The Tradeoff Analysis Model for Multi-dimensional Impact Assessment (TOA-MD) is a parsimonious, generic model for analysis of technology adoption (e.g. adaptation strategies), impact assessment (e.g. climate change), and ecosystem services analysis. The TOA-MD model simulates technology adoption and impact in a population of heterogeneous farms. There are several features of this model that are novel as compared to most other economic models being used for technology adoption and climate impact assessment. The TOA-MD represents the whole farm production system (i.e. includes crops, livestock and aquaculture sub-system, and the farm household characteristics). The TOA-MD is a model of a farm population, not a model of an individual or “representative” farm. Accordingly, the fundamental parameters of the model are population statistics – means, variances and correlations of the economic variables in the models and the associated outcome variables of interest. With suitable bio-physical and economic data, these statistical parameters can be estimated for current systems. Using established methods we can estimate how the TOA-MD model parameters would change in response to climate change or technological adaptations. These changes in model parameters are the basis for the climate impact, vulnerability and adaptation analysis.
The Tradeoff Analysis for Multi-Dimensional Impact Assessment (TOA-MD) is a simulation model designed to be used by multi-disciplinary research or technology deployment projects to carry out quantitative assessments of economic, environmental and social impacts associated with the adoption of agricultural technologies. TOA-MD has a number of desirable features: - Feasible and low-cost: TOA-MD can be implemented with the kinds of data that are typically available or that can be acquired in the course of a research or technology deployment project at reasonable cost. TOA-MD can be used to target data collection, thus avoiding the “shotgun” approach to data collection and lowering the cost of impact assessment. - User friendly: TOA-MD can be learned and used by researchers following the Learning Modules that are distributed with the model and by attending training workshops organized by the TOA team, plus time needed to acquire data and carry out analysis. TOA-MD is programmed in Excel, and provides a data template to help users identify data needed to carry out an analysis. - Scientifically credible: TOA-MD meets the standard of good science: it is based on a rigorous statistical and economic foundation of research published in respected, peer-reviewed journals; environmental indicators can be based on data in the scientific literature, on field measurements, or derived from process based simulation models. - Accurate: TOA-MD produces results comparable to what can be achieved with much more complex simulation models. - Consistent, transparent, and a public good: TOA-MD provides a generic framework that can be applied to most systems, thus providing comparability across projects. The model is public and transparent. Data and analysis can be evaluated independently, and data developed by projects can be archived and used by other projects.
The TOA Team may be able to offer some limited technical support to TOA-MD Model users upon request. However, we ask users to be aware that the free technical support we provide is a voluntary activity and our ability to respond to questions is limited.
The TOA Project Team also periodically offers training courses to interested organizations and user groups. We encourage prospective users of the TOA-MD model to incorporate training plans into their project plans and budgets. Please contact us to estimate the costs of a training plan and availability. Based on our experience, we recommend a series of two, 3-5-day workshops. At the first workshop, the TOA-MD model concepts and software are covered, and data requirements of the users' projects are discussed. After the first workshop, participants collect data and carry out preliminary analysis. At the second workshop, the participants' data and analysis are reviewed, questions are addressed.
Summary of uses:
• Carrying out quantitative assessments of economic, environmental and social impacts associated with the adoption of agricultural technologies, environmental and economic changes and ecosystem services
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