A standard MFA gives an overview of the current, or even historical, material status in a country (or economy). But in order to approach issues like sustainable development, there is also a need to analyze possible future developments of material flows. This is especially true when analyzing how different policies (environmental and others) may affect the material flows in a society.
The flows of materials are to a large degree determined by the broad interplay between different agents (the consumers and producers) that characterizes economies today. There is, for instance, a large volume of deliveries inside and between the different production sectors. Changes in the end consumption of a product will have repercussions through most sectors in the economy, since it is not only the producer of the product that must change the production but also producers of intermediate goods and raw materials. When studying the use of materials in an economy it is important to consider this complexity. Economic models do attempt to handle this interaction between economic agents and can therefore be considered as suitable tools for predicting and analyzing the consumption of materials.
For the purpose of this chapter economic activity is considered to be a driver of material consumption, and not vice versa. In the real world, the causality is more likely to be two-directional.
When doing a forecast of material flows (subject to the above caveat) one has to choose a model that describes the society, or economy, that the forecast will cover. This model may be rather simple. For instance, it may just extrapolate existing, and historical, trends for the variables one is analyzing. An illustration of this method is to use an input-output model (see Chapter 10) and extend it into the future with estimated growth rates for different economic activities. The model may also be more complicated and take into account interactions between different (economic) sectors and activities. For this type of forecast one often uses macroeconomic models, and preferably so-called 'computable general equilibrium' (CGE) models. This chapter will consider some examples of forecasting and policy analysis based on the second alternative, in the form of economic models, to see how they could be used together with information about material flows in order to forecast these flows.
When using models to do a forecast it is important to keep in mind that it will only give a picture of a possible development; it can never be looked upon as a definite answer. A forecast is most useful when comparing different possible developments, and especially in seeing how different policy measures might affect the development. One often starts with a business-as-usual path; that is, what is thought to be the most likely development given actual trends and today's policy. Then, by using the model, one constructs one or more new paths where the measure to be analyzed is implemented. Comparing these various paths gives a picture of how effective the measure might be.
It is also important to keep in mind that a model is necessarily a description of a limited aspect of a society. A model builder must always make a choice between simplicity and realism; the simpler (and maybe more user-friendly) the model, the less realistic. A model that is very detailed and hence more realistic runs the risk of being difficult to manage (although modern computer science has largely eliminated computational problems) and, worse, opaque. The more complicated the model is the more difficult it will be to interpret the results, and to determine how different effects interrelate. This is a crucial point, because it explains why most economic models up to now have neglected material/energy flows.
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