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Dynamic evolutions of resource stocks with stochastic elements in the transition equation are in general very difficult to master. Their handling requires a deep understanding of control theory, probability theory and sometimes even of game theory due to strategic interaction of 'agents'. But without strong mathematical backgrounds, students from adjacent research fields have a hard time with control theory. The same is true for probability theory and game theory. One way to avoid this problem is to change the aim: instead of target function optimization, guarantee the continuance of the system within certain boundaries. The latter relates to Viability theory. Unfortunately, even Viability theory requires more mathematics than the 'average' student is prepared for. The paper at hand will demonstrate how Excel can help here. Excel is applied since it is a widespread tool and most students are familiar with its basic features. Therefore students can concentrate on how to implement a dynamic system in a spreadsheet and how to simulate probability distributions and approximate the distribution of the target function - given different control rules. This enables them to assess opportunities and risks associated with these control rules. One topic appropriate to demonstrate the idea is renewable resource management. As many studies state, there is a deficit in sustainable learning not only in economics (Salemi and Siegfried 1999; Walstad and Allgood 1999) , but particular in system dynamic models (Moxnes, E. 2000; Pala and Vennix 2005). This is due to the complexity associated with long run- and feedback effects, and the complexity becomes even harder when stochastic development is included. The purpose of this paper will be to inspire students and to encourage them to solve stochastic dynamic problems later on their own with the simple tools at hand presently.


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