To Blank or Not to Blank? A Comparison of the Effects of Disclosure Limitation Methods on Nonlinear Regression Estimates

Josep Domingo-Ferrer, Vicenç Torra: PRIVACY IN STATISTICAL DATABASES, Springer Verlag Lecture Notes in Computer Science, 2004

Posted: 17 Jul 2006

See all articles by Sandra Nolte (Lechner)

Sandra Nolte (Lechner)

Lancaster University Management School

Winfried Pohlmeier

University of Konstanz - Department of Economics & Center of Finance & Econometrics (CoFE)

Abstract

Statistical disclosure limitation is widely used by data collecting institutions to provide safe individual data. However, the choice of the disclosure limitation method severely affects the quality of the data and limit their use for empirical research. In particular, estimators for nonlinear models based on data which are masked by standard disclosure limitation techniques such as blanking or noise addition lead to inconsistent parameter estimates.

This paper investigates to what extent appropriate econometric techniques can obtain parameter estimates of the true data generating process, if the data are masked by noise addition or blanking. Comparing three different estimators - calibration method, the SIMEX method and a semiparametric sample selectivity estimator - we produce Monte-Carlo evidence on how the reduction of data quality can be minimized by masking.

Keywords: disclosure limitation, blanking, semi-parametric selection models, errors in variables in nonlinear models

JEL Classification: C21, J24, J31

Suggested Citation

Nolte (Lechner), Sandra and Pohlmeier, Winfried, To Blank or Not to Blank? A Comparison of the Effects of Disclosure Limitation Methods on Nonlinear Regression Estimates. Josep Domingo-Ferrer, Vicenç Torra: PRIVACY IN STATISTICAL DATABASES, Springer Verlag Lecture Notes in Computer Science, 2004, Available at SSRN: https://ssrn.com/abstract=916482

Sandra Nolte (Lechner) (Contact Author)

Lancaster University Management School ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Winfried Pohlmeier

University of Konstanz - Department of Economics & Center of Finance & Econometrics (CoFE) ( email )

Konstanz, D-78457
Germany

HOME PAGE: http://econometrics.wiwi.uni-konstanz.de

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
1,179
PlumX Metrics