IDEAS home Printed from https://ideas.repec.org/a/ags/aareaj/260090.html
   My bibliography  Save this article

A response to Doole and Marsh (2013) article: methodological limitations in the evaluation of policies to reduce nitrate leaching from New Zealand agriculture

Author

Listed:
  • Daigneault, Adam
  • Greenhalgh, Suzie
  • Samarasinghe, Oshadhi

Abstract

A recent paper by Doole and Marsh (2013), questioned the validity of using the New Zealand Forest and Agriculture Regional Model (NZFARM) for New Zealand agri-environmental policy analysis. We respond to their critique by clearly describing the model structure, explaining the NZFARM parameterisation, calibration, and validation procedure, and presenting estimates from a series of nutrient reduction policy scenarios to highlight the utility of the model. In doing so, we demonstrate that NZFARM generates logical and intuitive results that can be used for robust agri-environmental policy decision-making.

Suggested Citation

  • Daigneault, Adam & Greenhalgh, Suzie & Samarasinghe, Oshadhi, 2014. "A response to Doole and Marsh (2013) article: methodological limitations in the evaluation of policies to reduce nitrate leaching from New Zealand agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(2), April.
    • Handle: RePEc:ags:aareaj:260090
    DOI: 10.22004/ag.econ.260090
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/260090/files/ajar12051.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.260090?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. Bruno Henry Frahan & Jeroen Buysse & Philippe Polomé & Bruno Fernagut & Olivier Harmignie & Ludwig Lauwers & Guido Huylenbroeck & Jef Meensel, 2007. "Positive Mathematical Programming for Agricultural and Environmental Policy Analysis: Review and Practice," International Series in Operations Research & Management Science, in: Andres Weintraub & Carlos Romero & Trond Bjørndal & Rafael Epstein & Jaime Miranda (ed.), Handbook Of Operations Research In Natural Resources, chapter 0, pages 129-154, Springer.
    2. Simon Anastasiadis & Suzi Kerr & Marie-Laure Nauleau & Tim Cox & Kit Rutherford, 2014. "Does complex hydrology require complex water quality policy?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(1), pages 130-145, January.
    3. Heckelei, Thomas & Britz, Wolfgang & Zhang, Yinan, 2012. "Positive Mathematical Programming Approaches – Recent Developments in Literature and Applied Modelling," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(1), pages 1-16, April.
    4. Graeme J. Doole & Dan K. Marsh, 2014. "Methodological limitations in the evaluation of policies to reduce nitrate leaching from New Zealand agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(1), pages 78-89, January.
    5. Suzi Kerr & Alex Olssen, 2012. "Gradual Land-use Change in New Zealand: Results from a Dynamic Econometric Model," Working Papers 12-06, Motu Economic and Public Policy Research.
    6. Graeme J. Doole, 2010. "Evaluating Input Standards for Non‐Point Pollution Control under Firm Heterogeneity," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(3), pages 680-696, September.
    7. Richard E. Howitt, 1995. "Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 329-342.
    8. Johansson, Robert & Peters, Mark & House, Robert, 2007. "Regional Environment and Agriculture Programming Model," Technical Bulletins 184314, United States Department of Agriculture, Economic Research Service.
    9. Bruce A. McCarl, 1982. "Cropping Activities in Agricultural Sector Models: A Methodological Proposal," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 64(4), pages 768-772.
    10. Kemal Dervis & Sherman Robinson, 1982. "A general equilibrium analysis of the causes of a foreign exchange crisis : The case of Turkey," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 118(2), pages 259-280, June.
    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. Doole, Graeme J. & Marsh, Dan K., 2014. "Use of positive mathematical programming invalidates the application of the NZFARM model: Response to Daigneault et al. (2014)," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(2), April.
    2. Gawith, David & Hodge, Ian & Morgan, Fraser & Daigneault, Adam, 2020. "Climate change costs more than we think because people adapt less than we assume," Ecological Economics, Elsevier, vol. 173(C).

