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.
Authors
Research Associate Boston College
Arthur is a Research Associate of the IFS and holds the Barbara A. and Patrick E. Roche chair in economics at Boston College.
Johns Hopkins University
Working Paper details
- DOI
- 10.1920/wp.cem.2007.1407
- Publisher
- Institute for Fiscal Studies
Suggested citation
Hu, Y and Lewbel, A. (2007). Nonparametric identification of the classical errors-in-variables model without side information. London: Institute for Fiscal Studies. Available at: https://ifs.org.uk/publications/nonparametric-identification-classical-errors-variables-model-without-side-information (accessed: 1 July 2024).
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