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Predicting farms’ noncompliance with regulations on nitrate pollution

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  • Lunn, Pete
  • Lyons, Seán
  • Murphy, Martin

Abstract

This paper demonstrates the use of “big data” to target behavioural interventions that aim to reduce environmental pollution. The data relate to ongoing noncompliance with the EU Nitrates Directive among farmers in Ireland. We compiled more than 1.2 million records from disparate administrative data, then employed multi-level statistical analysis to model regulatory breaches. The novel statistical associations generated shed light on possible reasons for noncompliance and allow us to predict violations more accurately than a regulatory rule of thumb previously used to target a behavioural ‘nudge’. By quantifying variation in likely rates of false positives and false negatives, the models can be used to improve the efficiency of the behavioural intervention. The work illustrates how big data can combine with behavioural interventions to support better environmental enforcement.
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Suggested Citation

  • Lunn, Pete & Lyons, Seán & Murphy, Martin, 2019. "Predicting farms’ noncompliance with regulations on nitrate pollution," Papers WP609, Economic and Social Research Institute (ESRI).
    • Handle: RePEc:esr:wpaper:wp609
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    References listed on IDEAS

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    1. Herzfeld, Thomas & Jongeneel, Roel, 2012. "Why do farmers behave as they do? Understanding compliance with rural, agricultural, and food attribute standards," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 29(1), pages 250-260.
    2. Achim Ahrens & Christian B. Hansen & Mark E Schaffer, 2018. "LASSOPACK: Stata module for lasso, square-root lasso, elastic net, ridge, adaptive lasso estimation and cross-validation," Statistical Software Components S458458, Boston College Department of Economics, revised 18 Sep 2024.
    3. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    4. Buckley, Cathal, 2012. "Implementation of the EU Nitrates Directive in the Republic of Ireland — A view from the farm," Ecological Economics, Elsevier, vol. 78(C), pages 29-36.
    5. Christian Lippert & Alexander Zorn & Stephan Dabbert, 2014. "Econometric analysis of noncompliance with organic farming standards in Switzerland," Agricultural Economics, International Association of Agricultural Economists, vol. 45(3), pages 313-325, May.
    6. Buckley, Cathal & Howley, Peter & Jordan, Phil, 2015. "The role of differing farming motivations on the adoption of nutrient management practices," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 4(4), July.
    7. Joel Slemrod, 2007. "Cheating Ourselves: The Economics of Tax Evasion," Journal of Economic Perspectives, American Economic Association, vol. 21(1), pages 25-48, Winter.
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