IDEAS home Printed from https://ideas.repec.org/a/wly/ajagec/v108y2026i1p336-362.html

Using synthetic farm data to estimate individual nitrate leaching levels

Author

Listed:
  • Konstantinos Mattas
  • Michail Tsagris
  • Vangelis Tzouvelekas

Abstract

This article delineates a synthetic population generation scheme in an attempt to estimate individual nitrate leaching rates among Greek farms in the region of Thessaly. The proposed scheme relies upon the construction of a Bayesian network describing farming activities in the region, which, coupled with the use of nonparametric regression models, facilitate the consistent generation of synthetic farm data. Then, building upon the sequential generalized maximum entropy approach suggested by Kaplan et al., enhanced with the multiple production relations model proposed by Murty et al., we obtain econometric estimates of the unified farm production and nitrate leaching technology for the synthetic population of farms. The estimation of individual nitrate emissions leads, thus, to the formulation of an optimal taxation scheme aiming to mitigate the negative externality created by chemical fertilization in agricultural activities.

Suggested Citation

  • Konstantinos Mattas & Michail Tsagris & Vangelis Tzouvelekas, 2026. "Using synthetic farm data to estimate individual nitrate leaching levels," American Journal of Agricultural Economics, John Wiley & Sons, vol. 108(1), pages 336-362, January.
  • Handle: RePEc:wly:ajagec:v:108:y:2026:i:1:p:336-362
    DOI: 10.1111/ajae.12541
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/ajae.12541
    Download Restriction: no

    File URL: https://libkey.io/10.1111/ajae.12541?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Michail Tsagris & Vangelis Tzouvelekas, 2022. "Nitrate leaching and efficiency measurement in intensive farming systems: A parametric by‐production technology approach," Agricultural Economics, International Association of Agricultural Economists, vol. 53(4), pages 633-647, July.
    2. Kaplan, Jonathan D. & Howitt, Richard E. & Farzin, Y. Hossein, 2003. "An information-theoretical analysis of budget-constrained nonpoint source pollution control," Journal of Environmental Economics and Management, Elsevier, vol. 46(1), pages 106-130, July.
    3. Murty, Sushama, 2010. "Externalities and fundamental nonconvexities: A reconciliation of approaches to general equilibrium externality modeling and implications for decentralization," Journal of Economic Theory, Elsevier, vol. 145(1), pages 331-353, January.
    4. David A. Bessler & Derya G. Akleman, 1998. "Farm Prices, Retail Prices, and Directed Graphs: Results for Pork and Beef," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(5), pages 1144-1149.
    5. Murty, Sushama & Robert Russell, R. & Levkoff, Steven B., 2012. "On modeling pollution-generating technologies," Journal of Environmental Economics and Management, Elsevier, vol. 64(1), pages 117-135.
    Full references (including those not matched with items on IDEAS)

    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. Michail Tsagris & Vangelis Tzouvelekas, 2022. "Nitrate leaching and efficiency measurement in intensive farming systems: A parametric by‐production technology approach," Agricultural Economics, International Association of Agricultural Economists, vol. 53(4), pages 633-647, July.
    2. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    3. Haleh Delnava & Kristiaan Kerstens & Timo Kuosmanen & Zhiyang Shen, 2024. "Semi-parametric Estimation of Convex and Nonconvex By-Production Technologies," Working Papers 2024-EQM-02, IESEG School of Management.
    4. Abad, Arnaud & Briec, Walter, 2019. "On the axiomatic of pollution-generating technologies: Non-parametric production analysis," European Journal of Operational Research, Elsevier, vol. 277(1), pages 377-390.
    5. Dakpo, K Hervé, 2016. "On modeling pollution-generating technologies: a new formulation of the by-production approach," Working Papers 245191, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    6. Sushama Murty & R. Robert Russell, 2018. "Modeling emission-generating technologies: reconciliation of axiomatic and by-production approaches," Empirical Economics, Springer, vol. 54(1), pages 7-30, February.
    7. Juan Aparicio & Magdalena Kapelko & Lidia Ortiz, 2021. "Modelling environmental inefficiency under a quota system," Operational Research, Springer, vol. 21(2), pages 1097-1124, June.
    8. Dakpo, Hervé K & Jeanneaux, Philippe & Latruffe, Laure, 2014. "Inclusion of undesirable outputs in production technology modeling: The case of greenhouse gas emissions in French meat sheep farming," Working Papers 207806, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    9. Bai, Ge & Shen, Zhiyang & Šermukšnytė-Alešiūnienė, Kristina & Štreimikienė, Dalia & Li, Tianxiang, 2024. "Energy structure and green productivity dynamics: Investigation from OECD Countries," Resources Policy, Elsevier, vol. 98(C).
    10. Kenneth Rødseth, 2014. "Efficiency measurement when producers control pollutants: a non-parametric approach," Journal of Productivity Analysis, Springer, vol. 42(2), pages 211-223, October.
    11. K Hervé Dakpo, 2016. "On modeling pollution-generating technologies: a new formulation of the by-production approach," Working Papers SMART 16-06, INRAE UMR SMART.
    12. Harald Dyckhoff, 2023. "Proper modelling of industrial production systems with unintended outputs: a different perspective," Journal of Productivity Analysis, Springer, vol. 59(2), pages 173-188, April.
    13. Sushama Murty, 2012. "Microfoundations for the Environmental Kuznets Curve: Invoking By-Production, Normality and Inferiority of Emissions," Discussion Papers 1203, University of Exeter, Department of Economics.
    14. A. Abad & P. Ravelojaona, 2017. "Exponential environmental productivity index and indicators," Journal of Productivity Analysis, Springer, vol. 48(2), pages 147-166, December.
    15. Sushama Murty, 2015. "On the properties of an emission-generating technology and its parametric representation," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 60(2), pages 243-282, October.
    16. Levi Marks, 2025. "A Sampling-Based Approach to Emissions Pricing," The Energy Journal, , vol. 46(6), pages 187-210, November.
    17. D’Inverno, Giovanna & Carosi, Laura & Romano, Giulia & Guerrini, Andrea, 2018. "Water pollution in wastewater treatment plants: An efficiency analysis with undesirable output," European Journal of Operational Research, Elsevier, vol. 269(1), pages 24-34.
    18. Atkinson, Scott E. & Tsionas, Mike G., 2021. "Generalized estimation of productivity with multiple bad outputs: The importance of materials balance constraints," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1165-1186.
    19. Lee, Andrew C. & Kim, Man-Keun, 2004. "Causality Among Fed Cattle Market Variables: Directed Acyclic Graphs Analysis Of Captive Supply," 2004 Annual meeting, August 1-4, Denver, CO 20124, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    20. Idiano D’Adamo & Cinzia Daraio & Simone Di Leo & Léopold Simar, 2024. "A Flexible and Sustainable Analysis of Waste Efficiency at the European Level," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 25(4), pages 881-894, December.

    More about this item

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water

    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:wly:ajagec:v:108:y:2026:i:1:p:336-362. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1467-8276 .

    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.