Lesson 1 - Introduction Tradeoff Analysis Model

The Tradeoff Analysis aims to analyse in close interaction with the stakeholders the potential impacts of different policy instruments and technological changes. To which state does the agricultural sector move within the opportunity space. In other words, it is a policy decision support system designed to quantify tradeoffs between key sustainability indicators under alternative policy and technology scenarios. The results are presented in the form of tradeoff curves that are intuitive and easy-to-understand for policy makers using the economic principle of opportunity cost. These tradeoff curves allow for the actual quantification of the sustainability concept. The tradeoff analysis model is based on econometric production models estimated on observed behaviour of the population of farmers. As a result its predictive power is much higher than some of the explorative or projective models. At the same time we have to realise that it its time horizon is also relatively limited. Its application allows a subsequent analysis in which the changes of policy interventions as well as technological changes influence agricultural land use and its impact on the environment.


Figure 1. Example of a tradeoff curve between production and environmental quality

The tradeoff curves represent the joint distribution of two indicators, in the example of Figure 1, production and environmental quality. A scenario analysis deals with the shift of the tradeoff curve as a result of technological changes, environmental degradation, or policy interventions.

The actual model application is part of a broader process. Tradeoff assessment provides an organizing principle and conceptual model for the design and organization of multi-disciplinary research projects to quantify and assess competing objectives in agricultural production systems. This process is illustrated in Figure 2. Input from stakeholders (i.e., the general public, policy makers and scientists) is used to identify the critical dimensions of social concern, i.e., criteria for assessment of the sustainability of the system. Based on these criteria, hypotheses are formulated as tradeoffs between possibly competing objectives, such as higher agricultural production and improved environmental quality. Once the key tradeoffs are identified, research team leaders can identify the appropriate scientific disciplines to further design and implement the research needed to quantify these tradeoffs. The next step, critical to quantifying tradeoffs, is the identification of disciplinary models and data needed to quantify each sustainability indicator. A key element at this stage is for all of the disciplines to agree upon basic spatial and temporal units of analysis, e.g. will analysis be conducted at the field scale or watershed scale and will time steps be daily, monthly, or yearly? Once these fundamental issues in research design have been resolved; data collection and disciplinary research can proceed. Upon completion of the disciplinary components of research, the respective data and models can be linked to test hypotheses about tradeoffs, and the findings can be presented to policy makers and the general public.


Figure 2. Tradeoff Analysis research design and implementation process

The structure of the Tradeoff Analysis Model is schematically presented in Figure 3. The Tradeoff Analysis Model itself is only the user shell and connects the different models and data.The first step is the collection of input data such as the GIS-based data, i.e., soil, altitude and climate data, and farm survey data. These data are used in the crop simulation and economic models together with several other input databases, e.g. prices, crop and livestock management. From the farm survey data a price distribution is calculated, which is used in the economic simulation model. With the crop growth simulation model an inherent productivity is calculated, which is the expected productivity with average management and without problems of pests and diseases. These survey field data are also used in the economic simulation model.

For the economic simulation a number of sample fields is taken, which can be stratified. For these fields the inherent productivity is calculated with the crop-model. Before the economic simulation model can be run, a scenario and a tradeoff must be defined. A tradeoff is defined as the set of outcomes generated by varying one parameter while holding other parameters constant, e.g. potato or pesticide price. The economic simulation model simulates crop selection and field management decisions for all sample fields and for the specified economic conditions, the tradeoff points. The output of this simulation is used together with the biophysical data of the field in the environmental impact model. The resulting large data sets can be aggregated over one or more of the parameters. The results can be presented as tradeoff curves, with a graphical program that is included in the user shell. Based on these results the tradeoff or scenario definition can be adapted. The theoretical course has been ordered according to this structure of the Tradeoff Analysis Model.


Figure 3. Structure of the Tradeoff Analysis Model (square boxes represent data and round boxes represent models)


Lesson 2