Nonparametric identification of the classical errors-in-variables model without side information

Susanne Schennach, Yingyao Hu and Arthur Lewbel ()
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Susanne Schennach: University of Chicago

No 674, Boston College Working Papers in Economics from Boston College Department of Economics

Abstract: This note establishes that the fully nonparametric classical errors-in-variables model is identifiable from data on the regressor and the dependent variable alone, unless the specification is a member of a very specific parametric family. This family includes the linear specification with normally distributed variables as a special case. This result relies on standard primitive regularity conditions taking the form of smoothness and monotonicity of the regression function and nonvanishing characteristic functions of the disturbances.

Keywords: errors in variables; nonparametric estimation; identification (search for similar items in EconPapers)
JEL-codes: C20 C14 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2007-07-16
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Working Paper: Nonparametric identification of the classical errors-in-variables model without side information (2007)
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