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Understanding Society: minimising selection biases in data collection using mobile apps

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  • Annette Jäckle
  • Jonathan Burton
  • Mick P. Couper

Abstract

Understanding Society, the UK Household Longitudinal Study has a programme of research and development that underpins innovations in data collection methods. One of our current focuses is on using mobile applications to collect additional data that supplement data collected in annual interviews. To date, we have used mobile apps to collect data on consumer expenditure, well‐being, anthropometrics and cognition. In this paper, we review the potential barriers to data collection using mobile apps and experimental evidence collected with the Understanding Society Innovation Panel, on what can be done to reduce these barriers.

Suggested Citation

  • Annette Jäckle & Jonathan Burton & Mick P. Couper, 2023. "Understanding Society: minimising selection biases in data collection using mobile apps," Fiscal Studies, John Wiley & Sons, vol. 44(4), pages 361-376, December.
    • Handle: RePEc:wly:fistud:v:44:y:2023:i:4:p:361-376
    DOI: 10.1111/1475-5890.12351
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    References listed on IDEAS

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    3. James Heckman, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    4. Martin O'Connell & Pierre Dubois & Rachel Griffith, 2022. "The Use of Scanner Data for Economics Research," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 723-745, August.
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    1. Michaela Benzeval & Thomas F. Crossley & Edith Aguirre, 2023. "A symposium on Understanding Society, the UK Household Longitudinal Study: introduction," Fiscal Studies, John Wiley & Sons, vol. 44(4), pages 317-340, December.

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