these energies with renewable sources is not only feasible but also pivotal for promoting environmental purification and sanitation through enhanced investments in renewable energies. Despite the theoretical potential for growth in the renewable sector, its actual development in these countries remains inadequate, and its contribution to fostering an ecological environment that supports economic growth is minimal. The study underscores the necessity of robust policies to facilitate ecological growth and the imperative of a shared commitment among nations to ensure the effectiveness of these policies.

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Section: Empirical Methodologymentioning

confidence: 99%

The Effects of Economic Cycle Shocks on Polluting Emissions in Developing Countries: Insights from a Panel Vector Autoregression Analysis

Fakhri,

Meshari,

Othayman

et al. 2024

CiS

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“…Jahanger et al [33] utilized the PVAR method to analyze the influence of economic development, transportation, renewable energy, and globalization on the tourism sector and carbon emissions in the region around the Bay of Bengal. Zhang et al [34] investigated the application of the PVAR model to analyze the relationship among economic growth, urbanization, energy consumption, and carbon emissions from 30 provinces in China. However, few studies have used the PVAR model to examine the decomposing driving effect of tourism transport CO 2 emissions.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In recent years, the panel vector autoregression (PVAR) model has been widely applied in economic research [32]. The PVAR model is an extension of the traditional vector autoregression (VAR) model, incorporating the advantages of both panel data analysis and VAR modeling [34]. The VAR model does not require the prior specification of causal relationships among variables [29].…”

Section: Pvar Modelmentioning

confidence: 99%

Tourism Transport-Related CO2 Emissions and Economic Growth: A Deeper Perspective from Decomposing Driving Effects

Yan,

Phucharoen

2024

Sustainability

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This study explores the intricate dynamics of CO2 emissions stemming from transport within the tourism sector. It aims to unravel the multidimensional aspects of how transport-related tourism contributes to CO2 emissions and to elucidate the complex relationship between regional economic growth and CO2 emissions from transport-related tourism. Our study employed Logarithmic Mean Divisia Index (LMDI) and Panel Vector Autoregression (PVAR) models to analyze data from 30 Chinese provincial regions between 2010 and 2018. The tourism transport-related CO2 emissions were decomposed into four separate driving effects using the LMDI approach. Then, PVAR models were constructed to reveal dynamic interactions between each driving effect and per capita gross regional product (GRP). Our results demonstrate a decrease in both energy structure effect (tourism transport-related CO2 emissions from energy structure) and energy intensity effect (tourism transport-related CO2 emissions from energy intensity) during the pre-COVID decade. Notably, the positive impulse response of energy structure effect to per capita GRP is observed. However, we found no evidence of a cointegrated relationship between energy intensity effect and regional economic growth, although other factors demonstrated connections. These findings echo the necessity to integrate sustainable practices into the tourism transportation business, especially in the area of energy structure, in order to mitigate adverse environmental effects from tourism. This paper disseminates the main drivers of CO2 emissions in the tourism transport sector and their interrelationship with regional economic growth. It not only guides tourism policymakers in targeting efforts to reduce carbon footprints, but also sets a new benchmark for future studies on CO2 emissions.

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Examining the decoupling relationship between new-type urbanization and carbon emissions and its driving factors in China: evidence from 260 cities

Li,

Lei,

Wang

2024

Stoch Environ Res Risk Assess

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Heterogeneous effects of urbanization, economic growth, and energy consumption on carbon emissions in China: evidence from a PVAR model

Cited by 6 publications

References 126 publications

The Effects of Economic Cycle Shocks on Polluting Emissions in Developing Countries: Insights from a Panel Vector Autoregression Analysis

The Effects of Economic Cycle Shocks on Polluting Emissions in Developing Countries: Insights from a Panel Vector Autoregression Analysis

Tourism Transport-Related CO2 Emissions and Economic Growth: A Deeper Perspective from Decomposing Driving Effects

Examining the decoupling relationship between new-type urbanization and carbon emissions and its driving factors in China: evidence from 260 cities

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