Skip to main content

Advertisement

SpringerLink
Log in

Economic growth of green agriculture and its influencing factors in china: Based on emergy theory and spatial econometric model

  • Published:
Environment, Development and Sustainability Aims and scope Submit manuscript

Abstract

Based on emergy theory, this paper calculates the agricultural green GDP of China and its provincial units from 2003 to 2018. Following this, the spatial distribution characteristics and influencing factors of the economic growth of green agriculture in China are studied using the spatial analysis method. The results show that: (1) Compared with the traditional GDP derived from agriculture, the per capita green agriculture GDP growth in China is relatively slow, and the proportion of green agriculture GDP to the traditional GDP from agriculture is between 85 and 91%, which shows a downward trend. (2) The economic growth of China's green agriculture manifests significant spatial agglomeration, with gradually growing effects. (3) The per capita GDP of green agriculture has not broken the overall pattern of high economic growth in China’s eastern regions and low growth in the western. According to the results, the major cause of this spatial pattern lay in the higher efficiency of agricultural production in the eastern, economically more developed areas, and the relatively less efficient mode of production in the western areas. (4) A region’s level of economic development, technological innovation, infrastructure investment and openness were found to have a positive impact on the growth of green agriculture within it. In previous research, emergy methods have not been applied to study the economic sectors in China, the largest developing country in the world, especially in the agricultural sector. Only few studies report on the analysis of spatial characteristics and factors influencing the growth of green agriculture. The agricultural green GDP was calculated based on the emergy analysis method. The temporal and spatial characteristics, as well as the driving factors of green agriculture GDP, were analyzed under the full consideration of the spatial correlation, which contributes to the theoretical explanation of spatial agglomeration of economic factors in spatial economic theory. The conclusions provide a theoretical and practical basis for accurate evaluation of the green growth of China's agricultural economy, optimization of the spatial structure of the country’s green agricultural economy and coordination of the development of green agriculture in different regions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Anselin, L. (2013). Spatial econometrics: methods and models (Vol. 4). Springer Science & Business Media.

    Google Scholar 

  • Chen, F. (2004). Agricultural ecology. China Agricultural University Press.

    Google Scholar 

  • Chen, Y.-h, Wen, X.-w, Wang, B., & Nie, P.-y. (2017). Agricultural pollution and regulation: How to subsidize agriculture? Journal of Cleaner Production, 164, 258–264. https://doi.org/10.1016/j.jclepro.2017.06.216

    Article  Google Scholar 

  • Chen, W., et al. (2018). An emergy accounting based regional sustainability evaluation: A case of Qinghai in China. Ecological Indicators, 88, 152–160. https://doi.org/10.1016/j.ecolind.2017.12.069

    Article  Google Scholar 

  • Chen, D., Zhang, P., Luo, Z., Cao, X., & Wang, W. (2019). Discussion of the study on sustainability of land resources in Dengkou County based on emergy analysis. Journal of Cleaner Production, 206, 724–726. https://doi.org/10.1016/j.jclepro.2018.09.230

    Article  Google Scholar 

  • Cheng, H., Chen, C., Wu, S., Mirza, Z. A., & Liu, Z. (2017). Emergy evaluation of cropping, poultry rearing, and fish raising systems in the drawdown zone of Three Gorges Reservoir of China. Journal of Cleaner Production, 144, 559–571. https://doi.org/10.1016/j.jclepro.2016.12.053

    Article  Google Scholar 

  • Franzluebbers, A. J., Lemaire, G., de Faccio Carvalho, P. C., Sulc, R. M., & Dedieu, B. (2014). Toward agricultural sustainability through integrated crop-livestock systems: environmental outcomes agriculture. Ecosystems & Environment, 190, 1–3. https://doi.org/10.1016/j.agee.2014.04.028

    Article  Google Scholar 

  • Geng, Y., Zhang, P., Ulgiati, S., & Sarkis, J. (2010). Emergy analysis of an industrial park: The case of Dalian. China Science of The Total Environment, 408, 5273–5283. https://doi.org/10.1016/j.scitotenv.2010.07.081

    Article  CAS  Google Scholar 

  • Graff Zivin, J., & Neidell, M. (2012). The impact of pollution on worker productivity. American Economic Review, 102, 3652–3673. https://doi.org/10.1257/aer.102.7.3652

    Article  Google Scholar 

  • Guo, L. Y., Lei, M., & Liu, X. Q. (2015). Green GDP accounting research based on emergy analysis method:a case study of shangluo city in Shanxi province. Journal of natural resources, 30, 1523–1533. https://doi.org/10.11849/zrzyxb.2015.09.009.

    Article  Google Scholar 

  • Hansen, M. H., Li, H., & Svarverud, R. (2018). Ecological civilization: Interpreting the Chinese past, projecting the global future. Global Environmental Change, 53, 195–203. https://doi.org/10.1016/j.gloenvcha.2018.09.014

    Article  Google Scholar 

  • He, L. Y., Zhang, L. H., & Zhong, Z. Q. (2019). Green credit, renewable energy investment and green economy development, Empirical analysis based on 150 listed companies of China. Journal of Cleaner Production, 208, 363–372. https://doi.org/10.1016/j.jclepro.2018.10.119

    Article  Google Scholar 

  • HoATEE, B. (1984). Handbook of agricultural technology economics. Agriculture Press.

