IDEAS home Printed from https://ideas.repec.org/p/ags/aaea16/235434.html
   My bibliography  Save this paper

Spatial analysis of determinants of dairy farmers' adoption of best management practices for water protection

Author

Listed:
  • Yang, Wei

Abstract

Purpose : It is undeniable that the NZ economy is heavily dependent on agriculture, especially dairy sector, but the increasing nutrient pollution discharged from dairy farms is a threat to the water quality of lakes, stream and rivers. Therefore, the dairy industry is under increasing pressure to make a commitment to improving the environmental performance of farming practices to protect water quality in waterways. Hence, farmer’s choice should be considered as one of the most important determinants of the success of policy aimed at water quality protection. It is therefore the aim of this paper to explore determinants of dairy farmers’ willingness to adopt Best manamgment practices (BMPs) for water quality protection. In addition, except for testing the commonly used determinants, such as farm characteristics, it will test for the hypothesis that spatial effects influence farmers’ choices. Design/methodology: Bayesian spatial Durbin (SDM) probit models are applied to survey data collected from dairy farmers in the Waikato Region of New Zealand. Specifically, this paper will verify the above hypothesis from two aspects. Firstly, spatial effects will be modelled according to the distance from farm to the nearest water bodies. It is assumed that dairy farmers whose farms are located close to water bodies are more inclined to be willing to adopt BMPs. Secondly, spatial effects will be presented as the existence of spatial interdependency in dairy farmers’ decision-making. It is hypothesised that dairy farmers observe or learn from nearby farmers thereby reducing the uncertainty of the performance of BMPs since BMPs are information-intensive farming techniques. Data were obtained from survey of 171 farms in the Waikato region of New Zealand; socioeconomic data were drawn from the 2013 Census. The advantage of the SDM probit model is that it allows for the inclusion of both the spatially lagged dependent variable and spatially lagged independent variables, which takes account the impact of neighbouring farmers’ decisions as well as of neighbouring farmers’ characteristics. Therefore, different from non-spatial probit models, the SDM probit model accounts for both direct and indirect effects. Significantly, the indirect effects (spatial spillovers) help to measure to what extent a change in the neighbouring farmers’ characteristics affect the adoption probability of a dairy farmer.Findings: Results show that farmers located in close proximity to each other exhibit similar choice behaviour indicating that access to industry information is an influential determinants of dairy farmers’ adoption of BMPs. In addition, these findings address the importance of farmer interactions in adoption decisions as participation in dairy-related activities are identified as an extension of information acquisition. Financial problems are considered a significant barrier to adopting BMPs. Overall, the study highlights the importance of accounting for interdependence in farmers’ decisions, which emerges as important in the formulation of agricultural-enviornmental policy. Originality/value: This paper is the first empirical study to examine the determinants of farmer’s adoption of BMPs in NZ by using spatial econometrics methods, which considers various determinants, including drivers and barriers for farmers to adopt the practices, farm and household characteristics as well as spatial issues. The results contribute to assist policy makers to specify water protection strategies. An understanding of dairy farmers’ drivers and barriers to adopting BMPs could assist policy makers to deliver support to solve the problems that are badly in the need of help. Besides, the importance of information availability in the neighbourhood network and social activities for the farmer's decision-making suggests that extension activities that address the whole community may be more efficient than targeting individual farmers to induce behavioural changes in adoption of BMPs.

Suggested Citation

  • Yang, Wei, 2016. "Spatial analysis of determinants of dairy farmers' adoption of best management practices for water protection," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235434, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea16:235434
    DOI: 10.22004/ag.econ.235434
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/235434/files/wei%20yang%20aaea2016.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.235434?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
    ---><---

    References listed on IDEAS

    as
    1. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," Review of Economic Studies, Oxford University Press, vol. 60(3), pages 531-542.
    2. Dan Marsh & Lena Mkwara & Riccardo Scarpa, 2011. "Do Respondents’ Perceptions of the Status Quo Matter in Non-Market Valuation with Choice Experiments? An Application to New Zealand Freshwater Streams," Sustainability, MDPI, vol. 3(9), pages 1-23, September.
    3. Knowler, Duncan & Bradshaw, Ben, 2007. "Farmers' adoption of conservation agriculture: A review and synthesis of recent research," Food Policy, Elsevier, vol. 32(1), pages 25-48, February.
    4. David J. Lewis & Bradford L. Barham & Brian Robinson, 2011. "Are There Spatial Spillovers in the Adoption of Clean Technology? The Case of Organic Dairy Farming," Land Economics, University of Wisconsin Press, vol. 87(2), pages 250-267.
    5. Seo, S. Niggol & Mendelsohn, Robert, 2008. "An analysis of crop choice: Adapting to climate change in South American farms," Ecological Economics, Elsevier, vol. 67(1), pages 109-116, August.
    6. Jørgensen, Sisse Liv & Olsen, Søren Bøye & Ladenburg, Jacob & Martinsen, Louise & Svenningsen, Stig Roar & Hasler, Berit, 2013. "Spatially induced disparities in users' and non-users' WTP for water quality improvements—Testing the effect of multiple substitutes and distance decay," Ecological Economics, Elsevier, vol. 92(C), pages 58-66.
    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. Wei Yang & Jorie Knook, 2021. "Spatial evaluation of the impact of a climate change participatory extension programme on the uptake of soil management practices," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(3), pages 539-565, July.
    2. Traxler, Emilia & Li, Tongzhe, 2020. "Agricultural Best Management Practices, A summary of adoption behaviour," Working Papers 305271, University of Guelph, Institute for the Advanced Study of Food and Agricultural Policy.
    3. Qi Li & Wanjiang Yang & Kai Li, 2018. "Role of Social Learning in the Diffusion of Environmentally-Friendly Agricultural Technology in China," Sustainability, MDPI, vol. 10(5), pages 1-12, May.
    4. Hongyun Zheng & Wanglin Ma & Gucheng Li, 2021. "Learning from neighboring farmers: Does spatial dependence affect adoption of drought‐tolerant wheat varieties in China?," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 69(4), pages 519-537, December.

