IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i7p981-d850210.html
   My bibliography  Save this article

Spatial Distribution and Driving Forces of the Vegetable Industry in China

Author

Listed:
  • Hongru Wang

    (College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China)

  • Jun He

    (College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China)

  • Noshaba Aziz

    (College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China)

  • Yue Wang

    (Institute of Agricultural Economics and Development, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China)

Abstract

Based on the ArcGIS geostatistical analysis method, this study offers a visualization of the spatial distribution pattern and spatial trend of vegetable production in China. The research also examines the degree of spatial agglomeration patterns of vegetable production by using the standard deviation ellipse technique and exploratory spatial data analysis method. In addition, we employ the spatial regression model partial differential method to explore the driving factors leading to the changing layout of vegetable production. The findings unveil that vegetable production in China exhibit strong spatial non-equilibrium characteristics, with “high-high” and “low-low” types as the main agglomeration patterns. Furthermore, the location distribution shows a northeast–southwest orientation with the center of gravity of distribution gradually directed toward the southwest. Regarding driving factors, the results show that the effective irrigated area of natural factors had a facilitating effect on the layout of vegetable production, while the affected area had an inhibiting effect on it. Climate indicators such as temperature, precipitation and light show different degrees of influence on the layout of vegetable production. The level of urbanization and transportation conditions have a negative impact on the layout of production in the region. Market demand has a positive spillover effect on the layout of local vegetable production, while it has a negative spillover effect on other regions. Technological progress shows positive spillover effects on the layout of vegetable production in the region and other regions. Financial support policy also shows positive effects from an overall perspective.

Suggested Citation

  • Hongru Wang & Jun He & Noshaba Aziz & Yue Wang, 2022. "Spatial Distribution and Driving Forces of the Vegetable Industry in China," Land, MDPI, vol. 11(7), pages 1-18, June.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:7:p:981-:d:850210
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/7/981/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/7/981/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    2. Qiangqiang Zhang & Fanji Shi & Nazir Muhammad Abdullahi & Liqun Shao & Xuexi Huo, 2020. "An empirical study on spatial–temporal dynamics and influencing factors of apple production in China," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-20, October.
    3. Yingnan Niu & Gaodi Xie & Yu Xiao & Keyu Qin & Jingya Liu & Yangyang Wang & Shuang Gan & Mengdong Huang & Jia Liu & Caixia Zhang & Changshun Zhang, 2021. "Spatial Layout of Cotton Seed Production Based on Hierarchical Classification: A Case Study in Xinjiang, China," Agriculture, MDPI, vol. 11(8), pages 1-23, August.
    4. Sellschopp, Jork & Kalter, Robert J., 1990. "Spatial Distribution Of The U.S. Dairy Industry: Long Term Impacts Of Policy Change," 1990 Annual meeting, August 5-8, Vancouver, Canada 270870, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. You, Liangzhi & Spoor, Max & Ulimwengu, John & Zhang, Shemei, 2011. "Land use change and environmental stress of wheat, rice and corn production in China," China Economic Review, Elsevier, vol. 22(4), pages 461-473.
    6. Brian Roe & Elena G. Irwin & Jeff S. Sharp, 2002. "Pigs in Space: Modeling the Spatial Structure of Hog Production in Traditional and Nontraditional Production Regions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 259-278.
    7. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    8. Mengyang Hou & Yuanjie Deng & Shunbo Yao, 2020. "Spatial Agglomeration Pattern and Driving Factors of Grain Production in China since the Reform and Opening Up," Land, MDPI, vol. 10(1), pages 1-17, December.
    9. Jacoby, Hanan C, 2000. "Access to Markets and the Benefits of Rural Roads," Economic Journal, Royal Economic Society, vol. 110(465), pages 713-737, July.
    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. Shengyong Xu & Yi Zhang & Wanjing Dong & Zhilong Bie & Chengli Peng & Yuan Huang, 2023. "Early Identification and Localization Algorithm for Weak Seedlings Based on Phenotype Detection and Machine Learning," Agriculture, MDPI, vol. 13(1), pages 1-19, January.
    2. Deping Ye & Shangsong Zhen & Wei Wang & Yunqiang Liu, 2023. "Spatial double dividend from China’s main grain-producing areas policy: total factor productivity and the net carbon effect," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-22, December.
    3. Feiyang Lin & Xuan Zhang & Zhiyao Ma & Yifu Zhang, 2022. "Spatial Structure and Corridor Construction of Intangible Cultural Heritage: A Case Study of the Ming Great Wall," Land, MDPI, vol. 11(9), pages 1-24, September.