  • Huang, A. S., Xu, J. X., Liu, Z. B., Huang, S. W., & Wang, Q. Q. (2014). China green agriculture technology and provincial difference analysis efficiency– Based on panel data from 1998 to 2012. Journal of Hunan Agricultural University (Social Sciences), 15, 68–75. https://doi.org/10.13331/j.cnki.jhau(ss).2014.04.011

    Article  Google Scholar 

  • Kamp, A., Morandi, F., & Østergård, H. (2016). Development of concepts for human labour accounting in emergy assessment and other environmental sustainability assessment methods. Ecological Indicators, 60, 884–892. https://doi.org/10.1016/j.ecolind.2015.08.011

    Article  Google Scholar 

  • Lan, S., & Qin, P. (2001). Emergy analysis of ecosystems. Chinese Journal of Applied Ecology, 12, 129–131.

    CAS  Google Scholar 

  • Lee, Y.-C., & Huang, S.-L. (2018). Spatial emergy analysis of agricultural landscape change: Does fragmentation matter? Ecological Indicators, 93, 975–985. https://doi.org/10.1016/j.ecolind.2018.05.067

    Article  Google Scholar 

  • LeSage, J. P., & Sheng, Y. (2014). A spatial econometric panel data examination of endogenous versus exogenous interaction in Chinese province-level patenting. Journal of Geographical Systems, 16, 233–262.

    Article  Google Scholar 

  • Li, J., et al. (2018). Exploring the socioeconomic and ecological consequences of cash crop cultivation for policy implications. Land Use Policy, 76, 46–57. https://doi.org/10.1016/j.landusepol.2018.04.009

    Article  Google Scholar 

  • Liang LT (2009) Study on the temporal and spatial evolution of rural ecological environment. Master’s Thesis of Nanjing Agricultural University

  • Liu XY (2014) Spatial efficiency and regional balance, an examination of the agglomeration effect at the provincial level in China The Journal of World Economy:55–80

  • Lu, M., & Xiang, K. H. (2012). Geography and service, does domestic demand disperse China’s urban system? China Economic Quarterly, 113, 1079–1096.

    Google Scholar 

  • Moyo, T. (2014). Green economy/growth policies and their implementation in the context of the renewable energy sector: The case of Mozambique South Africa and Zimbabwe. International Journal of African Renaissance Studies-Multi-, Inter-and Transdisciplinarity, 9, 39–60. 10(1080/18186874),pp.987954,2014.

    Article  Google Scholar 

  • Odum, H. T. (1996). Environmental accounting: emergy and environmental decision making. Wiley.

    Google Scholar 

  • Pan, D., & Ying, R. Y. (2013). Agricultural Total Factor Productivity Growth in China under the Binding of Resource and Environment Resources. Science, 35, 1329–1338.

    Google Scholar 

  • Parent, O., & LeSage, J. P. (2008). Using the variance structure of the conditional autoregressive spatial specification to model knowledge spillovers. Journal of Applied Econometrics, 23, 235–256. https://doi.org/10.1002/jae.981

    Article  Google Scholar 

  • Rehman, A., Jingdong, L., Chandio, A. A., & Hussain, I. (2017). Livestock production and population census in Pakistan: Determining their relationship with agricultural GDP using econometric analysis. Information Processing in Agriculture, 4, 168–177.

    Article  Google Scholar 

  • Viglia, S., Civitillo, D. F., Cacciapuoti, G., & Ulgiati, S. (2018). Indicators of environmental loading and sustainability of urban systems. An emergy-based environmental footprint Ecological indicators, 94, 82–99. https://doi.org/10.1016/j.ecolind.2017.03.060

    Article  Google Scholar 

  • Voumik, L. C., & Shah, M. G. H. (2014). A green economy in the context of sustainable development and poverty eradication: what are the implications for Bangladesh? Journal of Economics and Sustainable Development, 5, 119–131.

    Google Scholar 

  • Yan LD (2003) Green agriculture development and financial support Issues In Agricultural Economy:36–39. doi: https://doi.org/10.3969/j.issn.1000-6389.2003.10.007

  • Yingling, A. E. (2010). An assessment of the green economy in the upper coastal plain region of North Carolina. Chemical Engineering Science, 20, 443–444. https://doi.org/10.1002/psp.391

    Article  Google Scholar 

  • Zhang XX, Feng ZX (2008) Spatial Correlation and Regional Convergence in per capita GDP in China, 1978–2003 China Economic Quarterly:399–414

  • Zhang, H., Huang, M. S., & Hu, H. U. (2010). Green GDP calculation of Fujian province based on energy analysis. Acta Geographica Sinica, 65, 1421–1428. https://doi.org/10.11821/xb201011012

    Article  Google Scholar 

Download references

Funding

This project has received funding from National Natural Science Foundation of China (Noss. 71803145 and 71933004).

Author information

Authors and Affiliations

  1. College of Law and Business, Wuhan Institute of Technology, Wuhan, 430205, China

    Zhaoliang Li, Minghao Jin & Jianwei Cheng

Authors
  1. Zhaoliang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Minghao Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jianwei Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Minghao Jin.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Z., Jin, M. & Cheng, J. Economic growth of green agriculture and its influencing factors in china: Based on emergy theory and spatial econometric model. Environ Dev Sustain 23, 15494–15512 (2021). https://doi.org/10.1007/s10668-021-01307-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10668-021-01307-1

Keywords

Search

Navigation