Conditions for Identification in Nonparametric and Parametic Models.

Abstract

It is argued that most econometric models are nonparametric and that parameterizations should typicall y be viewed as approximations made for purposes of estimation. These parameterizations should not be used to judge identification when the y are not a precise representation of prior information. Identificati on in a nonparametric context is defined and theorems are developed t hat aid in judging the identifiability of both nonparametric and para metric models. Examples are given that illustrate the usefulness of t hese results for determining sources of identification. Copyright 1988 by The Econometric Society.