SIMPLICITY, SCIENTIFIC INFERENCE AND ECONOMETRIC MODELING

Two issues are discussed in this paper. The first is whether a formal definition and justification of simplicity (parsimony) in scientific i nference can be found, and whether an optimal level of simplicity is o btainable. A definition of simplicity is possible, as are the optimum conditions for the desired degree of simplicity. The model of inferenc e used here relates Bayesian inference to algorithmic information theo ry. Simplicity is examined in the light of induction, the Duhem-Quine thesis, and bounded rationality. The second issue relates to the role that simplicity might play in econometric modelling. This is elucidate d with some remarks on the 'general to specific' approach to modelling and discussion on the purpose of a model.