Estimation of a linear model under microaggregation by individual ranking

Arbeitspapier

Microaggregation by individual ranking is one of the most commonly applied disclosure control techniques for continuous microdata. The paper studies the effect of microaggregation by individual ranking on the least squares estimation of a multiple linear regression model in continuous variables. It is shown that the naive parameter estimates are asymptotically unbiased. Moreover, the naive least squares estimates asymptotically have the same variances as the least squares estimates based on the original (non-aggregated) data. Thus, asymptotically, microaggregation by individual ranking does not induce any efficiency loss on the least squares estimation of a multiple linear regression model. Keywords: Asymptotic variance ; consistent estimation ; disclosure control ; individual ranking ; linear model ; microaggregation

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Discussion Paper ; No. 453

Classification and Topics

• Subject: Schätztheorie ; Multiple Regression ; Ranking-Verfahren ; Theorie

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Schmid, Matthias
• Event: Veröffentlichung
• (who): Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
• (where): München
• (when): 2005

Further information

• DOI: doi:10.5282/ubm/epub.1822
• Handle: http://hdl.handle.net/10419/31072
• URN: urn:nbn:de:bvb:19-epub-1822-1
• Last update: 10.03.2025, 11:42 AM CET