Predicting farms' noncompliance with regulations on nitrate pollution. Issue 13 (9th November 2020) - Lunn, Peter D.; 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.