Dynamic analysis of spatial convergence of green total factor productivity in China’s primary provinces along its Belt and Road Initiative

Liu, Zuankuo; Li, Xin

doi:10.1080/10042857.2019.1611342

Cited by 29 publications

(12 citation statements)

References 11 publications

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“…Incorporating undesired outputs is widely adopted by academia, and typical undesired outputs include energy consumption and three wastes. Liu and Xin (2019) advanced this concept by proposing a measurement index of GTFP and dynamically analyzed spatial convergence. GTFP reflects the degree of high-quality development of the manufacturing industry, which is directly related to the sustainable economic and environmental development of a country.…”

Section: Literature Reviewmentioning

confidence: 99%

Path to sustainable development: Does digital economy matter in manufacturing green total factor productivity?

Hao

Wang

et al. 2022

Sustainable Development

108

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In the context of the outbreak of the COVID-19 pandemic and China's "digital power" strategy, the realization of a green shift of manufacturing has become a necessary condition to promote the economy, and the digital factor has increasingly become a new driving force. The DEA-Malmquist index and entropy method were used to measure the manufacturing green total factor productivity (GTFP) and the level of digital economy level from 2011 to 2018, respectively. This study then

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Section: Literature Reviewmentioning

confidence: 99%

Path to sustainable development: Does digital economy matter in manufacturing green total factor productivity?

Hao

Wang

et al. 2022

Sustainable Development

108

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“…In light of this, a major area of research has recently focused on assessing energy efficiency performance within the BRI region [4][5][6][7]. However, these researchers have failed to distinguish between transient and persistent energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

Estimating Persistent and Transient Energy Efficiency in Belt and Road Countries: A Stochastic Frontier Analysis

et al. 2020

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In this paper, we examine the energy efficiency performance of the Belt and Road Initiative (BRI) countries using a newly developed panel data stochastic frontier model that allows for estimation of both persistent and transient efficiency while controlling for random country effects and noise. By this, we contribute to the energy economic literature by providing a complete picture of the level of persistent, transient, and total energy efficiency estimates from a cross country perspective for a panel of 48 BRI countries during the period 1990–2015. Adding that there is little evidence to support energy efficiency convergence in the energy economic literature, we went further to check whether energy efficiency converges in the BRI countries. The results show that (1) persistent efficiencies are much lower than transient efficiencies, suggesting that the energy problem in the BRI countries is more of a structural issue; (2) while energy efficiency varies widely across the countries, high-income countries perform better than the lower-income countries; (3) there is evidence of efficiency convergence and it accelerates when trade increases, but decreases when the industrial sector increases. Based on these findings, we propose some policy implications.

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“…Ang and Kerstens (2017) introduced a decomposition of the additively complete Luenberger-Hicks-Moorsteen TFP indicator in the US agriculture. Liu and Xin (2019) performed the dynamic analysis on the TFP along the Belt and Road Initiative. However, the existing literature focuses on the sources of the productivity growth and ignores the variable-specific decomposition.…”

Section: Introductionmentioning

confidence: 99%

Industrial energy consumption and pollutant emissions: Combined decomposition of relative performance and absolute changes

et al. 2022

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Combined decomposition of relative productivity growth and absolute changes in input/output variables helps to identify the driving forces of energy conservation and emission reduction. This paper proposes a framework based on the Luenberger productivity indicator (LPI) and the logarithmic mean Divisia index (LMDI) approach to analyze the energy–economy–environment nexus. The empirical case of the China's industrial sector for 2006–2014 is analyzed. Following this approach, we present a variable‐specific decomposition framework which attributes the overall productivity change and its sources to individual input/output variables. Empirically, we examine the relationships between the productivity growth and energy consumption within the LPI–LMDI framework across China's province‐level regions. The results show important spatial variation in the productivity measures. The LPI–LMDI decomposition implies that the industrial energy consumption increased with productivity growth appearing as the only mitigating factor. As regards the industrial SO2 emission, the individual productivity growth effect and the efficiency change effect remained as suppressing factors for emission abatement. These results can be used for evidence‐based decision making.

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Dynamic analysis of spatial convergence of green total factor productivity in China’s primary provinces along its Belt and Road Initiative

Cited by 29 publications

References 11 publications

Path to sustainable development: Does digital economy matter in manufacturing green total factor productivity?

Path to sustainable development: Does digital economy matter in manufacturing green total factor productivity?

Estimating Persistent and Transient Energy Efficiency in Belt and Road Countries: A Stochastic Frontier Analysis

Industrial energy consumption and pollutant emissions: Combined decomposition of relative performance and absolute changes

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