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Patterns of Consent: Evidence from a General Household Survey

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Author Info

  • Stephen P. Jenkins
  • Lorenzo Cappellari
  • Peter Lynn
  • Annette Jäckle
  • Emanuela Sala

Abstract

We analyse consent patterns and consent bias in the context of a large general household survey, the 'Improving survey measurement of income and employment' (ISMIE) survey, also addressing issues that arise when there are multiple consent questions. Using a multivariate probit regression model for four binary outcomes with two incidental truncations, we show that there are biases in consent to data linkage with benefit and tax credit administrative records held by the Department for Work and Pensions, and with wage and employment data held by employers, and also in respondents' willingness and ability to supply their National Insurance Number. The biases differ according to the question considered, however. We also show that modelling consent questions independently rather than jointly may lead to misleading inferences about consent bias. A positive correlation between unobservable individual factors affecting consent to DWP record linkage and consent to employer record linkage is suggestive of a latent individual consent propensity.

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File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.43286.de/dp490.pdf
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Bibliographic Info

Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 490.

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Length: II, 34 p.
Date of creation: 2005
Date of revision:
Handle: RePEc:diw:diwwpp:dp490

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Related research

Keywords: Informed consent; Household surveys; Consent bias; Selection bias; Multivariate probit; Incidental truncation; Data linkage; National Insurance number;

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References

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  1. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
  2. Philip J. Smith & David C. Hoaglin & J. N. K. Rao & Michael P. Battaglia & Danni Daniels, 2004. "Evaluation of adjustments for partial non-response bias in the US National Immunization Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(1), pages 141-156.
  3. Van de Ven, Wynand P. M. M. & Van Praag, Bernard M. S., 1981. "The demand for deductibles in private health insurance : A probit model with sample selection," Journal of Econometrics, Elsevier, vol. 17(2), pages 229-252, November.
  4. repec:ese:iserwp:2004-16 is not listed on IDEAS
  5. Stewart, Mark B & Swaffield, Joanna K, 1999. "Low Pay Dynamics and Transition Probabilities," Economica, London School of Economics and Political Science, vol. 66(261), pages 23-42, February.
  6. Stephen P. Jenkins & Peter Lynn & Annette Jäckle & Emanuela Sala, 2005. "Linking Household Survey and Administrative Record Data: What Should the Matching Variables Be?," Discussion Papers of DIW Berlin 489, DIW Berlin, German Institute for Economic Research.
  7. Peter Lynn & Annette Jäckle & Stephen P. Jenkins & Emanuela Sala, 2005. "The Effects of Dependent Interviewing on Responses to Questions on Income Sources," Discussion Papers of DIW Berlin 487, DIW Berlin, German Institute for Economic Research.
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