A Goodness-of-Identifiability Criterion for Parametric Statistical Models

David Pacini

Journal of Statistical and Econometric Methods, 2022, vol. 11, issue 4, 1

Abstract: This note sets out a goodness-of-identifiability criterion. This criterion quantifies the identifying strength of a parametric statistical model. Unlike the qualitative criterion for identifiability based only on the Fisher matrix, it applies to both regular and irregular points of the Fisher matrix. Unlike the qualitative criterion based only on the Hellinger distance, it quantifies set-identification. Â JEL classification numbers: C10, C50.

Keywords: Parametric statistical model; Identifiability; Fisher matrix; Hellinger distance. (search for similar items in EconPapers)
Date: 2022
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