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Journal of Official Statistics

The Journal of Statistics Sweden

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2001-7367
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Access to Sensitive Data: Satisfying Objectives Rather than Constraints

Felix Ritchie
Published Online: 2014-09-02 | DOI: https://doi.org/10.2478/jos-2014-0033

The argument for access to sensitive unit-level data produced within government is usually framed in terms of risk and the legal responsibility to maintain confidentiality. This article argues that the framing of the question may restrict the set of possibilities; a more effective perspective starts from the data owner’s principles and user needs. Within this principlesbased framework, the role of law changes: It becomes an ‘enabling technology’, helping to define the solution but playing no role in setting the objectives.

This shift in perspective has a number of consequences. The perception of ‘costs’ and ‘benefits’ is reversed. Law and established practice are distinguished and appropriately placed within a cost-benefit framework. The subjectivity and uncertainty in risk assessments is made explicit. Overall, all other things being equal, the expectation is that a move towards objective-based planning increases data access and improves risk assessment.

This alternative perspective also addresses the problem of the public-good nature of research outputs. It encourages the data owner to engage with users and build a case for data access taking account of the wider needs of society.

The UK data access regime is used as the primary example of the arguments in this article

Keywords: Confidential data; data access; data security; public goods; risk

References

  • Brandt, M., L. Franconi, C. Guerke, A. Hundepool, M. Lucarelli, J. Mol, F. Ritchie, G. Seri, and R. Welpton. 2010. Guidelines for the Checking of Output Based on Microdata Research. Final report of ESSnet sub-group on output SDC, Eurostat. Available at: http://neon.vb.cbs.nl/casc/ESSnet/guidelines_on_outputchecking.pdf (accessed 10th June 2014).Google Scholar

  • Buurman, M., J. Delfgaauw, R. Dur, and S. van den Bossche. 2012. Public Sector Employees: Risk Averse and Altruistic? CESifo Working Paper: Behavioural Economics, No. 3851. Available at: http://www.econstor.eu/handle/10419/61046 (accessed 10th June 2014).Google Scholar

  • De Martino, B., D. Kumuran, B. Seymour, and R. Dolan. 2006. “Frames, Biases, and Rational Decision-Making in the Human Brain.” Science 313: 684-687. Available at: http://www.sciencemag.org/content/313/5787/684.full.pdf?sid¼e7dcf2c8-5bbb-4d89-97f2-5344613de9bf (accessed 10th June 2014).Google Scholar

  • Duncan, G., S. Keller-McNulty, and L. Stokes. 2001. Disclosure Risk vs Data Utility: the R-U Confidentiality Map. NISS Technical Report no. 121. Available at: http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid¼6BF9C4E902605252F4302A43786EF152?doi¼10.1.1.79.1598&rep¼rep1&type¼pdf (accessed 10th June 2014).Google Scholar

  • Hall, K. 2013. “Can Government Change its Risk-Averse Take on Security?” Computer Weekly, February 7, 2013. Available at: http://www.computerweekly.com/news/2240177688/Can-government-change-its-risk-averse-take-on-security (accessed 10th June 2014).Google Scholar

  • House of Lords 2006. Government Policy on the Management of Risk. Select Committee on Economic Affairs, 5th Report of Session 2005-06, Available at: http://www.publications.parliament.uk/pa/ld200506/ldselect/ldeconaf/183/183i.pdf (accessed 10th June 2014).Google Scholar

  • ISTAT 2013. Micro-data: A Crucial Asset for Statistical Systems. UNECE/CES 61st Plenary Session, item 4(b). Available at: http://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/2013/31.pdf (accessed 10th June 2014).Google Scholar

  • Kahneman, D. 2012. Thinking, fast and slow. London: Penguin Books.Google Scholar

  • Kahneman, D., J. Knetsch, and R. Thaler. 1991. “Anomalies: the Endowment Effect, Loss Aversion and Status Quo Bias.” Journal of Economic Perspectives 5:193-206. Available and reprinted at: http://www.jstor.org/stable/1942711 (accessed 10th June 2014).CrossrefGoogle Scholar

