By G. Flichman, K. Louhichi, J. M. Boisson (auth.), Guillermo Flichman (eds.)
The bio-economic modeling procedure awarded during this e-book is due to the special advancements: via one part, the development of bio-physical simulation versions utilized to agricultural platforms and via the opposite, the evolution of agricultural guidelines not easy a type of evaluation that traditional financial versions cannot offer. a few economists started to detect that biophysical versions may be regarded as distinctive engineering creation features, permitting to symbolize in a constant demeanour the joint items of agricultural actions. The views that this imaginative and prescient offers permit facing environmental and normal assets matters with an financial standpoint in an effective demeanour. Representing environmental affects of agricultural actions measured in actual devices permits appearing cost-efficiency calculations of other rules, possibly in a position to reach particular coverage ambitions. This strength accredited in recent times the improvement of utilized study comparable with institutional calls for from nationwide and overseas public associations. yet this process calls for a multidisciplinary technique, with optimistic and unwanted effects. The confident one is, either for economists and biophysical scientists, to amplify their imaginative and prescient of the realm. The unwanted effects are the larger hassle to get well-known of their particular self-discipline, the stumbling blocks to procure the required details for correctly use those versions, and the longer time to accomplish the examine job. The “productivity” for generating papers is decrease for economists employing this technique in comparison with economists utilising econometric equipment, utilizing on hand released information. inspite of those unwanted effects, because the calls for from the true global for the overview those versions may be able to supply is expanding, it's relatively attainable that there's a destiny for bio-economic versions utilized to agricultural structures. The demanding situations of weather swap, the rise take care of the upkeep of typical assets and the surroundings would require additional advancements of this type of approach.
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Extra info for Bio-Economic Models applied to Agricultural Systems
This line of criticisms against “estimated” production functions is also valid for all the methods known under the label of “data envelopment analysis”,5 as illustrated by the blue line of Fig. 1: indeed, it would be possible to derive an estimated isoquant (from which a full production function could be derived) from this “frontier”, the convex hull of observed production points. But apart from the fact that such a function would be difficult to handle (it is not smooth nor derivable), there are no indications of how much even the frontier production points are “inefficient”, nor why other points are so.
Once the first decision has been carried out, the system evolves (the decision-maker knows the response of nature) and the agent can adjust later decisions according to the new information available. The method consists in solving the dynamic problem by making a series of sequential optimisations, thus it is a recursive method where each optimisation comprises a dynamic model. Consequently, at moment 1, the decision-maker chooses a decision plan by taking into account all the information available at this moment.
In particular, if one maximizes the national welfare, a solution of the model could very well that one category of the population should be sacrificed. This is not realistic, nor compatible with the basic theorems of the welfare economics. But the input/output analysis is 2 Bio Physical Models as Detailed Engineering Production Functions 25 also compatible with the consideration of many agents, each optimizing their own objectives, under common constraints and information channels. 3 Multi-agent Input/Output Models Consider a model with two agents, 1 and 2, agent 1 producing x1 and agent 2 x2 (x1 and x2 can be some vector of productions or techniques) subject to agent specific resources the levels of which are k1 and k2 respectively and common resources the level of which is h.
Bio-Economic Models applied to Agricultural Systems by G. Flichman, K. Louhichi, J. M. Boisson (auth.), Guillermo Flichman (eds.)