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Energy-biased technical change in the Chinese industrial sector with CES production functions

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  • Zha, Donglan
  • Kavuri, Anil Savio
  • Si, Songjian

Abstract

We develop a theoretical framework to study energy-biased technical change considering capital, labor and energy as inputs. The framework involves a first order condition estimation of elasticity and technical change parameters for a three factor-nested Constant Elasticity of Substitution (CES) function. Technical change parameters, elasticities and time derivatives of marginal products are combined to compute technical change bias. Conceptually, we introduce total bias in order to estimate the direction without requiring a direct comparison with another factor. For Chinese industries from 1990 to 2012, the optimal structure is capital and energy to be combined at the composite level and then with labor to form total output. Technical change is found to be unambiguously energy biased, it increases in every year, and the bias is predominately away from labor. The results show that Chinese industrialization was fuelled by fossil fuels and energy-intensive technologies. Nonetheless, the growth rate of energy-biased technical change decreased during the 2000s that may result from more energy efficient development.

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  • Zha, Donglan & Kavuri, Anil Savio & Si, Songjian, 2018. "Energy-biased technical change in the Chinese industrial sector with CES production functions," Energy, Elsevier, vol. 148(C), pages 896-903.
    • Handle: RePEc:eee:energy:v:148:y:2018:i:c:p:896-903
    DOI: 10.1016/j.energy.2017.11.087
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    5. Cheng, Maolin & Han, Yun, 2020. "Application of a modified CES production function model based on improved PSO algorithm," Applied Mathematics and Computation, Elsevier, vol. 387(C).
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