    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. Adam Daigneault & Suzie Greenhalgh & Oshadhi Samarasinghe, 2018. "Economic Impacts of Multiple Agro-Environmental Policies on New Zealand Land Use," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(4), pages 763-785, April.
    2. Kooten, G. Cornelis van, 2013. "Modeling Forest Trade in Logs and Lumber: Qualitative and Quantitative Analysis," Working Papers 149182, University of Victoria, Resource Economics and Policy.
    3. Johnston, Craig M.T. & van Kooten, G. Cornelis, 2014. "Modelling Bi-lateral Forest Product Trade Flows: Experiencing Vertical and Horizontal Chain Optimization," Working Papers 197898, University of Victoria, Resource Economics and Policy.
    4. Doole, Graeme J. & Marsh, Dan K., 2014. "Methodological limitations in the evaluation of policies to reduce nitrate leaching from New Zealand agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(1), January.
    5. van Kooten, G. Cornelis & Johnston, Craig, 2014. "Global impacts of Russian log export restrictions and the Canada–U.S. lumber dispute: Modeling trade in logs and lumber," Forest Policy and Economics, Elsevier, vol. 39(C), pages 54-66.
    6. Cao, Zhaodan & Zhu, Tingju & Cai, Ximing, 2023. "Hydro-agro-economic optimization for irrigated farming in an arid region: The Hetao Irrigation District, Inner Mongolia," Agricultural Water Management, Elsevier, vol. 277(C).
    7. Umed Temurshoev & Marian Mraz & Luis Delgado Sancho & Peter Eder, 2015. "EU Petroleum Refining Fitness Check: OURSE Modelling and Results," JRC Research Reports JRC96207, Joint Research Centre.
    8. Gómez-Limón, José A. & Gutiérrez-Martín, Carlos & Riesgo, Laura, 2016. "Modeling at farm level: Positive Multi-Attribute Utility Programming," Omega, Elsevier, vol. 65(C), pages 17-27.
    9. Viaggi, Davide & Raggi, Meri & Gomez y Paloma, Sergio, 2011. "Farm-household investment behaviour and the CAP decoupling: Methodological issues in assessing policy impacts," Journal of Policy Modeling, Elsevier, vol. 33(1), pages 127-145, January.
    10. Liu, Xuan & van Kooten, Gerrit Cornelis & Duan, Jun, 2020. "Calibration of agricultural risk programming models using positive mathematical programming," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(3), July.
    11. Doole, Graeme J. & Marsh, Dan K., 2014. "Use of positive mathematical programming invalidates the application of the NZFARM model: Response to Daigneault et al. (2014)," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(2), April.
    12. Umed Temurshoev & Fréderic Lantz, 2016. "Long-term petroleum product supply analysis through a robust modelling approach," Working Papers 2016-003, Universidad Loyola Andalucía, Department of Economics.
    13. Jonathan R. Sweeney & Richard E. Howitt & Hing Ling Chan & Minling Pan & PingSun Leung, 2017. "How do fishery policies affect Hawaii's longline fishing industry? Calibrating a positive mathematical programming model," Papers 1707.03960, arXiv.org.
    14. Mack, Gabriele & Ferjani, Ali & Mohring, Anke & Zimmerman, Albert & Mann, Stefan, 2015. "How did farmers act? An ex-post validation of normative and positive mathematical programming for an agent-based sector model," 2015 Conference, August 9-14, 2015, Milan, Italy 212201, International Association of Agricultural Economists.
    15. Gómez-Limón, José A. & Gutiérrez-Martín, Carlos & Montilla-López, Nazaret M., 2021. "Priority water rights. Are they useful for improving water-use efficiency at the irrigation district level?," Agricultural Water Management, Elsevier, vol. 257(C).
    16. Claire Settre & Jeff Connor & Sarah Ann Wheeler, 2017. "Reviewing the Treatment of Uncertainty in Hydro-economic Modeling of the Murray–Darling Basin, Australia," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 1-35, July.
    17. Heckelei, Thomas & Britz, Wolfgang & Zhang, Yinan, 2012. "Positive Mathematical Programming Approaches – Recent Developments in Literature and Applied Modelling," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(1), pages 1-16, April.
    18. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Paloma, Sergio, 2015. "The Impact of Crop Diversification Measure: EU-wide Evidence Based on IFM-CAP Model," 2015 Conference, August 9-14, 2015, Milan, Italy 211542, International Association of Agricultural Economists.
    19. Britz, Wolfgang & Linda, Arata, "undated". "How Important Are Crop Shares In Managing Risk For Specialized Arable Farms? A Panel Estimation Of A Programming Model For Three European Regions," 56th Annual Conference, Bonn, Germany, September 28-30, 2016 244801, German Association of Agricultural Economists (GEWISOLA).
    20. Franz Sinabell & Martin Schönhart & Erwin Schmid, 2015. "Austrian Agriculture 2010-2050. Quantitative Effects of Climate Change Mitigation Measures – An Analysis of the Scenarios WEM, WAM and a Sensitivity Analysis of the Scenario WEM," WIFO Studies, WIFO, number 58400, February.

    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:aareaj:260090. 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/aaresea.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.