In this video Johannes Kossmann presents the results from the group work on numerical modelling. Compare it with your own work and join the discussion.
While interpreting results of a model we have to accomplish three things: We have to phrase results that are usually contained in mathematical expressions in words that can be understood …
When analyzing environmental policy measures, we often have to face more than a single problem. For instance, we might have to regulate emissions but do not know for certain, how …
Solving the model is a crucial step, as it shows whether a model that we have developed is indeed useful, or whether it needs to be changed. Can the model …
This week we have learned different mathematical model types, their impact on the obtainable solutions and the limitations imposed by data availability. Compared to the Problem and Model steps of …
When you finally got your model results there are two things to do: first, you need to make sure the numbers are correct; and second, you need to transfer the …
Getting the data needed to run a numerical model is oftentimes the most frustrating part of the whole modeling process, simply for the fact that data is hard to get …
Modern computer capacities and advances in modeling software and algorithms make numerical modeling much more accessible than a few decades ago. Nevertheless, basic understandings of the mathematical model structure and …
In this week we want to learn how to actually solve our numerical models, and produce the numbers we want to interpret. In week 3 you learned how to design …
In this live step the educators discussed the assignments uploaded by the Case Study Groups in a round table discussion. During the live event, which took place on Google Hangouts, …
Modeling is an extremely complex process. While we enjoy your submissions and try to answer all your questions, we can do so in this framework only to a certain degree. …
In Step 3.6 you have learned that the choice of optimization or equilibrium formulation is often more a choice of preferences in model design and the underlying economic thinking than …
Often the optimization and equilibrium approach can be transferred into each other and are thereby equally fitted for your model. Naturally, there are plenty of computational reasons to choose one …
Contrary to an optimization problem, an equilibrium model has no objective but consists of the respective conditions that need to hold when the market or system is in equilibrium, meaning …