JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. The Econometric Society is collaborating with JSTOR to digitize, preserve and extend access to Econometrica. http://www.jstor.org  A theory of identification is developed for a general stochastic model whose probability law is determined by a finite number of parameters. It is shown under weak regularity conditions that local identifiability of the unknown parameter vector is equivalent to nonsingularity of the information matrix. The use of "reduced-form" parameters to establish identifiability is also analyzed. The general results are applied to the familiar problem of determining whether the coefficients of a system of linear simultaneous equations are identifiable.
Rothenberg REF shows that if the rank of the FIM is constant over some open neighborhood of the desired parameter, then the nonsingularity of the FIM is equivalent to the local identifiability of the desired parameter.
Identification in Parametric Models
Econometrica
Mathematics