| Summary: | Model selection criteria are used in many contexts in economics. The issue of determining
an appropriate criterion, or alternative method, for model selection is a topic
of much interest for applied econometricians. These criteria are used when formal
testing methods are difficult due to a large number of models being compared, or
when a sequential modelling strategy is being used. In econometrics, we are familiar
with the use of model selection criteria for determining the order of an ARMA
process and the number of dependent variable lags in Augmented Dickey-Fuller equations.
The latter application is examined as an interesting example of the sensitivity
of results to the choice of criterion. An application of model selection criteria to spline
fitting is also considered, introducing a new, flexible, modelling strategy for technical
progress in a production economy and for returns to scale in a resource economics
context.
In this latter context we have a system of estimating equations. Two of the criteria
which are compared are the Cross-Validation score (CV) and the Generalized Cross-
Validation Criterion (GCV), which until now have only had single equation context
expressions. Multiple equation expressions for these criteria are introduced, and are
used in the two applications.
Comparison of the models selected by the different criteria in each context reveals
that results can differ greatly with the choice of criterion. In the unit root test application,
the choice of criterion influences the number of times the false hypothesis is
not rejected. In the production economy and resource applications, measures of technical
progress and returns to scale differ greatly, as do own and cross price elasticities, depending on which criterion is used for selecting the appropriate spline structure.
An overview of the literature on model selection is given, with new expressions
and interpretations for some model selection criteria, and historical notes.
|
|---|
