Multiplicative Measurement Error and the Simulation Extrapolation Method

24 Pages Posted: 9 May 2008

See all articles by Elena Biewen

Elena Biewen

Institute for Applied Economic Research (IAW)

Sandra Nolte (Lechner)

Lancaster University Management School

Martin Rosemann

ISG Institut für Sozialforschung und Gesellschaftspolitik

Date Written: January 1, 2008

Abstract

Whereas the literature on additive measurement error has known a considerable treatment, less work has been done for multiplicative noise. In this paper we concentrate on multiplicative measurement error in the covariates, which contrary to additive error not only modifies proportionally the original value, but also conserves the structural zeros.

This paper compares three variants to specify the multiplicative measurement error model in the simulation step of the Simulation-Extrapolation (SIMEX) method originally proposed by Cook and Stefanski (1994): i) as an additive one without using a logarithmic transformation, ii) as the well-known logarithmic transformation of the multiplicative error model, and iii) as an approach using the multiplicative measurement error model as such. The aim of the paper is to analyze how well these three approaches reduce the bias caused by the multiplicative measurement error. We apply three variants to the case of data masking by multiplicative measurement error, in order to obtain parameter estimates of the true data generating process. We produce Monte Carlo evidence on how the reduction of data quality can be minimized.

Keywords: Errors-in-variables in nonlinear models, disclosure limitation methods, multiplicative error

JEL Classification: C13,C21

Suggested Citation

Biewen, Elena and Nolte (Lechner), Sandra and Rosemann, Martin, Multiplicative Measurement Error and the Simulation Extrapolation Method (January 1, 2008). Available at SSRN: https://ssrn.com/abstract=1131136 or http://dx.doi.org/10.2139/ssrn.1131136

Elena Biewen

Institute for Applied Economic Research (IAW) ( email )

Ob dem Himmelreich 1
Tubingen, 72074
Germany

Sandra Nolte (Lechner) (Contact Author)

Lancaster University Management School ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Martin Rosemann

ISG Institut für Sozialforschung und Gesellschaftspolitik ( email )

Berlin
Germany

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
228
Abstract Views
2,058
Rank
266,255
PlumX Metrics