Predicting adoption of agri-environmental schemes by farmers in the European Union

Abstract

Much of the land across the European Union (EU) is threatened by unsustainable land-use through intensive farming. To help combat this, Agri-Environmental Schemes (AESs) are provided by the EU to encourage farmers to use a portion of their land to aid with environmental goals such as sustainable farming, bio-diversity or landscape recovery. Farmers in the EU are given the opportunity to take on an AES for a monetary payment that is based on the choice of scheme and the amount of land dedicated to it. If we know or can accurately predict which farmers adopt which AES, we can then predict if the intended benefits to the environment according to the given scheme are likely to be achieved. As a preliminary step, we develop a generalised linear model coupled with a microsimulation that is fed with data from the Farm Accountancy Data Network to predict AES uptake. We find the model is able to accurately predict approximately 70% of farmers’ decisions on whether to adopt an AES across 27 countries in the EU. In the future, this model can be used to predict, for example, if the chosen schemes adopted will lead to their intended benefits, and if changes in the offered AES payment may affect AES adoption.