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Secure access to confidential microdata: four years of the Virtual Microdata Laboratory

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  • Felix Ritchie

    (Office for National Statistics)

Abstract

Explains how this has become ONS's solution to providing access to sensitive microdata while maintaining its confidentiality and securityThis article explains how the Virtual Microdata Laboratory (VML) has become the Office for National Statistics' solution to providing access to sensitive microdata while maintaining the confidentiality and security of the data. In the four years since it was set up, the VML has gone from almost nothing to becoming a major resource for UK academic researchers. The VML has enabled both more detailed and wider research, and has influenced policy making at all levels. Looking ahead, the VML faces significant challenges and a bright future. Economic & Labour Market Review (2008) 2, 29–34; doi:10.1057/elmr.2008.73

Suggested Citation

  • Felix Ritchie, 2008. "Secure access to confidential microdata: four years of the Virtual Microdata Laboratory," Economic & Labour Market Review, Palgrave Macmillan;Office for National Statistics, vol. 2(5), pages 29-34, May.
    • Handle: RePEc:pal:ecolmr:v:2:y:2008:i:5:p:29-34
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    Cited by:

    1. Bunn, Philip & Ellis, Colin, 2011. "How do individual UK consumer prices behave?," Bank of England working papers 438, Bank of England.
    2. Philip Bunn & Colin Ellis, 2012. "How do Individual UK Producer Prices Behave?," Economic Journal, Royal Economic Society, vol. 122(558), pages 16-34, February.
    3. Thomas Abhayaratna & Andrew Carter & Shane Johnson, 2022. "The ATO Longitudinal Information Files (ALife): Individuals—A New Dataset for Public Policy Research," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 55(4), pages 541-557, December.
    4. Harimohan, Rashmi, 2012. "How has the risk to inflation from inflation expectations evolved?," Bank of England Quarterly Bulletin, Bank of England, vol. 52(2), pages 114-123.
    5. Frank Dunstan & David L Fone & Myer Glickman & Stephen Palmer, 2013. "Objectively Measured Residential Environment and Self-Reported Health: A Multilevel Analysis of UK Census Data," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-7, July.
    6. Stefan Bender, 2014. "Datenzugang in Deutschland: Der Paradigmenwechsel hat bereits stattgefunden," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 8(4), pages 237-248, November.
    7. Jamie C. Moore & Peter W. F. Smith & Gabriele B. Durrant, 2018. "Correlates of record linkage and estimating risks of non‐linkage biases in business data sets," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1211-1230, October.
    8. Maule, Becky & Pugh, Alice, 2012. "Do inflation expectations currently pose a risk to the economy?," Bank of England Quarterly Bulletin, Bank of England, vol. 53(1), pages 110-121.
    9. Macallan, Clare & Taylor, Tim & O'Grady, Tom, 2011. "Assessing the risk to inflation from inflation expectations," Bank of England Quarterly Bulletin, Bank of England, vol. 51(2), pages 100-110.
    10. Philip Bunn & Colin Ellis, 2012. "Examining The Behaviour Of Individual UK Consumer Prices," Economic Journal, Royal Economic Society, vol. 122(558), pages 35-55, February.
    11. Tian Lan & Paul A. Longley, 2023. "An Individual Level Method for Improved Estimation of Ethnic Characteristics," International Regional Science Review, , vol. 46(3), pages 328-353, May.

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