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Extending TSE to Administrative Data: A Quality Framework and Case Studies from Stats NZ

Author

Listed:
  • Reid Giles

    (Statistics New Zealand, 2018 Census, PO Box 2922, Wellington6140, New Zealand.)

  • Zabala Felipa

    (Statistics New Zealand, Statistical Methods, PO Box 2922, Wellington6140, New Zealand.)

  • Holmberg Anders

    (Statistics Norway, Division for Methodology, Akersveien 26 Oslo, Norway.)

Abstract

Many national statistics offices acknowledge that making better use of existing administrative data can reduce the cost of meeting ongoing statistical needs. Stats NZ has developed a framework to help facilitate this reuse. The framework is an adapted Total Survey Error (TSE) paradigm for understanding how the strengths and limitations of different data sets flow through a statistical design to affect final output quality. Our framework includes three phases: 1) a single source assessment, 2) an integrated data set assessment, and 3) an estimation and output assessment. We developed a process and guidelines for applying this conceptual framework to practical decisions about statistical design, and used these in recent redevelopment projects. We discuss how we used the framework with data sources that have a non-statistical primary purpose, and how it has helped us spread total survey error ideas to non-methodologists.

Suggested Citation

  • Reid Giles & Zabala Felipa & Holmberg Anders, 2017. "Extending TSE to Administrative Data: A Quality Framework and Case Studies from Stats NZ," Journal of Official Statistics, Sciendo, vol. 33(2), pages 477-511, June.
    • Handle: RePEc:vrs:offsta:v:33:y:2017:i:2:p:477-511:n:9
    DOI: 10.1515/jos-2017-0023
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    References listed on IDEAS

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    1. Marc Roemer, 2002. "Using Administrative Earnings Records to Assess Wage Data Quality in the March Current Population Survey and the Survey of Income and Program Participation," Longitudinal Employer-Household Dynamics Technical Papers 2002-22, Center for Economic Studies, U.S. Census Bureau.
    2. Li‐Chun Zhang, 2012. "Topics of statistical theory for register‐based statistics and data integration," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(1), pages 41-63, February.
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