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Measuring Research Intensity from Anonymized Data: Does Multiplicative Noise with Factor Structure Save Results Regarding Quotients?

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Author Info
Gerd Ronning () (Universität Tübingen)
Abstract

Economic researchers often consider quotients like R&D investment divided by sales which could be used to measure “research intensity” of firms if available. However, data on research in particular are highly confidential and would not be released in original form. Therefore scientific use files have to be generated from anonymized micro data. The paper considers joint anonymization of all variables by multiplicative noise which stems from a bimodal mixture distribution and can be regarded as an error model with factor structure. It is shown that quotients such as research intensity are not modified considerably by this procedure. However, already quotients from original data can give quite misleading results which is illustrated by simulation results and an empirical example using the German Cost Structure Survey.

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Publisher Info
Article provided by Justus-Liebig University Giessen, Department of Statistics and Economics in its journal Journal of Economics and Statistics.

Volume (Year): 228 (2008)
Issue (Month): 5-6 (December)
Pages: 644-653
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Handle: RePEc:jns:jbstat:v:228:y:2008:i:5+6:p:644-653

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Web page: http://wiwi.uni-giessen.de/home/oekonometrie/Jahrbuecher/
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Related research
Keywords: Data masking; measurement error; mixture distribution; R&D;

Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Microeconomic Data
O30 - Economic Development, Technological Change, and Growth - - Technological Change - - - General

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This page was last updated on 2009-12-17.


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