Causal reasoning in systems modelling

This paper will not discuss the philosophy of causality in depth, but will focus on its applications to the modelling of macroeconomic systems. There has been much discussion in econometrics about the extraction of structural parameters. This is the question of ‘identification’, and there are well-established procedures for this extraction. Equations estimated in econometrics usually provide the functional relations among variables or economic indicators. However, economists are not only concerned with mathematical connections, as the causal relations between variables are also considered to be important. Qualitative models in economics are usually specified in terms of variables and their relations. Moreover, data sets are not always available in qualitative models. Therefore, one possible approach for economic prediction is to apply causal reasoning methods to qualitative models. In this paper, modifications to the causal ordering concepts of Simon and Iwasaki will be proposed. A discussion on recent approaches for different types of tests for causality on stochastic models is also provided.