    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. Yanbing Wang & Niklas Möhring & Robert Finger, 2023. "When my neighbors matter: Spillover effects in the adoption of large‐scale pesticide‐free wheat production," Agricultural Economics, International Association of Agricultural Economists, vol. 54(2), pages 256-273, March.
    2. Wollni, Meike & Andersson, Camilla, 2014. "Spatial patterns of organic agriculture adoption: Evidence from Honduras," Ecological Economics, Elsevier, vol. 97(C), pages 120-128.
    3. Meredith T. Niles & Margaret Brown & Robyn Dynes, 2016. "Farmer’s intended and actual adoption of climate change mitigation and adaptation strategies," Climatic Change, Springer, vol. 135(2), pages 277-295, March.
    4. Ward, Patrick S. & Bell, Andrew R. & Droppelmann, Klaus & Benton, Tim G., 2018. "Early adoption of conservation agriculture practices: Understanding partial compliance in programs with multiple adoption decisions," Land Use Policy, Elsevier, vol. 70(C), pages 27-37.
    5. Heleene Tambet & Yaniv Stopnitzky, 2021. "Climate Adaptation and Conservation Agriculture among Peruvian Farmers," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 900-922, May.
    6. Vroege, Willemijn & Meraner, Manuela & Polman, Nico & Storm, Hugo & Heijman, Wim & Finger, Robert, 2020. "Beyond the single farm – A spatial econometric analysis of spill-overs in farm diversification in the Netherlands," Land Use Policy, Elsevier, vol. 99(C).
    7. Doris Läpple & Garth Holloway & Donald J Lacombe & Cathal O’Donoghue, 2017. "Sustainable technology adoption: a spatial analysis of the Irish Dairy Sector," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 44(5), pages 810-835.
    8. Meredith Niles & Margaret Brown & Robyn Dynes, 2016. "Farmer’s intended and actual adoption of climate change mitigation and adaptation strategies," Climatic Change, Springer, vol. 135(2), pages 277-295, March.
    9. Hailemariam Teklewold & Alemu Mekonnen & Gunnar Kohlin & Salvatore Di Falco, 2017. "Does Adoption Of Multiple Climate-Smart Practices Improve Farmers’ Climate Resilience? Empirical Evidence From The Nile Basin Of Ethiopia," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 1-30, February.
    10. Mannaf, Maksuda & Wheeler, Sarah Ann & Zuo, Alec, 2023. "Global and Local Spatial Spill-Overs: What Matters Most for the Diffusion of Organic Agriculture in Australia?," Ecological Economics, Elsevier, vol. 209(C).
    11. Beasley, W. Jason & Dundas, Steven J., 2021. "Hold the line: Modeling private coastal adaptation through shoreline armoring decisions," Journal of Environmental Economics and Management, Elsevier, vol. 105(C).
    12. Wollni, Meike & Andersson, Camilla I.M., 2013. "Spatial effects in organic agriculture adoption in Honduras: the role of social conformity, positive externalities, and information," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149911, Agricultural and Applied Economics Association.
    13. Loic Levi & Obafemi Philippe Koutchade & Laure Latruffe & Aude Ridier, 2018. "Spatial effects in investment decisions: Evidence from French dairy farms," Post-Print hal-02024077, HAL.
    14. Alexander Pfaff & Juan Robalino, 2017. "Spillovers from Conservation Programs," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 299-315, October.
    15. Fabrice Gilles & Sabina Issehnane & Florent Sari, 2022. "Using short-term jobs as a way to find a regular job. What kind of role for local context?," TEPP Working Paper 2022-07, TEPP.
    16. H Peyton Young, 2014. "The Evolution of Social Norms," Economics Series Working Papers 726, University of Oxford, Department of Economics.
    17. Ruomeng Cui & Dennis J. Zhang & Achal Bassamboo, 2019. "Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon," Management Science, INFORMS, vol. 65(3), pages 1216-1235, March.
    18. Gautier, Pieter & van Vuuren, Aico & Siegmann, Arjen, 2007. "The Effect of the Theo van Gogh Murder on House Prices in Amsterdam," CEPR Discussion Papers 6175, C.E.P.R. Discussion Papers.
    19. Dostie, Benoit & Jayaraman, Rajshri, 2006. "Determinants of School Enrollment in Indian Villages," Economic Development and Cultural Change, University of Chicago Press, vol. 54(2), pages 405-421, January.
    20. Mekonnen, Daniel Ayalew & Gerber, Nicolas & Matz, Julia Anna, 2018. "Gendered Social Networks, Agricultural Innovations, and Farm Productivity in Ethiopia," World Development, Elsevier, vol. 105(C), pages 321-335.

    More about this item

    Keywords

    Environmental Economics and Policy; Farm Management; Institutional and Behavioral Economics; Teaching/Communication/Extension/Profession;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ags:aaea16:235434. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    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.