IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v104y2017icp404-414.html
   My bibliography  Save this article

Factors affecting CO2 emissions in China’s agriculture sector: Evidence from geographically weighted regression model

Author

Listed:
  • Xu, Bin
  • Lin, Boqiang

Abstract

China is currently the world's largest emitter of carbon dioxide. Considered as a large agricultural country, carbon emission in China’s agriculture sector keeps on growing rapidly. It is, therefore, of great importance to investigate the driving forces of carbon dioxide emissions in this sector. The traditional regression estimation can only get “average” and “global” parameter estimates; it excludes the “local” parameter estimates which vary across space in some spatial systems. Geographically weighted regression embeds the latitude and longitude of the sample data into the regression parameters, and uses the local weighted least squares method to estimate the parameters point–by–point. To reveal the nonstationary spatial effects of driving forces, geographically weighted regression model is employed in this paper. The results show that economic growth is positively correlated with emissions, with the impact in the western region being less than that in the central and eastern regions. Urbanization is positively related to emissions but produces opposite effects pattern. Energy intensity is also correlated with emissions, with a decreasing trend from the eastern region to the central and western regions. Therefore, policymakers should take full account of the spatial nonstationarity of driving forces in designing emission reduction policies.

Suggested Citation

  • Xu, Bin & Lin, Boqiang, 2017. "Factors affecting CO2 emissions in China’s agriculture sector: Evidence from geographically weighted regression model," Energy Policy, Elsevier, vol. 104(C), pages 404-414.
    • Handle: RePEc:eee:enepol:v:104:y:2017:i:c:p:404-414
    DOI: 10.1016/j.enpol.2017.02.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421517300861
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2017.02.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Shao, Shuai & Liu, Jianghua & Geng, Yong & Miao, Zhuang & Yang, Yingchun, 2016. "Uncovering driving factors of carbon emissions from China’s mining sector," Applied Energy, Elsevier, vol. 166(C), pages 220-238.
    2. Lin, Boqiang & Ahmad, Izhar, 2016. "Energy substitution effect on transport sector of Pakistan based on trans-log production function," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1182-1193.
    3. Ma, Shuzhong & Feng, Han, 2013. "Will the decline of efficiency in China's agriculture come to an end? An analysis based on opening and convergence," China Economic Review, Elsevier, vol. 27(C), pages 179-190.
    4. Zhao, Xingrong & Zhang, Xi & Shao, Shuai, 2016. "Decoupling CO2 emissions and industrial growth in China over 1993–2013: The role of investment," Energy Economics, Elsevier, vol. 60(C), pages 275-292.
    5. Shao, Shuai & Huang, Tao & Yang, Lili, 2014. "Using latent variable approach to estimate China׳s economy-wide energy rebound effect over 1954–2010," Energy Policy, Elsevier, vol. 72(C), pages 235-248.
    6. Nguyen Hoa & Tomoko Hasegawa & Yuzuru Matsuoka, 2014. "Climate change mitigation strategies in agriculture, forestry and other land use sectors in Vietnam," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 19(1), pages 15-32, January.
    7. Zhang, Chuanguo & Zhou, Xiangxue, 2016. "Does foreign direct investment lead to lower CO2 emissions? Evidence from a regional analysis in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 943-951.
    8. Livia Bizikova & Erica Crawford & Maria Nijnik & Rob Swart, 2014. "Climate change adaptation planning in agriculture: processes, experiences and lessons learned from early adapters," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 19(4), pages 411-430, April.
    9. Xu, Bin & Lin, Boqiang, 2016. "Regional differences in the CO2 emissions of China's iron and steel industry: Regional heterogeneity," Energy Policy, Elsevier, vol. 88(C), pages 422-434.
    10. Tendall, Danielle M. & Gaillard, Gérard, 2015. "Environmental consequences of adaptation to climate change in Swiss agriculture: An analysis at farm level," Agricultural Systems, Elsevier, vol. 132(C), pages 40-51.
    11. Zhang, Tonglin & Lin, Ge, 2016. "On Moran’s I coefficient under heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 83-94.
    12. Zhu, Shu & Xu, Xin & Ren, Xiaojing & Sun, Tianhua & Oxley, Les & Rae, Allan & Ma, Hengyun, 2016. "Modeling technological bias and factor input behavior in China's wheat production sector," Economic Modelling, Elsevier, vol. 53(C), pages 245-253.
