Systems of Dynamic Simultaneous Equations

This chapter serves to point out some possible extensions of the models considered so far and to draw attention to potential problems related to such extensions. So far, we have assumed that all stochastic variables of a system have essentially the same status in that they are all determined within the system. In other words, the model describes the joint generation process of all the observable variables of interest. In practice, the generation process may be affected by other observable variables which are determined outside the system of interest. Such variables are called exogenous or unmodelled variables. In contrast, the variables determined within the system are called endogenous. Although deterministic terms can be included in the set of unmodelled variables, we often have stochastic variables in mind in this category. For instance, weather related variables such as rainfall or hours of sunshine are usually regarded as stochastic exogenous variables. As another example of the latter type of variables, if a small open economy is being studied, the price level or the output of the rest of the world may be regarded as exogenous. A model which specifies the generation process of some variables conditionally on some other unmodelled variables is sometimes called a conditional or {partial model} because it describes the generation process of a subset of the variables only.