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The Impact of Agricultural Production Efficiency on Agricultural Carbon Emissions in China

Author

Listed:
  • Yong Zhu

    (School of Business, Hunan University of Science and Technology (HNUST), Xiangtan 411201, China)

  • Congjia Huo

    (School of Business, Hunan University of Science and Technology (HNUST), Xiangtan 411201, China)

Abstract
With the rapid development of China’s economy, China has become the world’s largest carbon emitter. China not only has an obvious growth rate of industrial carbon emissions but also the intensity of agricultural carbon emissions is hovering at a high level. The development of China’s agricultural economy has largely come at the expense of high emissions. Currently, under the background of global warming and difficulty in controlling greenhouse gas emissions, the development of low-carbon agriculture is an important way to realize the harmonious development of the ecological environment and economic growth and to promote the sustainable development of agriculture. The agricultural production efficiency is the main factor affecting the intensity of agricultural carbon emissions. Based on provincial panel data of China from 2010 to 2019, this paper establishes an indicator system and uses the super-efficiency SBM model to measure agricultural production efficiency. The regional agricultural carbon emissions were estimated using carbon-emission-related agricultural production activities. In order to study the nonlinear relationship between agricultural production efficiency and agricultural carbon emission intensity in the narrow sense, this paper uses a threshold regression model with agricultural carbon emissions as the threshold variable. Based on the analysis of China’s agricultural production efficiency and agricultural carbon emissions from 2010 to 2019, an empirical test is conducted through a threshold regression model. The results show an “inverted U-shaped” relationship between agricultural production efficiency and agricultural carbon emission intensity. In areas with high agricultural production efficiency, the improvement of production efficiency can suppress the intensity of agricultural carbon emissions; in areas with low agricultural production efficiency, the improvement of production efficiency increases the intensity of agricultural carbon emissions. Finally, based on the research conclusions, this paper provides feasible suggestions and countermeasures for China’s agricultural carbon emission reduction and improvement of agricultural production efficiency.

Suggested Citation

  • Yong Zhu & Congjia Huo, 2022. "The Impact of Agricultural Production Efficiency on Agricultural Carbon Emissions in China," Energies, MDPI, vol. 15(12), pages 1-22, June.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4464-:d:842419
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    References listed on IDEAS

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    1. Gerlagh, Reyer, 2007. "Measuring the value of induced technological change," Energy Policy, Elsevier, vol. 35(11), pages 5287-5297, November.
    2. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    3. Dominic Moran & Michael Macleod & Eileen Wall & Vera Eory & Alistair McVittie & Andrew Barnes & Robert Rees & Cairistiona F. E. Topp & Andrew Moxey, 2011. "Marginal Abatement Cost Curves for UK Agricultural Greenhouse Gas Emissions," Journal of Agricultural Economics, Wiley Blackwell, vol. 62(1), pages 93-118, February.
    4. MacLeod, Michael & Moran, Dominic & Eory, Vera & Rees, R.M. & Barnes, Andrew & Topp, Cairistiona F.E. & Ball, Bruce & Hoad, Steve & Wall, Eileen & McVittie, Alistair & Pajot, Guillaume & Matthews, Rob, 2010. "Developing greenhouse gas marginal abatement cost curves for agricultural emissions from crops and soils in the UK," Agricultural Systems, Elsevier, vol. 103(4), pages 198-209, May.
    5. Goksel Armagan & Altug Ozden & Selim Bekcioglu, 2010. "Efficiency and total factor productivity of crop production at NUTS1 level in Turkey: Malmquist index approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(3), pages 573-581, April.
    6. Tom Broekel & Ron Boschma, 2012. "Knowledge networks in the Dutch aviation industry: the proximity paradox," Journal of Economic Geography, Oxford University Press, vol. 12(2), pages 409-433, March.
    7. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    8. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    9. Pamuk, Haki & Bulte, Erwin & Adekunle, Adewale A., 2014. "Do decentralized innovation systems promote agricultural technology adoption? Experimental evidence from Africa," Food Policy, Elsevier, vol. 44(C), pages 227-236.
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