    13. Xu, Bin & Lin, Boqiang, 2015. "How industrialization and urbanization process impacts on CO2 emissions in China: Evidence from nonparametric additive regression models," Energy Economics, Elsevier, vol. 48(C), pages 188-202.
    14. Esteve, Paloma & Varela-Ortega, Consuelo & Blanco-Gutiérrez, Irene & Downing, Thomas E., 2015. "A hydro-economic model for the assessment of climate change impacts and adaptation in irrigated agriculture," Ecological Economics, Elsevier, vol. 120(C), pages 49-58.
    15. Monchuk, Daniel C. & Chen, Zhuo & Bonaparte, Yosef, 2010. "Explaining production inefficiency in China's agriculture using data envelopment analysis and semi-parametric bootstrapping," China Economic Review, Elsevier, vol. 21(2), pages 346-354, June.
    16. Mardani, Aref & Taghavifar, Hamid, 2016. "An overview on energy inputs and environmental emissions of grape production in West Azerbayjan of Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 918-924.
    17. Xu, Bin & Lin, Boqiang, 2016. "A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie?," Energy Policy, Elsevier, vol. 98(C), pages 328-342.
    18. Viet-Ngu Hoang & Mohammad Alauddin, 2012. "Input-Orientated Data Envelopment Analysis Framework for Measuring and Decomposing Economic, Environmental and Ecological Efficiency: An Application to OECD Agriculture," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 51(3), pages 431-452, March.
    19. Fan, Meiting & Shao, Shuai & Yang, Lili, 2015. "Combining global Malmquist–Luenberger index and generalized method of moments to investigate industrial total factor CO2 emission performance: A case of Shanghai (China)," Energy Policy, Elsevier, vol. 79(C), pages 189-201.
    20. Dogan, Eyup & Sebri, Maamar & Turkekul, Berna, 2016. "Exploring the relationship between agricultural electricity consumption and output: New evidence from Turkish regional data," Energy Policy, Elsevier, vol. 95(C), pages 370-377.
    21. Li, Ke & Lin, Boqiang, 2016. "Impact of energy technology patents in China: Evidence from a panel cointegration and error correction model," Energy Policy, Elsevier, vol. 89(C), pages 214-223.
    22. Xu, Bin & Lin, Boqiang, 2015. "Carbon dioxide emissions reduction in China's transport sector: A dynamic VAR (vector autoregression) approach," Energy, Elsevier, vol. 83(C), pages 486-495.
    23. Julian Ramirez-Villegas & Mike Salazar & Andy Jarvis & Carlos Navarro-Racines, 2012. "A way forward on adaptation to climate change in Colombian agriculture: perspectives towards 2050," Climatic Change, Springer, vol. 115(3), pages 611-628, December.
    24. Robaina-Alves, Margarita & Moutinho, Victor, 2014. "Decomposition of energy-related GHG emissions in agriculture over 1995–2008 for European countries," Applied Energy, Elsevier, vol. 114(C), pages 949-957.
    25. Isa Yunusa & Graeme Blair & Ayalsew Zerihun & Shenjiao Yang & Susan Wilson & Iain Young, 2015. "Enhancing carbon sequestration in soil with coal combustion products: a technology for minimising carbon footprints in coal-power generation and agriculture," Climatic Change, Springer, vol. 131(4), pages 559-573, August.
    26. Fais, Birgit & Sabio, Nagore & Strachan, Neil, 2016. "The critical role of the industrial sector in reaching long-term emission reduction, energy efficiency and renewable targets," Applied Energy, Elsevier, vol. 162(C), pages 699-712.
    27. Xianwei Fan & Dan Zheng & Minjun Shi, 2016. "How Does Land Development Promote China’s Urban Economic Growth? The Mediating Effect of Public Infrastructure," Sustainability, MDPI, vol. 8(3), pages 1-12, March.
    28. Lin, Boqiang & Liu, Chang, 2016. "Why is electricity consumption inconsistent with economic growth in China?," Energy Policy, Elsevier, vol. 88(C), pages 310-316.
    29. Shao, Shuai & Yang, Lili & Gan, Chunhui & Cao, Jianhua & Geng, Yong & Guan, Dabo, 2016. "Using an extended LMDI model to explore techno-economic drivers of energy-related industrial CO2 emission changes: A case study for Shanghai (China)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 516-536.
    30. Sebri, Maamar & Abid, Mehdi, 2012. "Energy use for economic growth: A trivariate analysis from Tunisian agriculture sector," Energy Policy, Elsevier, vol. 48(C), pages 711-716.
    31. Wesseh, Presley K. & Lin, Boqiang, 2016. "Output and substitution elasticities of energy and implications for renewable energy expansion in the ECOWAS region," Energy Policy, Elsevier, vol. 89(C), pages 125-137.
    32. Cheung, Grace & Davies, Peter J. & Trück, Stefan, 2016. "Financing alternative energy projects: An examination of challenges and opportunities for local government," Energy Policy, Elsevier, vol. 97(C), pages 354-364.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lin, Boqiang & Xu, Bin, 2018. "Factors affecting CO2 emissions in China's agriculture sector: A quantile regression," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 15-27.
