IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i11p6612-d826832.html
   My bibliography  Save this article

Evaluating the Heterogeneity Effect of Fertilizer Use Intensity on Agricultural Eco-Efficiency in China: Evidence from a Panel Quantile Regression Model

Author

Listed:
  • Mengyang Hou

    (School of Economics, Hebei University, Baoding 071000, China
    Center of Resources Utilization and Environmental Conservation, Hebei University, Baoding 071000, China)

  • Zenglei Xi

    (School of Economics, Hebei University, Baoding 071000, China
    Center of Resources Utilization and Environmental Conservation, Hebei University, Baoding 071000, China)

  • Suyan Zhao

    (School of Management, Hebei GEO University, Shijiazhuang 050031, China
    Natural Resource Asset Capital Research Center, Hebei GEO University, Shijiazhuang 050031, China)

Abstract

Chemical fertilizer is one of the most important input factors in agricultural production, but the excessive use of fertilizer inevitably leads to the loss of agricultural eco-efficiency (AEE). Therefore, it is necessary to explore the impact of fertilizer use intensity (FUI) on AEE. However, ordinary panel regression, based on the assumption of parameter homogeneity may yield biased estimation conclusions. In this regard, a panel quantile regression model (QRM) was constructed with the provincial panel data of China from 1978–2020 to test the difference and variation of this impact under heterogeneous conditions. The model was then combined with the spatial econometric model to explore the effect of the spatial lag factor. The results are as follows: (1) The QSM has unveiled a great improvement space for AEE that remains low overall, despite displaying a rising trend; the highest AEE is in the eastern region. (2) The FUI has a significant negative effect on AEE with the rise in quantiles, this negative effect tended towards weakening overall, although it rebounded slightly; it was stronger in areas with low AEE. It is necessary to consider the heterogeneous conditions in comparison with the average treatment effect of ordinary panel econometric regressions. (3) The impact of FUI shows significant variability in different economic sub-divisions and different sub-periods. (4) After considering the spatial effect of fertilizer use, the negative influence on local AEE had a faster decay rate as the quantile rose, but could produce a positive spatial spillover effect on AEE in neighboring areas. Local governments should dynamically adjust and optimize their fertilizer reduction and efficiency improvement policies according to the level and development stage of their AEE to establish a complete regional linked agroecological cooperation mechanism.

Suggested Citation

  • Mengyang Hou & Zenglei Xi & Suyan Zhao, 2022. "Evaluating the Heterogeneity Effect of Fertilizer Use Intensity on Agricultural Eco-Efficiency in China: Evidence from a Panel Quantile Regression Model," IJERPH, MDPI, vol. 19(11), pages 1-22, May.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:11:p:6612-:d:826832
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/11/6612/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/11/6612/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Haixia Wu & Hantao Hao & Hongzhen Lei & Yan Ge & Hengtong Shi & Yan Song, 2021. "Farm Size, Risk Aversion and Overuse of Fertilizer: The Heterogeneity of Large-Scale and Small-Scale Wheat Farmers in Northern China," Land, MDPI, vol. 10(2), pages 1-15, January.
    2. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    3. 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.
    4. Bonfiglio, Andrea & Arzeni, Andrea & Bodini, Antonella, 2017. "Assessing eco-efficiency of arable farms in rural areas," Agricultural Systems, Elsevier, vol. 151(C), pages 114-125.
    5. Zhang, Kevin Honglin & Song, Shunfeng, 2003. "Rural-urban migration and urbanization in China: Evidence from time-series and cross-section analyses," China Economic Review, Elsevier, vol. 14(4), pages 386-400.
    6. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    7. Liu, Yansui & Zou, Lilin & Wang, Yongsheng, 2020. "Spatial-temporal characteristics and influencing factors of agricultural eco-efficiency in China in recent 40 years," Land Use Policy, Elsevier, vol. 97(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hai Li & Hui Liu, 2023. "Climate Change, Farm Irrigation Facilities, and Agriculture Total Factor Productivity: Evidence from China," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    2. Changming Cheng & Jieqiong Li & Yuqing Qiu & Chunfeng Gao & Qiang Gao, 2022. "Evaluating the Spatiotemporal Characteristics of Agricultural Eco-Efficiency Alongside China’s Carbon Neutrality Targets," IJERPH, MDPI, vol. 19(23), pages 1-18, November.
    3. Songbiao Li & Lina Shangguan, 2024. "Has the Policy of National Agricultural Green Development Pilot Zones Enhanced the Agricultural Eco-Efficiency? Observation Based on the County-Level Data from Hubei Province of China," Sustainability, MDPI, vol. 16(21), pages 1-19, October.
    4. Yunfei Feng & Yi Zhang & Zhaodan Wu & Quanliang Ye & Xinchun Cao, 2023. "Evaluation of Agricultural Eco-Efficiency and Its Spatiotemporal Differentiation in China, Considering Green Water Consumption and Carbon Emissions Based on Undesired Dynamic SBM-DEA," Sustainability, MDPI, vol. 15(4), pages 1-26, February.

