Farm Economic Modeling

Several organizations are using Farm Economic Models as “thinking tools” to inform strategy by looking at how different variables in different magnitudes and times affect outcomes in specific contexts. More granularly, a farm economic model will allow the mapping of how a farm of a certain size, age, crop, location, etc. would respond to certain agricultural practices and how that would affect income at a particular farm gate price.  The models can be used to build an aggregate picture of a sector to facilitate pre-competitive collaboration, run a scenario to foster good dialogue in a diverse group, and provide information to inform decision-making.   CocoaAction, NewForesight and GIZ shared their experience with building and using farm economic models.

While the CocoaAction and NewForesight’s Farmer Economic Model looks across the sector with reference to cocoa, GIZ’s model for Madagascar vanilla was created to be very specific to certain villages. Both models have been effective in informing strategy at the level they were created to model (sector vs. village) by grounding discussion, driving action by informing decision-makers, and fostering collaboration to align on how and what to measure in a certain context.

However, the presenters were keen to point out the limitations of models and encouraged their use only in the particular contexts for which they were designed. For instance, the limits of models to predict outside of the level they were designed for (e.g., model results at the sector level cannot be used to inform strategy on a particular farm), the dangers of using averages as the diversity that exists is lost and results can become inaccurate (e.g., equal amounts of large and small farms do not make a population of medium-sized farms), the importance of understanding the limits of each particular model and using it only as intended (e.g., is the model able to take into account effects of climate change, crop diversification, off-farm income, or large fluctuations in price that change the market, such as in Madagascar vanilla, etc.?)

Others in the room saw the need to pair these models with insight into the conditions of the farming family to better inform strategy, especially in the long-term with regard to the next generation of farmers.   The questions remain, how to accelerate the work of creating models that are grounded in farmer perception, and what are next steps to improve the usefulness of models. 

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