    2. Xu, Bin & Lin, Boqiang, 2016. "A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie?," Energy Policy, Elsevier, vol. 98(C), pages 328-342.
    3. Rafiq, Shuddhasattwa & Nielsen, Ingrid & Smyth, Russell, 2017. "Effect of internal migration on the environment in China," Energy Economics, Elsevier, vol. 64(C), pages 31-44.
    4. Wen, Hong-xing & Chen, Zhe & Yang, Qian & Liu, Jin-yi & Nie, Pu-yan, 2022. "Driving forces and mitigating strategies of CO2 emissions in China: A decomposition analysis based on 38 industrial sub-sectors," Energy, Elsevier, vol. 245(C).
    5. Zhen, Wei & Qin, Quande & Miao, Lu, 2023. "The greenhouse gas rebound effect from increased energy efficiency across China's staple crops," Energy Policy, Elsevier, vol. 173(C).
    6. Chao-Qun Ma & Jiang-Long Liu & Yi-Shuai Ren & Yong Jiang, 2019. "The Impact of Economic Growth, FDI and Energy Intensity on China’s Manufacturing Industry’s CO 2 Emissions: An Empirical Study Based on the Fixed-Effect Panel Quantile Regression Model," Energies, MDPI, vol. 12(24), pages 1-16, December.
    7. Jialing Zou & Zhipeng Tang & Shuang Wu, 2019. "Divergent Leading Factors in Energy-Related CO 2 Emissions Change among Subregions of the Beijing–Tianjin–Hebei Area from 2006 to 2016: An Extended LMDI Analysis," Sustainability, MDPI, vol. 11(18), pages 1-17, September.
    8. Lin, Boqiang & Xu, Bin, 2018. "How to promote the growth of new energy industry at different stages?," Energy Policy, Elsevier, vol. 118(C), pages 390-403.
    9. Liang, Wei & Gan, Ting & Zhang, Wei, 2019. "Dynamic evolution of characteristics and decomposition of factors influencing industrial carbon dioxide emissions in China: 1991–2015," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 93-106.
    10. Wang, Juan & Hu, Mingming & Rodrigues, João F.D., 2018. "The evolution and driving forces of industrial aggregate energy intensity in China: An extended decomposition analysis," Applied Energy, Elsevier, vol. 228(C), pages 2195-2206.
    11. Zhang, Xi & Geng, Yong & Shao, Shuai & Dong, Huijuan & Wu, Rui & Yao, Tianli & Song, Jiekun, 2020. "How to achieve China’s CO2 emission reduction targets by provincial efforts? – An analysis based on generalized Divisia index and dynamic scenario simulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    12. Hua Zhang & Sidai Guo & Yubing Qian & Yan Liu & Chengpeng Lu, 2020. "Dynamic analysis of agricultural carbon emissions efficiency in Chinese provinces along the Belt and Road," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-22, February.
    13. Xu, Bin & Lin, Boqiang, 2017. "Assessing CO2 emissions in China's iron and steel industry: A nonparametric additive regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 325-337.
    14. Xie, Xuan & Shao, Shuai & Lin, Boqiang, 2016. "Exploring the driving forces and mitigation pathways of CO2 emissions in China’s petroleum refining and coking industry: 1995–2031," Applied Energy, Elsevier, vol. 184(C), pages 1004-1015.
    15. Ying Han & Baoling Jin & Xiaoyuan Qi & Huasen Zhou, 2021. "Influential Factors and Spatiotemporal Characteristics of Carbon Intensity on Industrial Sectors in China," IJERPH, MDPI, vol. 18(6), pages 1-18, March.
    16. Shumin Jiang & Chen Yang & Jingtao Guo & Zhanwen Ding & Lixin Tian & Jianmei Zhang, 2017. "Uncovering the Driving Factors of Carbon Emissions in an Investment Allocation Model of China’s High-Carbon and Low-Carbon Energy," Sustainability, MDPI, vol. 9(6), pages 1-15, June.
    17. Yang, Zhenbing & Shao, Shuai & Yang, Lili & Miao, Zhuang, 2018. "Improvement pathway of energy consumption structure in China's industrial sector: From the perspective of directed technical change," Energy Economics, Elsevier, vol. 72(C), pages 166-176.
    18. Liu, Wei & Zhan, Jinyan & Zhao, Fen & Wang, Pei & Li, Zhihui & Teng, Yanmin, 2018. "Changing trends and influencing factors of energy productivity growth: A case study in the Pearl River Delta Metropolitan Region," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 1-9.
    19. Chen, Jiandong & Wang, Ping & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2018. "Decomposition and decoupling analysis of CO2 emissions in OECD," Applied Energy, Elsevier, vol. 231(C), pages 937-950.
    20. Fang, Debin & Hao, Peng & Yu, Qian & Wang, Jiancheng, 2020. "The impacts of electricity consumption in China's key economic regions," Applied Energy, Elsevier, vol. 267(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:104:y:2017:i:c:p:404-414. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.