Data Masking by Noise Addition and the Estimation of Nonparametric Regression Models
Lechner Sandra () and
Winfried Pohlmeier ()
Authors registered in the RePEc Author Service: Sandra Nolte (Lechner) ()
Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), 2005, vol. 225, issue 5, 517-528
Data collecting institutions use a large range of masking procedures in order to protect data against disclosure. Generally, a masking procedure can be regarded as a kind of data filter that transforms the true data generating process. Such a transformation severely affects the quality of the data and limits its use for empirical research. A popular masking procedure is noise addition, which leads to inconsistent estimates if the additional measurement errors are ignored.
Keywords: Data masking; errors-in-variables; SIMEX; local polynomial regression (search for similar items in EconPapers)
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