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Agriculture is the product of a complex mixture of behavioural, biophysical and market drivers. Understanding how these factors interact to produce crops and livestock for food has been the focus of economic investigation for many years. The advent of optimisation algorithms and the exponential growth in computing technology has allowed significant growth in mathematical modelling of the dynamics of agricultural systems. The complexity of approaches has grown in parallel with the availability of data at increasingly finer resolutions. Farm-level models have been widely used in agricultural economic studies to understand how farmers and land owners respond to market and policy levers. This book provides an in-depth description of different methodologies and techniques currently used in farm-level modelling. While giving an overview of the theoretical grounding behind the models, an applied approach is also used. Case studies range from the application of modelling to policy reforms and the subsequent impacts on rural communities and food supply. This book also provides descriptions of the use of farm-level models in much wider fields such as aggregation and linking with sectoral models. Its purpose is to show the reader the methods that have been employed to inform decision-makers about how to improve the economic, social and environmental goals required to achieve the aims of multidimensional policy.