A New Approach to Model Verification, Falsification and Selection

This paper shows that a qualitative analysis can always be used in evaluating a model's validity both in general and compared to other hypothesized models. The analysis relates the sign patterns and possibly other information of hypothesized structural arrays to the sign pattern of the estimated reduced form. It is demonstrated that such an analysis can always potentially falsify the hypothesized structural sign patterns or support an analysis of the relative likelihoods of alternative structural hypotheses, if neither are falsified. It is also noted that a partially specified structural hypothesis can be sometimes falsified by estimating as few as one reduced form equation. Additionally, zero restrictions in the structure can themselves be falsified; and, when so, current practice proposes estimated structural arrays that are impossible. It is further shown how the information content of the hypothesized structural sign patterns can be measured using Shannon's (1948) concept of entropy. In general, the lower the hypothesized structural sign pattern's entropy, the more a priori information it proposes about the sign pattern of the estimated reduced form. As an hypothesized structural sign pattern has a lower entropy, it is more subject to type 1 error and less subject to type 2 error.