Modeling regional supply responses using farm-level economic data and a biophysical model: A case study on Brazilian land-use change

Estimating farmers' supply responses to changes in framework conditions is important to in-form decision-makers on the expected impacts on production volume as well as the resulting land-use shifts. Existing agricultural supply response models generally require either larger databases with farm-level data for microregional analysis or are implemented with a coarse resolution (e.g., country level) due to the lack of data. While such approaches are suitable for regions with abundancy of data or for global-scale analysis, there is a need for an alternative for micro-level analysis in countries with low data availability. In addition, it is important to include the spatial component in the regional supply response analysis, allowing not only the quantification of the overall change in output but also the likely spatial land-use change. Against this background, this dissertation aims to answer the research question whether a combination of a biophysical model with farm-level economic data can be used to estimate farm-level profitability of individual crops and respective cropping systems and thereby simulate farmers' supply responses in countries with limited data availability. To answer this ques-tion, a new modeling approach called Profitability Assessment Model (PAM) is developed, tested and validated. This new modeling approach follows the principles of minimum data, focusing on delivering timely and quantitative analyses with satisfactory accuracy to inform decision-makers. That is an important feature since the overall goal of the concept is to limit the data required by the model to a minimum, allowing quick implementation while accepting moderate accuracy. [...]