    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. Guangyan Ran & Guangyao Wang & Huijuan Du & Mi Lv, 2023. "Relationship of Cooperative Management and Green and Low-Carbon Transition of Agriculture and Its Impacts: A Case Study of the Western Tarim River Basin," Sustainability, MDPI, vol. 15(11), pages 1-18, May.
    2. Shilin Li & Zhiyuan Zhu & Zhenzhong Dai & Jiajia Duan & Danmeng Wang & Yongzhong Feng, 2022. "Temporal and Spatial Differentiation and Driving Factors of China’s Agricultural Eco-Efficiency Considering Agricultural Carbon Sinks," Agriculture, MDPI, vol. 12(10), pages 1-17, October.
    3. Wei, Wei & Hu, Haiqing & Chang, Chun-Ping, 2022. "Why the same degree of economic policy uncertainty can produce different outcomes in energy efficiency? New evidence from China," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 467-481.
    4. Xiyao Zhang & Xiaolei Wang & Jia Liu, 2023. "Spatial–Temporal Evolution and Influential Factors of Eco-Efficiency in Chinese Urban Agglomerations," Sustainability, MDPI, vol. 15(16), pages 1-29, August.
    5. Lin Shi & Xiaofei Shi & Fan Yang & Lixue Zhang, 2023. "Spatio-Temporal Difference in Agricultural Eco-Efficiency and Its Influencing Factors Based on the SBM-Tobit Models in the Yangtze River Delta, China," IJERPH, MDPI, vol. 20(6), pages 1-22, March.
    6. Zheng Wang & Jinhua Luo, 2024. "Evaluating the tourism green productivity and its driving factors in the context of climate change," Tourism Economics, , vol. 30(3), pages 655-679, May.
    7. Changming Cheng & Jieqiong Li & Yuqing Qiu & Chunfeng Gao & Qiang Gao, 2022. "Evaluating the Spatiotemporal Characteristics of Agricultural Eco-Efficiency Alongside China’s Carbon Neutrality Targets," IJERPH, MDPI, vol. 19(23), pages 1-18, November.
    8. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    9. Honma, Satoshi, 2012. "Environmental and economic efficiencies in the Asia-Pacific region," MPRA Paper 43361, University Library of Munich, Germany.
    10. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    11. Le Sun & Congmou Zhu & Shaofeng Yuan & Lixia Yang & Shan He & Wuyan Li, 2022. "Exploring the Impact of Digital Inclusive Finance on Agricultural Carbon Emission Performance in China," IJERPH, MDPI, vol. 19(17), pages 1-18, September.
    12. Senhua Huang & Lingming Chen, 2023. "The Impact of the Digital Economy on the Urban Total-Factor Energy Efficiency: Evidence from 275 Cities in China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    13. Can Zhang & Jixia Li, 2024. "The Impact of Official Promotion Incentives on Urban Ecological Welfare Performance and Its Spatial Effect," Sustainability, MDPI, vol. 16(7), pages 1-29, April.
    14. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    15. Chenchen Su & Jinchuan Shen & Fei Wang, 2024. "Can income growth and environmental improvements go hand in hand? An empirical study of Chinese agriculture," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(7), pages 321-333.
    16. Ningyi Liu & Yongyu Wang, 2022. "Urban Agglomeration Ecological Welfare Performance and Spatial Convergence Research in the Yellow River Basin," Land, MDPI, vol. 11(11), pages 1-18, November.
    17. Zhou, Lin & Fan, Jianshuang & Hu, Mingzhi & Yu, Xiaofen, 2024. "Clean air policy and green total factor productivity: Evidence from Chinese prefecture-level cities," Energy Economics, Elsevier, vol. 133(C).
    18. Nguyen Thi Kim Lien & Luyen Le Anh, 2024. "Adopting SBM-Max and Super SBM-Max to Evaluate the Efficiency of Freight Transportation Arrangement Providers: A Study in Vietnam," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 15(1), pages 73-84.
    19. Chia-Nan Wang & Thi-Duong Nguyen & Min-Chun Yu, 2019. "Energy Use Efficiency Past-to-Future Evaluation: An International Comparison," Energies, MDPI, vol. 12(19), pages 1-15, October.
    20. Chan, Sok-Gee & Koh, Eric H.Y. & Zainir, Fauzi & Yong, Chen-Chen, 2015. "Market structure, institutional framework and bank efficiency in ASEAN 5," Journal of Economics and Business, Elsevier, vol. 82(C), pages 84-112.

    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:gam:jijerp:v:19:y:2022:i:11:p:6612-:d:826832. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.