Supports

In SEAMLESS-IF impact assessments, factors can be independent variables to be manipulated, including a policy option to be tested (e.g. A) an  agro-environmental context (e.g. B), nuisance variables (e.g. C), and a combination among independent variables and nuisance variables (e.g. C=AB, E=AC, F=BC).

Icône de l'outil pédagogique Factors as policy options

What is (are) the policy option(s) that should be assessed? Each Experiment within a project assesses the effects of one or a combination of several policy option(s). One policy option refers to one or a set of policy measures. Each policy option has a set of exogenous policy parameters within a given timeframe or for a given time series. Exogenous policy parameters are variables that together describe one policy option that are outside the SEAMLESS models. For example, the introduction of decoupled payments in the EU is described by the percentage of decoupling for a region, the reference yield for a region and the cut in premiums occurring in the EU. Base year and baseline are two examples/instances of the concept policy option that have policy parameters (namely policies that have already been agreed upon and are currently being phased-in) and occur in the years 2003, 2013 and 2020.


Icône de l'outil pédagogique Factors as agro- management contexts

Which are the relevant agro-management contexts to be simulated? The agro-management context of a problem is the object of interest (components of the cropping and farming system), which is delimited by the boundaries to the biophysical and agro-management system. These biophysical and agro-management boundaries determine what is inside and what is outside the investigated system. Each experiment within a problem will be based on ONE agro-management and biophysical context that can be different from those of other ‘experiment(s)’. This agro-management and biophysical context sets the boundaries for the agro-management and biophysical models (FSSIM-AM) and has to be defined before the assessment can be started. Given the current models, relevant properties to define for such a context include the crops to be considered, one or many representative farms (farm types), the production orientation and the crop management. An example of a context is a medium sized low intensity arable farm in the Flevoland region in the Netherlands, which could grow sugar beets, potatoes and spring wheat under conventional management. After one or more Agro-management Contexts have been defined within ONE ‘Problem definition’, the input parameters for the models that evaluate the Policy Options based on this Context (technical coefficient of the investigated farming activities) can be generated. These input parameters corresponding to the different contexts will be generated by some of the models, for example currently FSSIM-AM and APES, even before the specification of the different policy options. These sets of technical coefficients will serve as the base for the assessment of the policy options linked to the experiment.


Icône de l'outil pédagogique Factors as outlook parameters

What are trends and trend deviations foreseen to occur in society that might affect the implementation of policy options within a given context, which are not modelled endogenously in SEAMLESS-IF (Outlook)? What do the policy experts and/or integrated modellers expect to happen in the future for the external driving forces? A problem definition can have one or more Outlooks on the future. One reference outlook is always required that describes the prolongation of the current situation into the future, sometimes called ‘business-as-usual’ outlook. Outlooks are usually contrasting, for example a positive versus a negative outlook, a globalization versus a regionalization outlook, a high-employment versus a low employment outlook, etc. Each outlook has several exogenous parameters that capture the different trends occurring in society. These parameters are unchangeable by the models, meaning that the model run does not affect the value of the parameter. Examples of these parameters are atmospheric CO2-concentration, GDP-growth and unemployment rate. It should be noted that the exogenous parameters vary between models. For example, in the APES-FSSIM model chain, prices are exogenous, whereas in FSSIM-EXPAMOD-SEAMCAP chain these prices are endogenously determined by demand and supply.


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