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Operationalising ‘safe statistics’: the case of linear regression

Author

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  • Felix Ritchie

    (University of the West of England, Bristol)

Abstract

The recent growth in research access to confidential government microdata has prompted the development of more general 'output-based statistical disclosure control' (OSDC) methods which go beyond tabular protection. Central to OSDC is the concept of 'safe/unsafe statistics', allowing researchers and facility owners to make informed judgments about the types of research output that pose a disclosure risk. While increasingly accepted in specialist environments, in the wider community this novel approach causes some concern: how can 'safe' be unconditional? This paper therefore demonstrates the new approach using linear regression, a key research output, as an example. In doing so, the paper reconsiders the objectivity of SDC decision-making, arguing that ‘safety’ be explicitly acknowledged as a relative concept.

Suggested Citation

  • Felix Ritchie, 2014. "Operationalising ‘safe statistics’: the case of linear regression," Working Papers 20141410, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    • Handle: RePEc:uwe:wpaper:20141410
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    File URL: http://www2.uwe.ac.uk/faculties/BBS/BUS/Research/General/Economics%20papers%202014/1410.pdf
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    Cited by:

    1. Felix Ritchie & Jim Smith, 2019. "Confidentiality and linked data," Papers 1907.06465, arXiv.org.

    More about this item

    Keywords

    statistical disclosure control; confidentiality; safe statistics; regression;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other

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