Quantifying the role of technical progress towards China’s 2030 carbon intensity target

Abstract

This paper constructs a dynamic computable general equilibrium (DCGE) model to investigate the macroeconomic effects of endogenous technical progress in achieving China’s 2030 carbon intensity reduction target of 60–65% compared with 2005. We show that a combination of a carbon tax and technological progress can achieve the carbon intensity target in 2030, but it will exert a negative impact on economic growth. This negative effect, however, can be relieved by endogenously directed technological progress in the long term. In doing so, industrial structure and energy structure are dynamically adjusted by inhibiting the output and employment of the coal and oil sectors but promoting that of the clean energy and the service industry. We also find that with technological progress, the unit carbon abatement cost in the long term is estimated to be 200–250 yuan/ton, much lower than that in the short term (over 367 yuan/ton). Several policy implications are discussed accordingly.

Keywords:

• technological progress
• carbon emission intensity
• dynamic CGE model
• carbon tax
• carbon abatement cost

Acknowledgements

We thank the editor, Neil Powe, and the referee for their helpful comments. We thank Professor Weixian WEI and Dr. Xili MA for their help.

Disclosure statement

We declare that we have no competing financial, professional, or personal interests from other parties.

Notes

1 The data are from the world development indicators. See: https://data.worldbank.org/products/wdi.

2 Other solutions are also discussed in the literature, for instance, improving energy efficiency, namely, reducing energy use per unit production (Inglesi-Lotz and Pouris 2012; Shahbaz et al. 2015; Tajudeen, Wossink, and Banerjee 2018); changing energy consumption structure (Akalpler and Shingil 2017; Štreimikienė 2013); and making use of technology transfers from international trade (Haug and Ucal 2019; Kirkpatrick and Scrieciu 2008; Xie et al. 2013).

3 See: www.pep-net.org.

4 Note also that the revenue due to carbon taxation is taken as the government’s income as other taxation, which could be used in lump-sum transfers to consumers and enterprises and in fiscal spending.

5 For more detailed analysis, please refer to Figure 1 in Gerlagh and Kuik (2014).

6 Find more details in Gerlagh and Kuik (2014).

7 However, the increased elasticity of substitution is not a free lunch. It merely reflects additional flexibility in economic production, as much as that we typically assume a higher elasticity of substitution between inputs before the choice of machines is fixed and a lower elasticity of substitution between input factors after the physical capital stock has been installed. Furthermore, the increased substitution probability does not necessarily mean the change of use of input mix in the final production. Rather, the use of input mix is endogenously determined by the relative price between factors, which depends on the input productivity and scarcity in the market. In this sense, technological progress is endogenous, since input mix endogenously responds to the increased elasticity of substitution due to the changes of relative price in the economic system. The same idea is – in a dynamic context – presented in Wing (2006).

8 https://www.ipcc-nggip.iges.or.jp/public/2006gl/

9 National Bureau of Statistics. China Input-Output Table 2012. Beijing: China Statistics Press 2013

10 The data are sourced from the World Bank.

Additional information

Funding

This work was supported by the China Postdoctoral Science Foundation under Grant [No. 2019M650945].