    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. Oumarou Zallé & Idrissa M. Ouédraogo, 2021. "Spillover effects of corruption and democracy on territorial attractiveness of foreign direct investment in sub‐Saharan Africa," African Development Review, African Development Bank, vol. 33(4), pages 756-769, December.
    2. Krishnan, Pramila & Gunning, Jan Willem & Mengistu, Andualem Telaye, 2018. "Fading Choice: Transport Costs and Variety in Consumer Goods," CEPR Discussion Papers 12910, C.E.P.R. Discussion Papers.
    3. Abate, Gashaw T. & Dereje, Mekdim & Hirvonen, Kalle & Minten, Bart, 2020. "Geography of public service delivery in rural Ethiopia," World Development, Elsevier, vol. 136(C).
    4. Guilherme Resende & Alexandre Carvalho & Patrícia Sakowski & Túlio Cravo, 2016. "Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 1-31, January.
    5. Scherngell, Thomas & Borowiecki, Martin & Hu, Yuanjia, 2014. "Effects of knowledge capital on total factor productivity in China: A spatial econometric perspective," China Economic Review, Elsevier, vol. 29(C), pages 82-94.
    6. Marcel Fafchamps & Forhad Shilpi & The World Bank, 2004. "Isolation and Subjective Welfare," Economics Series Working Papers 216, University of Oxford, Department of Economics.
    7. Hao, Yu & Guo, Yunxia & Li, Suixin & Luo, Shiyue & Jiang, Xueting & Shen, Zhiyang & Wu, Haitao, 2022. "Towards achieving the sustainable development goal of industry: How does industrial agglomeration affect air pollution?," Innovation and Green Development, Elsevier, vol. 1(1).
    8. Escobal, Javier, 2005. "The Role of Public Infraestructure in Market Development in Rural Peru," MPRA Paper 727, University Library of Munich, Germany.
    9. Celbis M.G. & Crombrugghe D.P.I. de, 2014. "Can internet infrastructure help reduce regional disparities? : evidence from Turkey," MERIT Working Papers 2014-078, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    10. Liu, Mengsha & Jiang, Yan & Wei, Xiaokun & Ruan, Qingsong & Lv, Dayong, 2023. "Effect of high-speed rail on entrepreneurial activities: Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    11. Ping Lu & Jianhui Liu & Yunxuan Wang & Lei Ruan, 2021. "Can industrial agglomeration improve regional green total factor productivity in China? An empirical analysis based on spatial econometrics," Growth and Change, Wiley Blackwell, vol. 52(2), pages 1011-1039, June.
    12. Qin, Xionghe & Wang, Xueli & Kwan, Mei-Po, 2023. "The contrasting effects of interregional networks and local agglomeration on R&D productivity in Chinese provinces: Insights from an empirical spatial Durbin model," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    13. Juan Soto & Milena Vargas & Julio A. Berdegué, 2018. "How Large Are the Contributions of Cities to the Development of Rural Communities? A Market Access Approach for a Quarter Century of Evidence from Chile," Documentos de Trabajo 17060, The Latin American and Caribbean Economic Association (LACEA).
    14. Volpe Martincus, Christian & Carballo, Jerónimo & Cusolito, Ana, 2017. "Roads, exports and employment: Evidence from a developing country," Journal of Development Economics, Elsevier, vol. 125(C), pages 21-39.
    15. Hochard, Jacob & Barbier, Edward, 2017. "Market Accessibility and Economic Growth: Insights from a New Dimension of Inequality," World Development, Elsevier, vol. 97(C), pages 279-297.
    16. Xie, Rui & Fu, Wei & Yao, Siling & Zhang, Qi, 2021. "Effects of financial agglomeration on green total factor productivity in Chinese cities: Insights from an empirical spatial Durbin model," Energy Economics, Elsevier, vol. 101(C).
    17. Davenport, Sally, 2005. "Exploring the role of proximity in SME knowledge-acquisition," Research Policy, Elsevier, vol. 34(5), pages 683-701, June.
    18. Alberto Chong & Virgilio Galdo & Máximo Torero, 2005. "Does Privatization Deliver? Access to Telephone Services and Household Income in Poor Rural Areas Using a Quasi-Natural Experiment in Peru," Research Department Publications 4417, Inter-American Development Bank, Research Department.
    19. Mark Partridge & M. Rose Olfert & Alessandro Alasia, 2007. "Canadian cities as regional engines of growth: agglomeration and amenities," Canadian Journal of Economics, Canadian Economics Association, vol. 40(1), pages 39-68, February.
    20. João Juchem Neto & Julio Claeyssen, 2015. "Capital-induced labor migration in a spatial Solow model," Journal of Economics, Springer, vol. 115(1), pages 25-47, May.

    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:jlands:v:11:y:2022:i:7:p:981-:d:850210. 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.