  • Mellers, B., A. Schwartz, and I. Ritov. 1999. “Emotion-Based Choice.” Journal of Experimental Psychology: General 128:332-345. Reprinted at http://www.researchgate.net/publication/215515670_Emotion-based_choice/file/79e4150b79f973939f.pdf (accessed 10th June 2014).Google Scholar

  • OAG 1998. Innovation in the Federal Government: The Risk not Taken. Public Policy Forum discussion paper, Office of the Auditor General of Canada. Available at: http:// www.oag-bvg.gc.ca/internet/English/meth_gde_e_10193.html (accessed 10th June 2014).Google Scholar

  • Pfeifer, C. 2008. Risk Aversion and Sorting into Public Sector Employment. IZA Discussion Papers no. 3503. Available at: http://ftp.iza.org/dp4401.pdf (accessed 10th June 2014).Google Scholar

  • Ritchie, F. 2009. “UK Release Practices for Official Microdata.” Journal of the International Association of Official Statisticians. 26(3/4): 103-111. DOI: http://dx.doi.org/10.3233/SJI-2009-0706.CrossrefGoogle Scholar

  • Ritchie, F. 2013. “International Access to Restricted Data - a Principles-Based Standards Approach.” Statistical Journal of the International Association of Official Statisticians. 29: 289-311. Reprinted at DOI: http://dx.doi.org/10.3233/SJI-130780.CrossrefGoogle Scholar

  • Ritchie, F. and R. Welpton. 2012. “Data Access as a Public Good.” In Work session on statistical data confidentiality 2011, UNECE/Eurostat. Available at: http://www.unece. org/fileadmin/DAM/stats/documents/ece/ces/ge.46/2011/presentations/21_Ritchie- Welpton.pdf (accessed 10th June 2014).Google Scholar

  • Samuelson, W. and R. Zeckhauser. 1988. “Status Quo Bias in Decision Making.” Journal of Risk and Uncertainty 1: 7-59. Available at: http://dtserv2.compsy.uni-jena.de/__C125757B00364C53.nsf/0/F0CC3CAE039C8B42C125757B00473C77/%24FILE/samuelson_zeckhauser_1988.pdf (accessed 10th June 2014). Google Scholar

  • Skinner, C. 2012. “Statistical Disclosure Risk: Separating Potential and Harm.” International Statistical Review 80: 349-368. Available at: http://onlinelibrary.wiley.com/doi/10.1111/j.1751-5823.2012.00190.x/pdf (accessed June 10, 2014).Web of ScienceCrossrefGoogle Scholar

  • Trewin, D., A. Andersen, T. Beridze, L. Biggeri, I. Fellegi, and T. Toczynski. 2007. Managing Statistical Confidentiality and Microdata Access: Principles and Guidelines of Good Practice. Geneva: UNECE /CES. Available at http://www.unece.org/stats/publications/Managing.statistical.confidentiality.and.microdata.access.pdf (accessed 10th June 2014).Google Scholar

  • Varian, H. 1992. Microeconomic Analysis. 3rd ed. New York: W.W. Norton.Google Scholar

  • Viscusi, K., W. Magat, and J. Huber. 1987. “An Investigation of the Rationality of Consumer Valuations of Multiple Health Risks.” Rand Journal of Economics 18: 465-479. Available at: http://www.jstor.org/discover/10.2307/2555636?uid¼3738032&uid¼2&uid¼4&sid¼21102275515957 (accessed 10th June 2014). CrossrefGoogle Scholar

About the article

Received: 2012-07-01

Revised: 2013-09-01

Accepted: 2014-01-01

Published Online: 2014-09-02

Published in Print: 2014-09-01


Citation Information: Journal of Official Statistics, ISSN (Online) 2001-7367, DOI: https://doi.org/10.2478/jos-2014-0033.

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© by Felix Ritchie. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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