2019
DOI: 10.3390/su11236809
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Carbon Sequestration Total Factor Productivity Growth and Decomposition: A Case of the Yangtze River Economic Belt of China

Abstract: To find out whether carbon sequestration is both effective at mitigating climate change and promoting economic growth, in this paper, by adopting a stochastic frontier panel model with translog production function, carbon sequestration is incorporated into endogenous variables to establish estimation model of carbon sequestration total factor productivity (CSTFP) and examine CSTFP growth and its drivers decomposition of the Yangtze River Economic Belt (YREB) of China in three estimations. The result shows that… Show more

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Cited by 6 publications
(4 citation statements)
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“…The "Energy Productivity" indicator is another indicator making up the Resource Efficiency Scoreboard to control resource-efficient Europe, complementing the carbon index [18].…”
Section: Energy Productivitymentioning
confidence: 99%
“…The "Energy Productivity" indicator is another indicator making up the Resource Efficiency Scoreboard to control resource-efficient Europe, complementing the carbon index [18].…”
Section: Energy Productivitymentioning
confidence: 99%
“…By introducing a composite error term that included individual technical efficiency, the authors estimated a frontier production function that explained the variance across individuals. The main benefit of this formulation is that it allows the maximum achievable output to be estimated given a set of inputs, thereby providing a more precise definition of the production function and the determinants of growth (Mastromarco 2008;Rao et al 2019). The economic rationale of such an approach, as shown by Aigner et al (1977), relies on considering elements which the individual economic agent can directly manage (such as production factors) together with elements that remain outside the agent's direct sphere of control.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In most of the applied SFA modelling literature, the parameters of interest to be estimated are those contained in the technology vector β in Eq. ( 2), since they represent the marginal contribution of each production input (Rao et al 2019). However, in our case, the relevant parameters are those of the variables representing environmental externalities (γ j and δ k ) since they represent the quantified effect of CO 2 emissions and material extraction on GDP.…”
Section: Model Descriptionmentioning
confidence: 99%
“…On the basis of DEA-Malmquist, Xue et al [33] selected three indicators, i.e., forestry fixed asset, forestry employees, and forest area as inputs, with forestry output value and carbon sequestration as outputs, and then analyzed the forestry carbon sequestration performance of four major forest regions in China from 1988 to 2013. In a study of Rao et al [34], based on the SFA with Translog production function, carbon sequestration was incorporated as an endogenous variable to estimate the carbon sequestration total factor productivity of the Yangtze River Economic Belt of China. Li et al [35] used DEA to measure the performance of net carbon sequestration of the provincial agriculture in China from 2005 to 2017, suggesting that an uneven regional development existed, with the performance in the eastern region being significantly better than in other regions.…”
Section: Introductionmentioning
confidence: 99%