How common is identification in parametric models?

This paper examines whether identification is a ‘common’ or ‘rare’ phenomenon in nonlinear parametric models. For several broad classes of models, it is shown that there is an open and dense subset of identified models, and that consequently the set of nonidentified models is nowhere dense. The resu...

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Bibliographic Details
Published in:Journal of econometrics 1992-07, Vol.53 (1), p.5-23
Main Author: McManus, Douglas A.
Format: Article
Language:English
Subjects:
Applications
Econometrics
Economic models
Economic statistics
Economic theory
Exact sciences and technology
Identification
Mathematics
Probability and statistics
Sciences and techniques of general use
Statistics
Utility functions
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Summary:This paper examines whether identification is a ‘common’ or ‘rare’ phenomenon in nonlinear parametric models. For several broad classes of models, it is shown that there is an open and dense subset of identified models, and that consequently the set of nonidentified models is nowhere dense. The results of this paper suggest that the assumption of linearity in functional relationships to ease the conceptual and computational development of a theory can drastically limit the estimability of the model. An interesting feature of this paper is that global identification is established in the context of nonlinear models.
ISSN:0304-4076
1872-6895
DOI:10.1016/0304-4076(92)90077-5