In both theoretical and applied modeling in behavioral sciences, it is common to choose a mathematical specification of functional form and distribution of unobservables on grounds of analytic convenience without support from explicit theoretical postulates. This article discusses the issue of deriving particular qualitative hypotheses about functional form restrictions in structural models from intuitive theoretical axioms. In particular, we focus on a family of postulates known as dimensional invariance. Subsequently, we discuss how specific qualitative postulates can be reformulated so as (...) to allow for conventional statistical hypothesis testing, and we also derive details of a particular likelihood ratio test procedure. An empirical application of the testing procedure is carried out, based on data from a Stated Preference survey. (shrink)

The first invariance principle, called “meaningfulness,” is germane to the common practice requiring that the form of a scientific law must not be altered by a change of the units of the measurement scales. By itself, meaningfulness does not put any constraint on the possible data. The second principle requires that the output variable is “order-invariant” with respect to any transformation (of one of the input variables) belonging to a particular family or class of such transformations which are characteristic of (...) the law. These principles are formulated as axioms of a theory. Taken together, meaningfulness and order-invariance axioms have strong consequences on the feasible theories. Three applications of our results are discussed in details, involving the Lorentz–FitzGerald contraction, Beer's law, and the Monomial laws, each of which is derived from three axioms implementing meaningfulness and order-invariance concepts. (An “initial condition” axiom is also used.) Not all scientific laws are order-invariant in the sense of this paper. An example is van der Waals' equation. (shrink)

Amartya Sen has developed the so-called capability approach to meet the criticism that income alone may be insufficient as a measure of economic inequality. This is because knowledge about people’s income does not tell us what they are able to acquire with that income. For example, people with the same income may not have the same access to health and transportation services, schools and opportunities in the labor market. Recently, there has been growing interest in empirical studies based on the (...) capability approach. Most of these, however, are only loosely related to quantitative behavioral theory, at least in a concrete and empirically operational way. The purpose of this paper is to demonstrate that the theory of random scale models offers a powerful theoretical and empirical framework for representing and accounting for key aspects of Sen’s theory. (shrink)